The Big Shift Challenges Both

The 2011 Shift Index Measuring the forces of long-term change

Deloitte Center for the Edge John Hagel III, John Seely Brown, and Duleesha Kulasooriya

Core Research Team Shalini Bhatia Michelle Lally Jonathon Wong Kimberly Korinek Sarah Scharf SJ Lu 2011 Shift Index Measuring the forces of long-term change i

“We are shifting “I believe that most large from a world where organizations today are suffering the key source of from a crippling disease — strategic advantage hierarchical bureaucracy. This disease was in protecting is resulting in remarkable declines and extracting value in long term return on assets, life from a given set of expectancy of firms and engagement knowledge stocks — of people doing the work, as shown by the sum total of what studies such as Deloitte’s Shift Index” we know at any point ~ Knowledge Leader and Best Selling Author, Steve Denning, April 12, 2011 in time, which is now depreciating at an accelerating pace — “Until now, executives have focused into a world in which on two forms of strategic advantage: the focus of value structural and capability-based. creation is effective The Big Shift challenges both. It participation in undermines traditional approaches to knowledge flows” structural advantage by systematically ~ NY Times Columnist, reducing barriers to entry and Thomas L. Friedman, movement.” Published: January 19, 2010 ~ Bloomberg, December 10, 2009, Are Your Sources of Strategic Advantage Eroding?

“Overall, the Deloitte report provides fodder for those, like BusinessWeek’s Michael Mandel, who argue that the woes of the U.S. economy extend beyond the financial sector and began showing up well before the housing bubble.” ~ Business Week, November 23, 2009, Why You’d Better Beware of the Big Shift, By Harry Maurer and Cristina Linblad work from the customer back into your own organization. into your own organization. the customer back work from A product for starters. stream, Consider the revenue means that the big money comes conception for revenues The A from Sale, when the customer buys the product. sum of money is paid at that point, and then lump large as he or she wishes. A the customer uses that product little time or business spends relatively product-focused time comes money with the customer after that, until the for the next sale. This to business. approach is the Push The Things different are in a service-oriented company. of the the inauguration is merely sale of the product with many subsequent interactions customer relationship, And the service-oriented company may offer to to follow. for a stream to the customer in return the product transfer of payments, instead of one initial sum. The company of the stream engaged throughout and customer remain by the Power payments. A clear example of this is GE’s GE’s Hour offering for its jet engines. Under this approach, So GE upfront. rather than customers pay per flight hour, flying, planes are makes money only when the customer’s a In this way, which is when the customer makes money. GE wants to fixed cost is converted to a variable cost. And keep those planes flying every bit as much as its customers Push to Pull. do. From Another important dimension of the Shift Index is the both importance it rightly assigns to openness. People, access a wealth producers, as customers and as creative outside their own of useful knowledge, most of it from is its 1

A lot has changed since the 2010 Shift Index came out. In A lot has changed since has been in nearly continual Euro the no particular order, Spring has toppled crisis for many months; the Arab the Middle East; Occupy Wall across regimes autocratic number inhabit a large and its Occupy brethren Street the US amidst persistently high of city centers across Jobs finally succumbed to a unemployment; and Steve long-term illness, much to the dismay iPad, of Mac, iPod, iPhone (and, one suspects, even PC) users everywhere. valuable one of the most a lot has changed. Yet Yes, that aspects of the 2011 Shift Index is its timely reminder that will drive our many of the most important trends largely remain future economic lives for the foreseeable unchanged. The companies’ profitability, 45 year decline in persists, despite by their declining ROA as measured fluctuations. temporary rate of leadingThe topple firms a rising continues to rise (supplemented, perhaps, by the around political regimes of undemocratic topple rate firms in world). And the competitive intensity confronting So the the global market economy continues to intensify. remain very much identified by the Shift Index trends core before. as they were I elements of the 2011 Shift Index that There three are with my due to their resonance would like to reinforce, explored One that I have recently own research. implications for thinking about one’s business, whether implications for thinking about one’s or a service, as a service business. one makes a product one learns to When one conceives the business this way, Foreword

Foreword Foreword Foreword

four walls. This incredible use and re-use of knowledge Lest this be considered incredibly naïve, consider the most permits both economies of scale and economies of scope. recent quarterly income statements from two leading By opening up its server infrastructure to others, Amazon innovators. One spent 13.4% of its sales on R&D, while Web Services has created a new business that is built on those sales grew 7.3% from a year ago to over $17 billion. the open access it provides to its internal operations. In The other spent only 2.3% of its sales on R&D, yet its sales the process, it spreads its fixed costs over much more grew 39.0% from a year ago to reach over $28 billion. volume (provided by the external customers using the Which organization is getting more results from being infrastructure), making its own costs lower. By allowing connected, from empowered and passionate people, and third party merchants to use amazon’s web page creation from the pull exerted by its customers? While Microsoft tools, amazon achieves economies of scope: customers (the first of these two innovators) is no slouch, few would going to amazon’s site have the same purchasing dispute that Apple (the second innovator) is realizing experience whether they are buying books (stocked by greater leverage from its innovation investments. And Steve amazon) or jewelry (stocked by third party merchants). A Jobs’ passing reminds us all of the value of focusing on the virtuous cycle ensues: the more we purchase, the more individual customer’s experience amidst the overwhelming amazon knows about our buying habits, the more useful panoply of technological possibilities. amazon becomes to us as a shopping destination, and the more attractive amazon becomes to those third party So take the time to read this latest Shift Index, as a guide vendors looking for customers. to what is coming over the longer term. It might help you connect with enduring trends that can carry you past the The final dimension of the 2011 Shift Index I wish to daily distractions and noise, to a more successful business, highlight is its fundamental orientation towards people, with more satisfied customers, thanks to more connected not towards technology. While there is a lot of technology and empassioned people, both inside and outside your in these pages, the whole perspective is anchored in a organization. humanistic approach. Focusing on the passion of your people is vital to effective innovation performance. Being connected, both within your own organization and especially outside to many other people, organizations and institutions, is central to accessing the knowledge flows that bring prosperity. And today’s business empires, or autocratic states, are only temporary structures, destined to be undermined by the fundamental human desire to open up, to connect, to inspire, and to collaborate with Henry Chesbrough one another. Author2 and Professor at the Haas School of Business, UC Berkeley

1 H. Chesbrough, Open Services Innovation: Rethinking Your Business to Grow and Compete in a New Era, (Jossey-Bass: San Francisco), 2011 2 H. Chesbrough, Open Innovation: The New Imperative for Creating and Profiting from Technology (Harvard Business School Press), 2003

Contents

4 Executive Summary

6 2011 Shift Index: Key Themes

20 Big Shift Overview: Context, Findings, and Implications

26 Key Ideas

28 Cross-Industry Perspectives

40 Shift Index in Practice

42 The Shift Index: Numbers and Trends

48 2011 Foundation Index

68 2011 Flow Index

106 2011 Impact Index

149 Shift Index Methodology

171 Appendix

224 Acknowledgements

Read This Focus for New Readers These sections provide a concise introduction to the key ideas behind the Big Shift and this year’s Shift Index. Focus for Seasoned Readers These sections provide new insights and findings captured in this year's Shift Index. Connect the Dots New to this year's release, these journalistic nuggets help bring to life the key metrics of change captured in the Shift Index. Join the Conversation Participate in the debate by posting your opinion on these propositions. Scan the Quick Response (QR) code from your mobile or follow the Uniform Resource Locator (URL). Executive Summary Executive Summary

In the midst of an economic downturn, when it is all too This 2011 release of the Shift Index updates all 25 metrics easy to fixate on cyclical events, there is real danger of and finds new revelations and examples. This year, we also losing sight of deeper trends. Short-term cyclical thinking explore several themes in depth that have influenced our risks discounting or even ignoring powerful forces of thinking on the Big Shift. longer-term change. To provide a clear, comprehensive, and sustained view of the deep dynamics changing our A few of the key themes that we will discuss this year are: world, Deloitte’s Center for the Edge has developed the • ROA performance continues its long-term decline due Shift Index. The Shift Index consists of 3 indices and 25 to deteriorating firm performance. This year, we explore metrics designed to make longer-term performance trends ROA performance in context of two macro trends, more visible and actionable. Mergers & Acquisitions (M&A) activity and declining interest rates, which have been put forth to explain Our first release of the Shift Index in 2009 highlighted (or explain away) the observed decline. Based on our the decline in firm performance that has been playing out analysis, we contend that the declining trend in ROA for decades. Remarkably, in 2009, the Return on Assets reflects fundamental firm performance. (ROA) for U.S. firms had fallen to less than one-third of • Layoffs and other short-term measures taken by firms 1965 levels while improvements in Labor Productivity had are largely the cause of the recent uptick in ROA. modestly improved over the same period. While there As performance pressures mount, firms are reacting has been a modest improvement in ROA over the past by taking short-term measures and pushing hard on couple of years as the downturn eases up, we believe employment and payroll as the principal cost-cutting that this is simply a short-term adjustment similar to the levers. While offering short-term relief, current efforts improvements in ROA seen in previous economic cycles. taken by firms to eliminate jobs are not sustainable The long-term trend is still an underlying reality and there drivers of firm performance going forward. is no reason to believe that these short-term adjustments, • Connected individuals, not companies, are the ones achieved largely through significant layoffs, mark a reversal harnessing flows and have more power because of it. of the long-term trend. Declining information asymmetry, lower switching costs, and emerging trends, such as a technology-enabled Additional findings of our Shift Index include the following: resources sharing, are increasing Consumer Power and • The ROA Performance Gap between winners and losers providing additional options for consumption. While has increased over time, with the “winners” barely individuals are leveraging knowledge flows to increase maintaining previous performance levels, while losers their power in the marketplace, this hyper-connectivity experience rapid deterioration in performance. also drives volatility in the economic, social, and political • The “topple rate,” the rate at which big companies arenas. lose their leadership positions, has more than doubled, • Firms have untapped opportunities to reverse their suggesting that “winners” are in a precarious positions. declining performance by embracing pull. To accomplish • Competitive Intensity in the United States has more than this, firms must develop and encourage passionate doubled during the last 40 years. workers at every level of the organization. Additionally, • While the performance of U.S. firms is deteriorating, companies must tap into knowledge flows and expand the benefits of productivity improvements appear to be the use of powerful tools, such as social software to As used in this document, “Deloitte” means Deloitte LLP captured in part by creative talent, which is experiencing solve operational/product problems more efficiently and and its subsidiaries. Please see greater growth in total compensation. Customers also effectively as well as to discover emerging opportunities. www.deloitte.com/us/about appear to be gaining and using their market power for a detailed description of the legal structure of Deloitte LLP as reflected in increasing Consumer Power and Brand Given these trends, we cannot reasonably expect to see a and its subsidiaries. Disloyalty. significant or sustainable easing of performance pressure • The exponentially advancing price/performance capability as the current economic downturn begins to dissipate — 3 More than just bits and bytes, this digital infrastruc- of computing, storage, and bandwidth is driving an on the contrary, all long-term trends point to a continued ture consists of institutions, adoption rate for our new “digital infrastructure”3 that erosion of performance. So what can be done to reverse practices, and protocols that is two to five times faster than previous infrastructures, these performance trends? together organize and deliver the increasing power of such as electricity and telephone networks. digital technology to business and society.

4 Executive Summary The answer can be found in the three waves of deep In the end, these innovations will lead to a change occurring in today’s epochal “Big Shift.” The first, the “Foundation” wave, involves changes to the fundamental shift in the rationale for institutions fundamentals of our business landscape catalyzed by the emergence and spread of digital technology infrastructure from scalable efficiency to scalable learning and reinforced by long-term public policy shifts toward as firms use digital infrastructure to create economic liberalization. The metrics in our Foundation Index monitor changes in these key foundations and environments where performance improvement provide leading indicators of the potential for change on other fronts. Changes in foundations have systemati- accelerates as more participants join. cally and significantly reduced barriers to entry and to movement, leading to a doubling of Competitive Intensity. where we are in the Big Shift and what to anticipate in the future. Current metrics indicate that we are still in the The second, the “Flow” wave, focuses on the key drivers first wave of the Big Shift and facing challenges in moving of performance in a world increasingly shaped by digital forward into the second. Changes still manifest them- infrastructure. This second wave looks at the flows of selves much more as challenges rather than opportunities knowledge, capital, and talent enabled by the foundational because our institutions and practices are still geared to advances, as well as the amplifiers of these flows. Because earlier infrastructures. At the same time, an understanding of the rapid change, higher unpredictability and volatility of these three waves leads to significant insights about the created by the Big Shift, knowledge flows are a particular moves required to reverse current performance trends: key to improving performance. Developments on this front are lagging behind the foundations metrics because of the • Deeper, yet strategic, restructuring of firm economics time required to understand changes in foundations and to generate maximum possible value from existing develop new practices consistent with new opportunities. resources; • Development of new management practices to more The third, the “Impact” wave, centers on the consequences effectively catalyze and participate in growing knowledge of the Big Shift. Given the time it will take for the first flows; and two waves to play out and manifest themselves, this third • Significant innovation in institutional arrangements to wave—and its related index—provides an even greater drive scalable participation in knowledge flows and reap lagging indicator. While current trends in firm performance the increasing returns to performance improvement. indicate sustained deterioration, we expect, over time, that performance will improve as firms begin to figure out how The Shift Index is updated regularly to track changes over to participate in and harness knowledge flows. Doing so time and measure movement along the Big Shift. We will require significant institutional innovations, not just have designed this year’s Shift Index both as a stand-alone changes in practices, resulting in value creation through summary of the findings to date and as an update for increasing returns performance improvement. In the end, those who have read previous editions. we expect these innovations to lead to a fundamental shift in the rationale for institutions from scalable efficiency to In response to growing interest from executives, the scalable learning as firms use digital infrastructure to create Center for the Edge is also further researching which flow environments where performance improvement accelerates metrics at the individual firm level, could be drivers of as more participants join. Early signs of these changes are performance, ultimately captured in operating and financial visible in emerging open innovation and process network metrics. In particular, we are investigating the ability of initiatives underway today. companies to participate effectively in a larger and more diverse range of knowledge flows, with the intent of iden- The Shift Index seeks to measure these three waves of tifying a set of flow metrics that can be drivers of perfor- deep and overlapping change operating beneath the visible mance metrics for the firm to monitor on an ongoing basis. surfaces of today’s events. The relative rates of change across the three indices can help executives understand

2011 Shift Index Measuring the forces of long-term change 5 Key Themes 2011 Shift Index: 2011 Shift Index: Key Themes

Challenging times and opportunities: Unemployment, volatility, and worker passion in an era of constant change

Introduction infrastructure and its amplifying effect on change. The Big Shift is a story of long-term trends and the Finally, we conclude by discussing how firms can behave increasing pressures on firms in an environment of more like these connected individuals by tapping into constant, and disruptive, change. The Shift Index was knowledge flows and stoking worker passion. By creating developed in 2009 to help describe and quantify the a passionate workforce and giving these workers ample dimensions of the Big Shift. With this third edition of the access to flows of knowledge, corporations can drive Shift Index report, we have updated our 25 metrics and real, sustainable improvement and begin to reverse their gone deeper into a few dimensions of the Big Shift. We long-term performance deterioration. hope to entice new readers and provide fresh perspectives to those we have connected with in the past. We have ROA Continues its Long-Term Decline Due to explored our metrics again, finding new insights and Deteriorating Firm Performance examples, and for each metric, relayed a story that we One of the central themes of the Shift Index, and the topic hope will resonate with the reader and make the metric which generates the most questions each year, is that asset come to life. profitability (ROA) has shown a downward trend over the past four decades; a trend illustrating a steady decline In this foreword, we explore several themes that have in firm performance that not many have even noticed, influenced our thinking on the Big Shift. First we continue much less investigated. Indeed, there continues to be a to explore our most discussed finding: the persistent profound cognitive dissonance around this point: on one decline in firm performance, manifested in declining asset hand, we all acknowledge experiencing increasing stress profitability. We will address two challenges put forth to as performance pressures mount; on the other hand, we explain the decline in Return on Assets (ROA) as a result of seem unwilling to accept that all of our efforts continue to external factors. Analysis of these challenges suggests that produce deteriorating results. they do not explain away the sustained decline in ROA over a period of more than four decades. The challenges to our findings prompted us to undertake additional analyses — to test, re-test, and validate our Next, we add our perspective to the public discourse approach, data, and assumptions. We welcome and around the hot-button topic of unemployment, presenting encourage such conversations as they test our thinking, our findings from the perspective of firms, an often open our minds to new possibilities, and bring us neglected player in this discussion. We argue that cuts to collectively closer to discovering an answer for declining headcount, while providing relief in the short-term, are firm performance. only a temporary balm for more fundamental performance issues. Although such measures may help to explain the In last year’s edition of the Shift Index, we addressed recent upturn in asset profitability, we believe that only by several questions surrounding the decline in ROA for embracing the changes required by the Big Shift can firms the overall economy. We began by analyzing two other be able to reverse their declining performance in the long measures closely related to ROA — Return on Invested run. Capital (ROIC) and Return on Equity (ROE). For each of these proxies, we found a similar downward trend, further This finding, along with the insights provided by our 25 bolstering our argument for declining firm performance. metrics, left us with a question we wished to explore: if The downward trend of ROE was not as dramatic as that knowledge flows are increasing, and firms are not tapping of ROIC or ROA. But, as stated in the 2010 Shift Index, ROE into them, then who is? The answer can be found in what may vary depending on a firm’s capital structure. In short, we refer to as the ‘connected individual.’ In this section, it does not provide the same comprehensive picture of a we discuss the social and economic impacts brought about firm’s fundamental performance as ROA does. by these individuals, testaments to the power of the digital

6 What’s New 1

Exhibit 1: Summary of Forces and Impact on ROA Exhibit 1: Summary of Forces and Impact on ROA

Return = Return on assets (ROA) Assets Need to insert the

starting points2011 Shift Index: of Themes Key all trendlines Economic trend Resulting impact of company Expected impact on ROA trend

• Service-based companies tend to have • Assuming constant returns, as assets Transition from product fewer intangible assets than product-based reduced, ROA should have improved over to service economy companies time

• Depends on the return over time; current impairment rules would not result in write • Firm assets are market valued at point of down of goodwill and certain other intangibles sale, usually resulting in an increase over Increased M&A activity if subsequent performance is equal to or book value being added to the acquiring better than expectations at the acquisition firm’s balance sheets date; therefore, ROA should accurately reflect market performance

• Companies shed assets related to asset- • Assuming constant returns, as assets Outsourcing/ offshoring intensive operations (e.g., manufacturing, reduced, ROA should have improved over call centers) time

• Goodwill and many intangible assets are not • Intangible assets make up a larger portion of Increased importance of amortized. In the absence of impairment total assets and are increasingly important intangible assets writedowns of these assets, ROA should for driving competitive success reflect market performance

Source: Compustat, Deloitte Analysis Source: Compustat, Deloitte Analysis

In addition to investigating these two proxies, we also Although intangibles assets (including but not limited to considered several alternate explanations for the decline Goodwill) have grown from 0.47% of the total asset base in ROA. These included the transition from a product in 1965 to 5.54% in 2010, these intangible assets continue to a service economy and the growing prevalence of to constitute a minor portion of the total asset base. Thus, outsourcing. While these topics provided interesting we do not believe that this increase in intangible assets is a additional dimensions of the changes we are experiencing, primary driver of economy-wide Return on Assets. we ultimately found that the data did not support either 1 © 2011 Deloitte Touche Tohmatsu argument. Again, we returned to our original finding: ROA Interest Rates & ROA is following a downward trend due to the deterioration of The second alternative explanation proposed is that the fundamental firm performance. decline in ROA is a natural and inevitable consequence of declining interest rates over this time period. Proponents In the 2011 edition of the Shift Index, we will continue our of this argue that when rates are low, there are implicitly open dialogue by investigating in greater depth the impact lower expectations on all invested capital. Because of two other challenges we have received. Two common investors cannot get better returns by putting their money objections we address this year are: elsewhere, it eases the performance pressure on assets. On one level, it is easy to understand how one might draw this • Increased M&A activity has driven down ROA by conclusion. Over the past few decades, both interest rates increasing Goodwill and other intangible assets, thus and ROA have shown a strong decline. However, here we growing the asset base denominator of ROA must reinforce our core belief in the value of longitudinal • Lower interest rates have caused the decline in ROA; as study. Though public policy, economic conditions, and the the cost of capital declines, the expected returns on any like may change from decade to decade, creating false invested capital also decreases positives, it is the long-term trends that truly illuminate changes in firm performance and can be used to derive The M&A Challenge sound explanations. First, let us begin by addressing the Mergers & Acquisitions argument. As shown in Exhibit 2, both the absolute Looking at the longitudinal data in Exhibit 3, it becomes number of transactions and the total value of these clear that ROA is not declining as a result of falling interest transactions peaked in 2000 and have been on the decline rates. For the first third of our analysis, from 1965 to 1981, since then. interest rates rose from 4.1% to 16.4%. During this same period, however, ROA declined by almost 30% from 4.7%

2011 Shift Index Measuring the forces of long-term change 7 Key Themes 2011 Shift Index: Join the Conversation The long-term decline in performance is a result of firms’ slow responses to the Big Shift. www.deloitte.com/us/DecliningPerformance What’s New 1

Exhibit 2: M&A Activity and Goodwill Created, ($, Billions), (1992–2011) Exhibit 2: M&A Activity and Goodwill Created ($, Billions) (1992-2011)

700 900

800 600

700 500 per year per 600 )

400 500 ($, Billions ($, 300 400

of M&A transactions M&A of 300 200 per year 200 Number 100 100 Sumof Goodwill Created through M&A Activity

0 0 1992 1997 2001 2005 2009 Number of M&A Transactions Sum of Goodwill Created, $B What’s New 2

Source: Compustat, Deloitte Analysis Source: Compustat, Deloitte Analysis

Exhibit 3: Federal Reserve Interest Rate and Economy ROA (1965-2010) Exhibit 3: Federal Reserve Weighted Annual Interest Rate and Economy ROA, (1965-2010)

18.0% 1981 5.0%

16.0%

14.0% 4.0%

Interest 6.0%

4.0% 1.0% Federal Reserved

2.0% Overall Economy Return

0.0% 0.0% 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 FED Interest Rate ROA Linear (ROA) Linear (Fed Interest Rate (1965-1981) Linear Fed Interest Rate (1981-2010)

Source: Data from Compustat, Deloitte analysis

3 © 2011 Deloitte Touche Tohmatsu to 3.4%. While interest rates and ROA have shown a significant price pressures on more traditional producers. similar trend in recent decades, one cannot draw causality As technology makes sharing knowledge easier and more between the two. Thus, we can assume that ROA decline prevalent, virtual flows will become increasingly important cannot be explained away merely as the result of falling drivers of competition. interest rates. 2011 Shift Index: Themes Key While some firms are embracing Pull tactics, such as In fact, we believe that the declining interest rates of scalable learning, to overcome mounting performance the past two decades may be shielding firms from the pressures, most are still using outdated Push business full effects of the significant decline in performance. practices, reacting to one-off problems rather than finding Because interest rates are so low, investors have had lower innovative ways to circumvent them. These persistent expectations of invested capital. When interest rates rise, issues are only exacerbated in economic downturns- but however, there will be even more pressure on companies how do firms respond in particularly tough times? We to improve their performance. have found that firms by and large are taking short-term measures in an effort to salvage quarterly earnings. Given this analysis, we still contend that the long-term Like plugging holes in a ship, these measures can offer decline in performance is the result of firms’ slow response temporary relief. However, over time, the underlying to the Big Shift. If anything, the imperative to adapt to the structural issues must be addressed if firms want to address changes in the Big Shift will become all the more pressing the real causes of their performance challenges. as interest rates- and expectations- rise in the future. The Layoff ‘Solution’ Layoffs and Other Short-Term Measures Taken by Unemployment is a hot button topic in political discourse, Firms are Largely the Cause of the Recent Upturn media coverage, and around the dinner table. The social in ROA effects of unemployment have been covered from many Performance Pressures are Mounting angles: the long-term impact on youth, the gender divide Take one glance at the Sunday business section, and it is (men have endured three-quarters of job losses since the clear that today’s firms are facing tremendous pressures beginning of 2008), and the disproportionate impact on and scrutiny. It is not simply a matter of a poor economic already hard-hit urban neighborhoods, just to name climate. As our Competitive Intensity metric shows, market a few.4 concentration has steadily decreased, meaning that more and more firms are battling it out for top market shares. A less-discussed topic, however, is the impact on firms. Not only has the intensity of competition increased, but Why are firms laying off workers? What is the effect also the velocity and frequency at which changes are on firm performance? Are these employment trends occurring. As described by our Firm Topple Rate metric, sustainable in the long run? firms are dropping out of their ROA rankings at an increasing rate since 1965. Not only is overall performance Headcount is one of the key levers firms use to improve declining, but firms are finding their time at the top of the performance, particularly in poor economic climates. pile to be all the more tenuous. Payroll expenses primarily accrue to Cost of Goods Sold (COGS) and Selling, General, and Administrative Expense In parallel with Competitive Intensity, Virtual Flows, (SG&A). When a firm lays off workers, the firm’s costs including inter-firm knowledge flows, wireless minutes, decrease, and assuming constant revenue, returns and Internet activity, have risen steadily over time. increase. Thus, ROA will increase following periods of Some participants are harnessing these flows to add heavy layoffs. This made us curious about the relationship significant competitive pressures in the marketplace. between national unemployment (an indicator of the The open source model, for example, was first adopted extent to which companies are using layoffs to achieve in software development and is now gaining traction in financial performance) and ROA. Our analysis shows a other arenas such as Media, Government, and Scientific strong relationship between unemployment and ROA. Research. This model of development, tapping into an increasingly diverse range of virtual flows, has allowed new The data reveals that similar patterns have emerged generations of producers to overcome the limitations of multiple times since 1965 (see Exhibit 4). When cyclical traditional business models by leveraging a vast pool of economic pressures mount on firms, they are forced talent, accelerating the development cycle, and has placed to address the severe and short-term pressure on 4 Peck, Don. “How a New Jobless Era will Transform America.” The Atlantic, March 2010, http://www.theatlantic.com/ magazine/archive/2010/03/how- a-new-jobless-era-will-transform- america/7919/2/?single_page=true 2011 Shift Index Measuring the forces of long-term change 9 What’s New 3 Key Themes 2011 Shift Index:

Exhibit 4: Return on Assets and U.S. Unemployment Rate, (1976–2010) Exhibit 4: ROA and U.S. Unemployment Rate (1976-2010)

’07-’10: Unemployment from ’81-’82: Unemployment from 7.6%-9.7% 4.6%-9.6% 12.0% ’82-’83: ROA from 2.7%-2.8% ’08-’10: ROA from 0.5%-1.7% 4.5%

’00-’03: Unemployment from 4.0%- 4.0% 10.0% 6.0% ’01-’06: ROA from 0.2%-2.2% 3.5%

8.0% 3.0%

2.5% 6.0% 2.0%

4.0% 1.5%

Unemployment Rate (%) ’91-’92: Unemployment from 6.8%- 7.5% 1.0% 2.0% ’92-’96: ROA from 1.6%-2.3% 0.5% Overall(%)Return on Assets Economy

0.0% 0.0% 1976 1980 1984 1988 1992 1996 2000 2004 2008

Unemployment Rate ROA Source: U.S. Bureau of Labor Statistics, Compustat, Deloitte Analysis Source: U.S. Bureau of Labor Statistics, Compustat, Deloitte Analysis

performance. In these times, firms use layoffs as a release competitive economy, companies are seeking to preserve valve, triggering a spike in the unemployment rate. Exhibit profits at the expense of employment. This increasing 4 shows that following a short lag, Return on Assets rises reliance on layoffs is not a sustainable practice in the as well. However, all these efforts to be more efficient, long-run; in order to reverse declining performance, firms take people out, and drive productivity are proving cannot focus solely on short-term, reactive solutions. insufficient in the face of long-term trends. While the Labor Productivity metric has increased by almost 2.5 times from The Automation Paradox 1965 to 2010, firm performance has continued a steady We have argued here that the recent upturn in ROA decline. reflects short-term and largely unsustainable measures rather than the more fundamental changes required 4 While companies have long used layoffs as a means to cut to respond to the mounting pressures of the Big Shift. © 2011 Deloitte Touche Tohmatsu costs, the practice has become especially prevalent in more However, how does one reconcile this with the prevailing recent economic downturns. As explained in a McKinsey belief that automation is driving sustained productivity Global Institute report, management in the 1960’s and growth and making workers dispensable? 1970’s considered labor to be a ‘quasi-fixed’ resource since they had already invested in their training and workers held It is true that firms are finding ways to automate low firm-specific knowledge that was not easily transferable. In complexity, and increasingly, mid-complexity positions. tough times, firms were less likely to lay off large numbers; Indeed, the rapid adoption of self-checkout at retail they were instead willing to take a hit to profit and locations has shown that even some face-to-face customer productivity so that workers could drive recovery faster on interactions can be replaced with technology. However, the back end.5 as shown in Exhibit 6, Fixed Investment IT Spend in 2000 was almost three times as high as in 2010, whereas As shown in Exhibit 5, employment has constituted unemployment was only 4.0%, as compared to 9.6% in an increasingly larger portion of Real GDP loss in each 2010. Given these numbers, it would be difficult to make subsequent recession since the event of 1973-1975. the case that the significant recent increase in layoffs is GDP loss measures the severity of a downturn on a due to a sudden surge in automation. While IT spend macroeconomic level. Firms’ decisions whether or not to rose significantly between 2009 and 2010 in parallel with lay off workers during these recessions dictate the degree the unemployment rate, this increase marked a return to to which employment bears the brunt of the downturn pre-crash levels of investment. and the degree to which firms absorb GDP loss internally, taking a hit to productivity. As shown in a McKinsey Global Firms are seeking increased employment flexibility by 5 James Manyika et. all. “An Institute study, where once companies were shielding relying on short-term, part-time, or contract workers. Economy that Works: Job Creation and America’s Future.” McKinsey workers and absorbing losses themselves, in this globally In particular, routine and administrative tasks are being Global Institute Report. June 2011.

10 Join the Conversation Layoffs are not a sustainable solution to improving long-term firm performance. www.deloitte.com/us/Layoffs 2011 Shift Index: Themes Key

2011 Shift Index Measuring the forces of long-term change 11 What’s New 4 Key Themes 2011 Shift Index:

Exhibit 5: Contribution to Change in Real GDP During Recessions, (1973–2009) Exhibit 5: Contribution to Change in Real GDP During Recessions (1973-2009) Compounded quarterly growth rate peak to trough (%)

100%= -0.65 -0.53 -0.45 -0.27 -0.70 100%

90% 32% 80% 51% 70%

75% 60%

50% 98% 98%

40% 68% 30% 49% 20%

Percentage contributionto change in real GDP (%) 25% 10%

0% 2% 2% 1973-75 1981-82 1990-91 2001 2007-09

Productivity Employment

1 CalculatedNote: Calculated from the onsetfrom ofthe recession onset of to recession trough of GDP.to trough Calculations of GDP. use Calculations real GDP estimate use real (2005 GDP chained estimate dollars) (2005 and chained total em dollars)ployment and (full total-time employment and(full-time part-time) and for workerspart-time) age for 18 workersand over age 18 and over

Source:Source: U.S. U.S. Bureau Bureau of Labor of Labor Statistics, Statistics, U.S. Bureau U.S. Bureau of Economic of Economic Analysis, Analysis, McKinsey McKinsey Global Institute Global Analysis Institute Analysis

pushed out around the world to temporary workers, often and demand from the market, which may translate to a in remote locations, propelled by digital infrastructure and more persistent breed of unemployment, particularly for sites, which make managing virtual resources easier. In low-skilled workers. 2010, the number of part-time workers reached a new high of 19.7% of all employees. According to one survey, The automation and flexible staffing of jobs have largely 2 © 2011 Deloitte Touche Tohmatsu 58% of firms expected to use more part-time, temporary, been focused on routine tasks, and thus, have diminishing or contract employees over the next 5 years.6 returns. There are certainly examples of firms using flexible employment to drive real productivity gains and improve At the same time, there is a growing compensation performance; however, these practices have not been gap between high-skilled and low-skilled work.7 Skilled, widely adopted in the market. Ultimately, most firms or ‘creative class,’ workers are increasingly critical to a are still engaging in Push tactics to deal with immediate firm’s profitability and, as a result, these skilled workers problems. As these companies eliminate jobs, they squeeze have increased bargaining power with their employers, harder on the remaining workers to get more output. reinforced by greater visibility into alternative employment While firms can push hard on employment for the sake options than ever before. As shown in our Returns to of productivity in the short-term, it is not a sustainable Talent metric, creative class workers are garnering higher practice for long-term growth. compensation and market power because of these advantages. As shown in the repeated cycles of unemployment in Exhibit 4, these short-term responses to longer-term Lower skilled workers have less bargaining power and pressures are not sufficient to address the real causes of therefore feel the brunt of the increasing performance declining performance. It is only when firms embrace the

6 James Manyika et. all. “An pressure on companies. Moreover, as jobs return to the institutions and practices required to drive scalable learning Economy that Works: Job Creation economy, they are in highly-skilled service sectors, such and America’s Future.” McKinsey and tap into the digital underpinnings of the Big Shift will Global Institute Report. June 2011. as health care, and not in those industries hardest hit. they be better positioned to see a sustainable upward This means a growing divide between the supply of skills trend in ROA, rather than simply representing cyclical 7 “The Great Mismatch.” The Economist, September 10, 2011.

12 Join the Conversation Consumers are gaining more power than firms because they are quicker to adopt disruptive technologies. www.deloitte.com/us/ConsumerPower What’s New 5 2011 Shift Index: Themes Key

ExhibitExhibit 6: 6:Unemployment Unemployment and Fixed and InvestmentFixed Investment IT Spend ContributionsIT Spend Contributions to Real GDP, (to1997 Real–2010 GDP) (1997-2010)

12.00% 1.00%

0.80% 10.00%

0.60% 8.00%

0.40% 6.00% 0.20%

4.00% 0.00% Unemployment Rate (%)

2.00% IT Contributionsto Real GDP (%) -0.20%

0.00% -0.40% 1997 1999 2001 2003 2005 2007 2009 Unemployment Rate Fixed Investment IT Contributions to GDP

Note:Note: IT Calculated Spend Contribution as the sum to Real of FixedGDP isInvestment calculated asfinal the sumsales of of Fixed Computers, Investment Software, final sales and of Computers,Communication Software, equipment and Communication equipment

Source:Source: Bureau Bureau of Economicof Economic Analysis, Analysis, Compustat Compustat,, Deloitte Deloitte Analysis Analysis

noise. When cyclical economic pressures mount on

Connected Individuals, Not Companies, are firms, they are forced to address the severe Harnessing Flows — and Have More Power Because of It and short-term pressure on performance. In In decades past, the possession and protection of stocks of these times, firms use layoffs as a release valve, knowledge set apart the powerful from the uninformed. Today, however, it is one’s ability to harness flows of triggering a spike in the unemployment rate. knowledge, made possible by the digital infrastructure, which gives advantage. But if companies are not tapping 47% of respondents strongly agreed that there wasn’t into these increasing flows to create value, then who 6 much cost associated with switching between brands. Only © 2011 Deloitte Touche Tohmatsu is? The answer is the “connected individual,” whether 6 and 7% of respondents strongly disagreed with either of acting as individual consumers or as creative talent, who these statements, respectively. Consumers are leveraging harnesses flows to exert power in the marketplace and increased information to make real-time comparisons society in unprecedented ways.. between prices and product features before they even get to the store. And for firms, this means it is more difficult to Consumer Power and the Connected Individual use information asymmetry to their competitive advantage. One clear outcome of this phenomenon is an upward trend in our Consumer Power score, which measures the While consumers perceive themselves as having more value captured by consumers based on the degree to information, we wondered if they were changing their which consumers perceive they have choices, convenient purchasing decisions in a way that affects company access to and information about those choices, access to earnings. According to our Brand Disloyalty metric, customized offerings, the ability to avoid marketing efforts, consumers are starting to view brands in the same and minimal switching costs. In 2011, 49% of consumers categories as more interchangeable. As a result, they surveyed strongly agreed that they have more information are less likely to “buy in” to traditional advertising and about brands and products. And as shown in Exhibit 7,

2011 Shift Index Measuring the forces of long-term change 13 What’s New 6 Key Themes 2011 Shift Index:

Exhibit 7: Consumer Power, (2011)

Exhibit 7: Consumer Power (2011)

Strongly Disagree Strongly Agree

1 2 3 4 5 6 7 Top 2

There are a lot more choices now in this category 1 than there used to be 3% 3% 7% 26% 20% 20% 21% 41%

2 I have convenient access to choices in this category 16% 12% 12% 20% 16% 12% 12% 24% There is a lot of information about brands in this 3 category 3% 3% 5% 21% 19% 22% 27% 49% It is easy for me to avoid marketing efforts 4 7% 5% 10% 26% 16% 17% 18% 35% I have access to customized offerings in this 5 category 9% 7% 9% 27% 17% 16% 15% 31% There is not much cost associated with switching 6 away from this brand 4% 3% 5% 20% 21% 23% 24% 47%

Source: Synovate,Synovate, Deloitte Deloitte analysis analysis

Consumers are leveraging increased information companies use in running their internal applications. Firms such as ZipCar prove how business models based to make real-time comparisons between prices on sharing can both grow the market and capture share from traditional incumbents. A single ZipCar, for and product features before they even get to example, is estimated to replace the need for 15-20 the store. And for firms, this means it is more privately-owned cars, posing a significant threat to car dealerships in addition to the traditional car rental firms.9 difficult to use information asymmetry to their At the same time, ZipCar extends the car rental market to college campuses and other consumers previously competitive advantage. excluded from reliable access to a vehicle. Both rental companies and auto manufacturers have borrowed from are instead leveraging new knowledge flows to alter the ZipCar sharing model in hopes of gaining access to their purchase decisions. Homemakers, who often make these underserved markets. The passage of legislation in purchase decisions for the household, have seen the California that amends insurance law and permits auto 7 © 2011 Deloitte Touche Tohmatsu highest jump in brand disloyalty, suggesting that brands owners to share their private vehicles is a telling example no longer hold the clout for consumers they once did. of how these emerging trends, made scalable by the digital Additionally, consumer trust in firms has declined from infrastructure, are becoming mainstream. 59% in 2008 to 46% in 2011, according to the Edelman Trust Barometer.8 Firms can no longer rely on customers Growing Pains of the Big Shift “shopping blind” and buying out of trust and loyalty. The notion of empowering individuals through knowledge Instead, they must win the hearts and wallets of an transfer is significant and seductive. In a world where increasingly brand-agnostic and mistrustful population. consumers can widely disseminate knowledge and choose their preferred means for acquiring goods and Emerging Trends in Consumer Choice services (buying, renting, borrowing), end-users can push Technology is also enabling other consumer trends, some back on firms, forcing them to be more transparent, to 8 Respondents were posed the of which have significant implications for businesses question “How much do you trust price competitively, and to engage in dialogue with their business to do what is right?” and the market. One such trend is the growth of a customers. While these are positive outcomes of the digital 2011 Edelman Trust Barometer, Edelman, January 2011< http:// ‘sharing economy,’ which is increasing the power of infrastructure, society is experiencing growing pains along www.edelman.com/trust/2011/ collective individuals by providing additional options uploads/Edelman%20Trust%20 the way; today’s increasingly inverted pyramid of power Barometer%20Global%20Deck. for consumption. While the proclivity to share is by no is driving greater volatility in the economic, social, and pdf> 9 Keegan, Paul. “Zipcar- The best means new, technology has enabled the sophisticated political arenas as hyper-connected individuals tap into new idea in business.” CNN coordination of resources, from smartphone applications Money, August 27, 2009. < http:// increased flows of knowledge. money.cnn.com/2009/08/26/news/ for accessing shared car services to the cloud platforms companies/zipcar_car_rentals. fortune/>

14 Exhibit 8: Economy-wide Stock Price Volatility, (1972-2010) Exhibit 8: Economy-wide Stock Price Volatility (1972-2010)

0.030

0.025 2011 Shift Index: Themes Key

0.020

0.015 Standard Deviations 0.010 0.0120

0.005 0.005

0.000 1972 1975 1978 1981 1984 1987 1990 1993 1996 1999 2002 2005 2008 Stock Price Volatility Linear (Stock Price Volatility)

Source: CRSP US Stock Database ©200903 Center for Research in Security Prices (CRSP®), The University of Chicago Booth School of Business, Source:Deloitte CRSP analysis US Stock Database ©200903 Center f or Research in Security Prices (CRSP®), The Univ ersity of Chicago Booth School of Business, Deloitte analy sis

The power of individuals to create market disruptions At the intersection of these social and economic has been put into sharp relief by the global recession. disruptions is a real and growing political volatility, With greater access to information, both factual and characterized by faster cycles of change. As individuals questionable, an already fearful and reactive public is become more empowered, the change they are affecting causing significant and oftentimes unanticipated shifts in has real consequences- both in the United States and economic activity. However, this volatility is not just a side abroad. As Tom Friedman writes, “This globalization/I.T. effect of a poor economic climate; it is an outcome of revolution is also ’super-empowering’ individuals, enabling long-term changes brought about by the Big Shift. them to challenge hierarchies and traditional authority figures — from business to science to government. 2As shownFooter by the Stock Price Volatility index data, there It is also enabling the creation of powerful minorities © 2011 Deloitte Touche Tohmatsu has been a long-term increase in stock price volatility (see and making governing harder and minority rule easier Exhibit 8). The many online and on-air financial gurus that than ever.11 Egypt provides perhaps the most striking have emerged, with their legions of loyal fans, are likely example — leveraging the digital infrastructure, the large one factor contributing to markets movements — at least youth population has banded together and rallied for in the short-run. political reform. The incarceration and trial of Egyptian autocrat Hosni Mubarak for allegedly ordering violence Not only are individual investors capable of driving short- against peaceful demonstrators is a testament to how term fluctuations in the marketplace, groups are also “the power-pyramid is being turned upside down” and leveraging the digital infrastructure in socially disruptive individuals are affecting true change on a national, and ways, generating greater social volatility. The London Riots global, platform.12 and youth flash mobs in Philadelphia demonstrate the power of the digital infrastructure to organize and rally Firms Have Untapped Opportunities to Reverse individuals faster and more visibly than ever before. On Declining Performance by Embracing Pull August 8, 2011, in the heat of the London Riots, 1 in every As of today, individuals have largely been the beneficiaries 170 U.K. internet visits was to Twitter, and the Twitter of flows, leveraging them to increase their own power and 10 “London Riots cause traffic spike on Twitter.” Experian Hitwise. handle ‘LondonRiot’ received over 1.1 million tweets.10 drive change. And for firms caught in a long-term trend of August 9, 2011. < http:// weblogs.hitwise.com/james- While demonstrations and rallies were disruptive social declining performance, this transfer of power to end-users murray/2011/08/london_riots_ forces throughout the 20th century and much earlier, the is certainly a driver of increasing performance pressure. cause_traffic_spi.html> 11 Friedman, Thomas. “A Theory of digital infrastructure allows impassioned individuals to However, companies have untapped opportunities to “act Everything (Sort Of).” New York Times, August 13, 2011 < http:// disseminate knowledge faster, stoke the emotions and like consumers” and reverse their declining performance. www.nytimes.com/2011/08/14/ interests of others, and catalyze unrest at a pace and scale To accomplish this, firms must consider fostering opinion/sunday/Friedman-a- theory-of-everyting-sort-of. previously unthinkable. passionate workers at every level of the organization. html?_r=3&ref=unemployment> 12 Ibid. 2011 Shift Index Measuring the forces of long-term change 15 Key Themes 2011 Shift Index: Join the Conversation Worker Passion drives interfirm knowledge flows, which can significantly improve firm performance. What’s New 8 www.deloitte.com/us/WorkerPassion

Exhibit 9: Passion and Questing Disposition, (2011)

Exhibit 9: Passion and Questing Disposition (2011)

80% 72% 70% 61% 60%

50% 48%

40% 36%

30%

20%

Percentage of respondents by disposition 10%

0% Disengaged Passive Engaged Passionate When asked how they would respond to an unexpected challenge responded ‘Energized’ or ‘Inspired' Source: 2011 Deloitte Worker Passion/Inter-firm Knowledge Flow Survey (n=3108); Administered by Synovate

Source: 2011 Deloitte Worker Passion / Inter-firm Knowledge Flow Survey (n=3108); Administered by Synovate Additionally, companies should consider tapping into keep an eye fixed on developments across a broad range knowledge flows and expanding the use of powerful tools of industries, game changers, and new ideas — as they such as social software. no longer enjoy the luxury of time to exploit accrued knowledge to generate value for an indefinite period. One lesson we take from the Egyptian youth is how individuals with passion and access to knowledge flows In this competitive atmosphere where time-to-market is can collaborate to create change. If a similar equation, critical, creating and retaining passionate workers provides passion + flows, was applied to workers within an a strong competitive advantage to firms. Passionate organization, firms could begin to reverse declining workers drive sustained performance improvement, inspire performance. They can accomplish this by tapping into innovation and possess both a “questing” disposition, knowledge flows and expanding the use of powerful tools which drives them to seek out new sources of knowledge, 9 © 2011 Deloitte Touche Tohmatsu such as social software to support and foster passionate and a “connecting“ disposition, which drives them to build workers at every level of the organization. relationships within the organization and outside of its walls to tap into the latest thinking and insights. Why is Passion Important? What, exactly, is worker passion, and why is it important When asked how they respond to unexpected challenges, to firms? Worker passion, different from employee the passionate employee most often responded that they satisfaction, denotes a strong desire to continually improve are inspired (seeing an opportunity to learn something performance. More than being satisfied with their current new) or energized (seeing an opportunity for problem job, passionate employees constantly seeking to stimulate solving) rather than being indifferent or exhibiting negative new thinking and creativity. behaviors. The passionate are twice as likely (72% versus 36%) as disengaged workers to express this disposition As cycles for innovation and knowledge creation speed (See Exhibit 10). The questing disposition drives higher up in today’s world, the stocks of knowledge held by performance as passionate workers do not shy from any one organization or institution rapidly depreciate. challenges and actively pursue opportunities to blend new Further, competition continues to intensify as technology ideas from across companies, industries and disciplines into based platforms make replication of services and solutions their current work (see Exhibit 9). easier and faster. In this environment, companies must

16 As the rate of change in the business environment The U.S. labor force is projected to reach 166.9 million by increases, the passionate worker is most apt to adjust and 2018, an 8.2% increase from the 2008, with an increasing thrive, and will likely foster those behaviors within their proportion of older workers. Workers aged 55 years and 2011 Shift Index: Themes Key companies. They view challenges as exciting opportunities older will make up 23.9% of the labor force, up from to drive themselves to a new level of performance. 18.1% in 2008. Meanwhile workers aged 16 to 24 are Employees who are not passionate tend to experience expected to make up only 12.7% of the labor force (down unexpected challenges as a source of stress and are from 14.3%), and the primary working-age group, those increasingly likely to burnout and become a drain on the between 25 and 54 years old, is projected to decline to organizational vitality. 63.5% (from 67.6%).

In addition to thriving in challenging environments, The ability to ignite and sustain the passion of senior passionate workers also seek out connections with others workers is becoming more and more important as who are relevant to their work and to their continuing the labor force ages. Organizations should explore efforts to find and overcome performance challenges opportunities to retain retiring employees as advisors Looking at proclivity to engage in a range of inter-firm within the company. Passionate older workers could be knowledge flows, from social media and news alerts to assigned roles where they can focus their energies on conferences and professional organizations, as well as taking performance challenges that have a measurable frequency of engagement, passionate workers are twice effect on the company. This can eliminate the need for as likely to participate in knowledge flows as disengaged workforce reductions, and may allow for faster return employees. Our Shift Index suggests that effective on asset gains in periods of economic recovery and participation in an increasing range of diverse knowledge strengthening the organization in the long run. flows will be a key driver of performance improvement in the Big Shift — as employees seek to bring external Social Software & Knowledge Flows thinking into the organization to cross-pollinate ideas. Worker passion will be crucial for firms as they seek to Workers who lack passion and who self select out of inter- compete in a globally connected and evolving service firm or intra-firm knowledge flows will likely find their value economy. A second critical element, as discussed earlier, diminished over time as they vainly draw on aging stocks is providing workers with access to flows that can drive of knowledge to try to deliver results for a shifting world. real, sustainable value throughout the organization. For firms, social software is a powerful, and under-utilized, What’s New 9 The Future of Worker Passion tool as they seek to leverage flows more effectively. While An important consideration for companies is the need to current technologies like ERP software are excellent tools draw out the passion of workers of all ages and enable for standard processes, and are geared towards scalable them to tap into knowledge flows. efficiencies, these technologies are ill-adapted to handle Exhibit 10: Passion and knowledge flows, (2010–2011)

Exhibit 10: Passion and knowledge flows (2011, 2010)

25 21.8 20.9 20 17.6 16.6 14.9 15 12.8 10.7 9.8 10

5 firm Knowledge Flow Index score Index Flow Knowledge firm - Inter

0 Disengaged Passive Engaged Passionate 2011 2010

Source: 2010, 2011 Deloitte Worker Passion/Inter-firm Knowledge Flow Survey; Administered by Synovate 2011 Shift Index Measuring the forces of long-term change 17

Source: 2010, 2011 Deloitte Worker Passion / Inter-firm Knowledge Flow Survey; Administered by Synovate

Exhibit 11: Percent of Labor Force by Age Group, (2011) Exhibit 11: Percentage of Labor Force by Age Group

25 23.9 22.7 23.3 21.6 22.1 20.8 20.6 20 18.1

14.3 15 12.7 of Labor Force

Percentage Percentage 5

0 16 to 24 25 to 34 35 to 44 45 to 54 55 years and older 2008 2018 (projected)

Source:Source: Bureau Bureau of Labor of Labor Statistics Statistics

Lighter, more nimble firms are often better inter-firm knowledge flows. Of front line workers surveyed, 30% do not participate in any inter-firm knowledge flows, positioned to more quickly to translate these virtual or physical (e.g., conferences and lunch meetings). Firms stand to reap tremendous benefits if they can expand disruptive technologies into new practices, participation through adoption of social software tools and therefore, will likely be among the first to throughout the organization. OSIsoft, a data solutions company, experienced a 22% improvement in average garner the business benefits. issue resolution time after deploying a Socialtext workspace (wiki) for their customer-facing technical support team and 14 non-standard business transactions, or “exceptions,” which engineering units.

3 are increasingly common in business operations. These © 2011 Deloitte Touche Tohmatsu one-time events, which can be time sensitive and resource Prior to the wiki, OSIsoft had no central repository for intensive to handle, are unwieldy to resolve via traditional expert knowledge and employees relied upon word-of- means. mouth connections to resolve issues. Moreover, the expert knowledge they did have was static and generic, rarely Social software tools, on the other hand, have a uniquely offering the level of detail and specificity needed to handle relevant set of capabilities to address the exceptions. The exception cases. E-mail was the primary tool for collecting real-time and borderless nature of social software makes it and exchanging knowledge, so any documentation of well-suited for organizations to identify expertise, facilitate how to resolve an issue was privately held and not easily cross-boundary communication, preserve institutional available to other engineers when they encountered similar memory, harness distributed knowledge and create new issues. With the wiki, OSIsoft was successful in creating knowledge. In short, social software can give companies a single, easily accessible source of reliable customer the ability to solve problems more efficiently and with solutions that represented a breadth of issues and up-to- better results — while discovering new opportunities. date information.

Although social software is an invaluable tool in an Knowledge flows and worker passion might seem like 13 The survey defined participation amorphous concepts, but firms can gain tangible results in social media as “Using social increasingly connected world, today, it is largely relegated media to connect with other to consumer-facing functions. As shown in Exhibit 12, by engaging and supporting workers at every level of professionals (e.g., Blogs, Twitter, the organization and giving them the tools and channels LinkedIn).” While we intend for 62% of marketing professionals surveyed use social media, this metric to capture the use of to drive scalable learning. Of course, simply investing in social software for business, we but only 34% of accounting/finance professionals tap into recognize that this terminology this flow.13 Further, while companies do not explicitly ban social software is not sufficient to turn around almost four is not yet commonplace and that decades of deteriorating performance. However, it is a the definition of ‘social media’ is social media (only 16% of respondents reported that it subject to interpretation by the promising tool to help amplify knowledge flows within survey respondent was banned), they are not using it effectively (only 22% of 14 Miller, Megan, Aliza Marks, respondents reported that social media is used internally). and across institutions. Companies that fall behind in the and Marcelus DeCoulode. deployment of this technology are likely to increasingly fall “Social Software for Business The Deloitte Inter-Firm Knowledge flow survey indicates Performance.” Deloitte Publication, behind in a world of accelerating change. 2011. that front line workers are the least likely to participate in

18 Join the Conversation The digital infrastructure will likely increase the frequency and scope of social volatility. www.deloitte.com/us/SocialVolatility 2011 Shift Index: Themes Key

Of course, the adoption of new technology in and of Creating a new set of indices is not a straight-forward or itself is not sufficient to reverse declining performance. simple process. Through our discussions and analysis we Corporations will first have to “unlearn” certain practices continue to refine our perspective on the metrics that make in order to leverage the digital infrastructure as individuals up the Index. When we set out on this journey, more than have done to increase their own market power. Lighter, anything else, we wanted to serve as a catalyst to re-focus more nimble firms are often better positioned to more attention on longer-term trends that, ultimately, have a quickly to translate these disruptive technologies into new much more profound effect on the markets and society practices, and therefore, will likely be among the first to we work and live in than the short-term changes that garner the business benefits. As these new practices scale dominate our media attention. we may see the emergence ‘institutional’ innovations significant enough to improve aggregate firm performance. Our goal, in part, is to motivate others to join us on this These new innovations in turn could drive new practices journey as we continue to develop and refine the analytics in a recursive and positively reinforcing manner to reverse and insights that capture these longer-term changes. decreasing returns. We invite everyone to undertake additional research to test, challenge, refine, and add to the metrics we have The Journey Continues… presented. From our first conception of the Shift Index, our view was What’s New 11 that traditional economic indicators did not accurately In that spirit, it is our pleasure to present the 2011 Shift capture the long-term shifts that are producing a world of Index. We welcome your thoughts and questions. Let the constant change and increasing performance pressures. discussion continue.

Exhibit 12: Social media usage by position, (2011) Exhibit 12: Social media usage by position (2011)

70% 62% 60%

50% 47% 45% 39% 40% 38% 37% 34% 30% 30% 27% 23%

20%

10% Percentage of respondents by position

Note: Based on use of social media to connect with other professionals Note:Source: Based 2011 on useDeloitte of social Worker media Passion/Inter-firm to connect with other Knowledge professionals Flow Survey (n=3108); Administered by Synovate Source: 2011 Deloitte Worker Passion / Inter-firm Knowledge Flow Survey (n=3108); Administered by Synovate

2011 Shift Index Measuring the forces of long-term change 19

12 © 2011 Deloitte Touche Tohmatsu To help managers in this decidedly help managers challenging time, we To for understandinghave developed a framework three competitive landscape: in the waves of transformation such as resources, change; flows of foundations for major and knowledge, that allow to enhance productivity; firms and flows on companies the impacts of the foundations what we these factors reflect Combined, and the economy. call business environment. the Big Shift in the global a Shift Index consisting of we have developed Additionally, indicesthree waves of long-term that quantify the three quantifying these By change we see happening today. we seek to help institutional leaders steer a course forces, while helping to minimize distraction from for "true north,” dinshort-term events — and the growing of metrics that them. reflect we face epochal challenges continue to that Today, them will not we take now to address Steps intensify. economic storm but can only help us to weather today’s significant economic value in an also position us to create believe that challenging business landscape. We ever-more and catalyst the Shift Index can serve as a useful compass for the discussions and actions necessary to make this happen.

Introduction: The Shift Introduction: Big on traditionalFocusing business metrics often masks normal sources undercut of change that long-term forces in fact, be a “normal”of economic value. Indeed, may, when the economy heats up again, thing of the past. Even Trends pressure. under will likely remain companies’ returns fundamentally altering the ago are set in motion decades abetted by a new digitalglobal business environment, built on the sustained exponential pace of infrastructure and in computing, storage, performance improvements and bytes bandwidth. This is not just bits infrastructure that and protocols — it consists of institutions, practices, power of and deliver the increasing together organize This power must digital technology to business and society. be harnessed if business is to thrive. the No one, to our knowledge, has yet quantified dimensions by digital of deep change precipitated metrics technologies and public policy shifts. Fragmentary and sporadic studies certainly exist. But nothing yet and sustained view of comprehensive, a clear, captures experience the deep dynamics changing our world. We of short-term economic instead a daily bombardment indicators — employment, inventory levels, inflation, commodity prices, etc.

Findings, and Implications Findings, Big Shift Overview: Context, Context, Overview: Shift Big

Big Shift Overview 20 Big Shift Overview

Select Findings the last 40 years. While the performance of U.S. firms The Shift Index report highlights a core performance is deteriorating, at least some of the benefits of the challenge and paradox for the firm that has been productivity improvements appear to be captured by playing out for decades. ROA for U.S. firms has steadily creative talent, which is experiencing greater growth in fallen to almost one-quarter of 1965 levels at the same total compensation. Customers also appear to be gaining time that we have seen continued, albeit much more and using power as reflected in increasing customer modest, improvements in Labor Productivity. While disloyalty toward brands. this deterioration in ROA has been particularly affected • The exponentially advancing price/performance capability by trends in the financial sector, significant declines in of computing, storage, and bandwidth is driving an ROA have occurred in the rest of the economy as well. adoption rate for the digital infrastructure that is two to Some additional findings that highlight the performance five times faster than previous infrastructures, such as challenges facing U.S. firms include the following: electricity and telephone networks.

• The gap in ROA performance between winners and These findings have two levels of implication. First, the losers has increased over time, with the “winners” barely gap between potential and realized firm performance maintaining previous performance levels, while the losers is steadily widening as productivity grows at a rate far experience rapid deterioration in performance. slower than the underlying performance increases of the • The “topple rate,” at which big companies lose their digital infrastructure. Potential performance refers to the leadership positions, has more than doubled, suggesting opportunity companies have to harness the increasing that “winners” have increasingly precarious positions. power and capability of the digital infrastructure to create Some of them dropped out of the market during the higher returns for themselves as they achieve even higher 12 recent economy downturn, which temperately raised the levels of productivity improvement through product, average ROA of the bottom players. process, and institutional innovations. • U.S. Competitive Intensity has more than doubled during D Exhibit 13: Firm performance metric trajectories, (1965-2010)

Exhibit 13: Firm performance metric trajectories (1965-2010)

Present

1965

Linear (Labor Productivity) Linear (Competitive Intensity) Linear (Return on Assets) Linear (Topple Rate)

Source: Deloitte analysis Source: Deloitte analysis

2011 Shift Index Measuring the forces of long-term change 21

Second, the financial performance of the firm continues to and delivered to markets. In other words, change occurs in deteriorate as a quickly evolving digital infrastructure and distinct waves that are causally related. public policy liberalization combine to intensify competition (Recent regulatory moves to the contrary, the To quantify these waves, we broke the corresponding overwhelming policy trend since World War II has been Shift Index into three separate indices. In this section, we toward reducing barriers to entry and movement in terms will explain each wave and the metrics we have chosen to of freer trade and investment flows as well as deregulation represent it. of major industries). The benefits from the modest productivity improvements companies have achieved The first wave involves the fast-moving, relentless evolution increasingly accrue not to the firm or its shareholders, but of a new digital infrastructure and shifts in global public to creative talent and customers, who are gaining market policy that have reduced barriers to entry and movement, power as competition intensifies. enabling vastly greater productivity, transparency, and connectivity. Consider how companies can use digital How do we reverse this trend? For precedent and technology to create ecosystems of diverse, far-flung users, inspiration, we might look to the generation of companies designers, and suppliers in which product and process that emerged in the early 20th century. As Alfred Chandler innovations fuel performance gains without introducing and Ronald Coase later made clear, these companies too much complexity. This wave is represented in the first discovered how to harness the capabilities of newly index of the Shift Index — the Foundation Index, which emerging energy, transportation, and communication quantifies and tracks the rate of change in the foundational infrastructures to generate efficiency at scale. Today’s forces taking place today. companies must consider how to make the most of our own era’s new infrastructure through institutional The Foundation Index reflects new possibilities and innovations that shift the rationale from scalable efficiency challenges for business as a result of new technology to scalable learning by using digital infrastructure to create capability and public policy shifts. In this sense, it is a environments where performance improvement accelerates leading indicator because it shapes opportunities for new as more participants join, as illustrated in various kinds of business and social practices to emerge in subsequent emerging open innovation and process network initiatives. waves of change as everyone seeks to explore and master Only then can the corporate sector generates greater new potentialities. However, business will also be exposed productivity improvement from the rapidly evolving digital to challenges as a result of increased competition. Key infrastructure and capture their fair share of the ensuing metrics in this index include the change in performance rewards. As this takes place, the Shift Index will turn from of the technology components underlying the digital an indicator of corporate decline to an indicator that infrastructure, growth in the adoption rate of this reflects powerful new modes of economic growth. infrastructure, and the degree of product and labor market regulation in the economy. Three Waves; three Indices The trends reported above, and the connections across The second wave of change, represented in the second them, are consistent with the theoretical model we used index in the Shift Index, the Flow Index, is characterized to define and structure the metrics in the Shift Index. The by the increasing flows of capital, talent, and knowledge Shift Index seeks to measure three waves of deep and across geographic and institutional boundaries. In this overlapping change operating beneath the visible surfaces wave, intensifying competition and the increasing rate of of today’s events. In brief, this theoretical model suggests change precipitated by the first wave shifts the sources of that a first wave of change in the foundations of our economic value from “stocks” of knowledge to “flows” of business and society are expanding flows of knowledge new knowledge. in a second. These two waves are expected to intensify competition in the near term and put increasing pressure Knowledge flows — which occur in any social, fluid envi- on corporate performance. Later, institutional innovations ronment where learning and collaboration can take place emerging in a third wave of change is expected to harness — are quickly becoming one of the most crucial sources the unique potential of these foundations and flows, of value creation. Facebook, Twitter, LinkedIn, Yammer, improving corporate performance as more value is created Google+, and other social media can foster them,

22 Big Shift Overview as do virtual communities and online discussion forums flows. That is why we give such prominence to them in the and companies situated near one another, working on second wave of the Big Shift. The number and quality of similar problems. Twentieth-century institutions built and knowledge flows at a firm — partly determined by protected knowledge stocks — proprietary resources its adoption of openness, cross-enterprise teams, and that no one else could access. The more the business information sharing — will be key indicators of its ability environment changes, however, the faster the value to master the Big Shift and turn performance challenges of what you know at any point in time diminishes. In into opportunities. The ultimate differentiator among this world, success hinges on the ability to participate companies, though, may be a competency for creating in a growing array of knowledge flows in order to and sharing knowledge across enterprises. Growth in rapidly refresh your knowledge stocks. For instance, intercompany knowledge flows will be a particularly when an organization tries to improve cycle times in important sign that firms are adopting the new institutional a manufacturing process, it can find far more value in architectures, governance structures, and operational problem solving shaped by the diverse experiences, practices necessary to take full advantage of the digital perspectives, and learning of a tightly knit team (shared infrastructure. through knowledge flows) than in a training manual (knowledge stocks) alone. The final wave — captured by the Impact Index — reflects how well companies are exploiting foundational Knowledge flows can help companies gain competitive improvements in the digital infrastructure by creating and advantage in an age of near-constant disruption. The sharing knowledge — and what impacts those changes software company SAP, for instance, routinely taps more are having on markets, firms, and individuals. For now, than 1.5 million participants in its Developer Network, institutional performance is broadly suffering in the face which extends well beyond the boundaries of the firm. of intensifying competition. But over time, as firms learn Those who post questions for the network community how to harness the digital infrastructure and participate to address will receive a response in 17 minutes, on more effectively in knowledge flows, their performance can average, and 85% of all the questions posted to date improve. have been rated as “resolved.” By providing a virtual platform for customers, developers, system integrators, Differences in approach between top performing and service vendors to create and exchange knowledge, and underperforming companies are telling. As some SAP has significantly increased the productivity of all the organizations participate more in knowledge flows, we participants in its ecosystem. should see them break ahead of the pack and significantly improve overall performance in the long term. Others The metrics in the Flow Index capture physical and virtual still wedded to the old ways of operating are likely to flows as well as elements that can amplify a flow — deteriorate quickly. examples of these “amplifiers” include social media use and the degree of passion with which employees are This conceptual framework for the Big Shift underscores engaged with their jobs. This index represents how quickly the belief that knowledge flows are expected to be the individual and institutional practices are able to catch up key determinant of company success as deep foundational with the opportunities offered by the advances in digital changes alter the sources of value creation. Knowledge infrastructure. The Flow Index illustrates a conceptual way flows thus serve as the key link connecting foundational to represent practices. Given the slower rate at which changes to the impact that firms and other market social and professional practices change relative to the participants will experience. digital infrastructure, this index will likely serve as a lagging indicator of the Big Shift, trailing behind the Foundation To respond to the growing long-term performance Index. It will be useful to track the degree of lag over time. pressures described earlier, companies should consider how to design and then track operational metrics showing how The good news is that strong foundational technology well they participate in knowledge flows. For example, is enabling much richer and more diverse knowledge companies might want to identify relevant geographic flows. The bad news is that mind sets and practices tend clusters of talent around the world and assess their access to hamper the generation of and participation in those to that talent. In addition, they might want to track the

2011 Shift Index Measuring the forces of long-term change 23 Big Shift Overview

number of institutions with which they collaborate to suggests a potential red flag for institutional leaders — improve performance. Success against these metrics can companies appear to have difficulty holding onto provide a clue as to how well companies will perform later passionate workers. as the Big Shift continues to unfold. But management can play an important supporting role, Implications for Business Executives recognizing that passionate employees are often talented Our research findings highlight the stark performance and motivated, but also tend to be unhappy because they challenges for companies. What is more, the data suggest see a lot of potential for themselves and their companies, that unless firms take radical action, the gap between although they can feel blocked in their efforts to achieve their potential and their realized opportunities will likely it. Management should consider identifying those who grow wider. That is because the benefits from the modest are adept participants in knowledge flows, providing productivity improvements that companies have achieved them with platforms and tools to pursue their passions, increasingly accrue not to the firm or its shareholders, but equipping them with proper guidance and governance, to creative talent and customers, who are gaining market and then celebrating their successes to inspire others. power as competition intensifies. Performance pressures will continue to increase well past Until now, companies were designed to become more the current downturn. As a result, beneath these surface efficient by growing ever larger, and that is how they pressures are underlying shifts in practices and norms created considerable economic value. However, the rapidly that are driven by the continuous advances in the digital changing digital infrastructure has altered the equation: As infrastructure: stability gives way to change and uncertainty, institutions must increase not just efficiency, but also the rate at which • A rich medium for connectivity and knowledge flows they learn and innovate, which, in turn, can boost their is emerging as Wireless Subscriptions have increased rate of performance improvement. Scalable efficiency, as from 1% of the U.S. population in 1985 to over 90% in mentioned above, must be replaced by scalable learning. 2010, growing at a 20% compound annual growth rate The mismatch between the way companies are operated (CAGR). As a result of technology advances in the areas and governed on the one hand and how the business of computing, storage, and bandwidth, innovations, landscape is changing on the other helps to explain why such as 3G and emerging 4G wireless networks, and returns are deteriorating while talent and customers reap more powerful and affordable access devices, such as the rewards of productivity. smartphones and tablets, the line between the Internet and wireless media will continue to blur, moving us to a In contrast to the twentieth century — when senior world of ubiquitous connectivity. management decided what shape a company should take • Practices from personal connectivity are bleeding over in terms of culture, values, processes, and organizational into professional connectivity — institutional boundaries structure — we now see institutional innovations largely are becoming increasingly permeable as employees propelled by individuals, especially the younger workers, harness the tools they have adopted in their personal who put digital technologies, such as social media, to their lives to enhance their professional productivity, often most effective use. Findings from our research indicate without the knowledge of, and sometimes over the a correlation between the rapidly growing use of social opposition of, corporate authorities. media and the increasing knowledge flows between • Talent is migrating to the most vibrant geographies and organizations. institutions because that is where individuals can improve their performance more rapidly by learning faster. Our Worker passion also appears to be an important amplifier: analysis has shown that the top 10 creative cities have When people engage with their work and push the outpaced the bottom 10 in terms of population growth performance envelope, they seek ways to connect with since 1990. Between 1990 and 2008, the top 10 creative others who share their passion and who can help them cities grew more than twice as fast as the bottom 10. improve faster. Self-employed people are more than twice as likely to be passionate about their work as those who work for firms, according to a survey we conducted. This

24 • Companies appear to have difficulty holding onto improvements promised by technology is to jettison Big Shift Overview passionate workers. Workers who are passionate about management’s distinction between creative talent and their jobs are more likely to participate in knowledge the rest of the organization. All workers can continually flows and generate value for their companies — on improve their performance by engaging in creative average, the more passionate participate twice as much problem solving, often by connecting with peers inside as the disengaged in nearly all the knowledge flows and outside the firm. Japanese automakers used elements activities surveyed. We also found that self-employed of this approach with dramatic effects on the bottom line, people are more than twice as likely to be passionate turning assembly line employees from manual laborers into about their work as those who work for firms. The problem solvers. current evolution in employee mindset and shifts in the talent marketplace require new rules on managing and At the end of the day, the Big Shift framework puts a retaining talent. number of key questions on the leadership agenda: Are companies organized to effectively generate and Leaders must move beyond the marginal expense cuts on participate in a broader range of knowledge flows, which they might be focusing now in order to weather especially those that go beyond the boundaries of the firm? the economic downturn. They need instead to be ruthless How can they best create and capture value from such about deciding which assets, metrics, operations, and flows? And most importantly, how do they measure their practices have the greatest potential to generate long-term progress navigating the Big Shift in the business landscape? profitable growth and shedding those that do not. They We hope that the Shift Index will help executives answer must keep coming back to the most basic question of all: those questions — in these difficult times and beyond. What business are we really in?

It is not just about being lean but also about making smart investments in the future. One of the easiest but most powerful ways firms can achieve the performance

2011 Shift Index Measuring the forces of long-term change 25 Key Ideas Key Ideas

Foundation Index Advances in computing power accelerate the pace of innovation Computing p. 53 The fast moving, relentless evolution of a Plummeting storage costs accelerate the creation of information and the need for Digital Storage new digital infrastructure data filters p. 55 and shifts in global public policy are reducing Low-cost bandwidth bolsters connectivity, enabling consumption of richer data Bandwidth barriers to entry and p. 58 movement Accelerating internet adoption makes digital technology more accessible, increasing Internet Users competitive pressure as well as creating opportunity p. 60

Explosion in wireless communication expands knowledge flow and reach Wireless Subscriptions p. 64

Increasing economic freedom intensifies competition while at the same time Economic Freedom enhancing the ability to collaborate p. 66

Flow Index Individuals are finding new ways to reach beyond the four walls of their organization Inter-Firm Knowledge to participate in diverse knowledge flows Flows p. 74 Sources of economic value are moving from Wireless activity is surging due to demand for mobile data and a growing ecosystem Wireless Activity “stocks” of knowledge of applications and services p. 79 to “flows” of new knowledge Broader availability of Internet access enables “connected-ness” with a growing range Internet Activity of people, resources, and rich content p. 82

Increasing migration suggests virtual connection is not enough — people continue to Migration of People to seek rich and serendipitous face-to-face encounters as well Creative Cities p. 86

Travel volume continues to rise as virtual connectivity supplements, but does not Travel Volume replace in person interactions p. 90

Cross-border capital flows provide an efficient way to access pockets of global talent Movement of Capital and innovation p. 92

Passionate workers are more likely to participate in knowledge flows and generate Worker Passion value for companies p. 96

Social media activity creates scalable ways to connect and tap into knowledge flows Social Media Activity p. 102

26 Key Ideas Key

Impact Index Competitive Intensity is increasing as the digital infrastructure and changing public Competitive Intensity policy erode the barriers to entry and movement p. 111 Foundations and knowledge flows Technological and business innovation, open public policy, and fierce competition, Labor Productivity are fundamentally drive long-term increases in Labor Productivity p. 114 reshaping the economic playing field Digital infrastructures and public policy initiatives amplify Competitive Intensity, Stock Price Volatility market uncertainty, and Stock Price Volatility p. 117

Cost savings and the value of modest productivity improvement tends to get Asset Profitability value from productivity gains are being competed away and captured by p. 120 customers and talent

Winning companies are barely holding on, while losers experience rapidly ROA Performance Gap deteriorating performance p. 124

Big companies are losing their leadership position at an increasing rate Firm Topple Rate p. 128

Shareholder returns for market “winners” increase at a modest rate; while “losers” Shareholder Value Gap destroy more value than ever before p. 131

Greater access to information and choices boost Consumer Power Consumer Power p. 134

Brand Disloyalty is increasing among consumers, particularly the younger generation Brand Disloyalty p. 138

Talented workers garner higher compensation and market power as their value and Returns to Talent career options expand p. 142

Executive Turnover is increasing as performance pressures rise Executive Turnover p. 145

2011 Shift Index Measuring the forces of long-term change 27 Perspectives Cross-Industry Cross-Industry Perspectives

The forces of the Big Shift are affecting U.S. industries at of the value created by productivity improvements. Access varying rates of speed. One set of industries has already to information and greater availability of alternatives been severely disrupted and is suffering the consequences: have put customers squarely in the driver’s seat. Similarly, declining return on assets ROA and increased Competitive creative talent finds itself in a better bargaining position as Intensity.15 A second set, which includes the bulk of talent becomes more central to strategic advantage and U.S. industries, is currently midstream: some are seeing labor markets become more transparent. declining ROA, and others are facing increases in Competitive Intensity, but none have yet encountered How, then, can firms also benefit from the Big Shift? The both. A third, smaller set of as-yet-unaffected industries key is to not only create value, but to capture the value shows little change in performance. created. To do so, firms must learn how to participate in and harness knowledge flows and to tap into the These findings — a follow-up to the macro-level study passion of workers who will be a significant source of released in June 200916 — reflect a U.S. corporate sector value creation as companies shift away from stocks of on a troubling trajectory. The difficulties are more apparent knowledge. This move, from scalable efficiency to scalable in some industries, but all industries will eventually be learning, will be a key to surviving, and thriving, in the subject to the forces of the Big Shift, which represent a world of the Big Shift. fundamental reordering of the economy driven by a new digital infrastructure17 and public policy changes. Most Industries are Feeling the Effects of the Big Shift The industry-level findings are cause for some alarm. U.S. The 2009 Shift Index highlighted trends at the economy- industries are currently more productive than ever, as wide level: declining ROA, increasing Competitive Intensity, measured by increases in Labor Productivity.18 Yet those increasing Labor Productivity. The industry-level findings are improvements have not translated into financial returns. similar. With few exceptions, all U.S. industries are being Underlying this paradox is the growing Competitive affected by the foundational forces of the Big Shift. Intensity in most industries. In some cases, consolidation has helped offset the effect of increasing competition, but One set of industries is already deeply impacted by the it is a short-term solution. Likewise, although firms in most Big Shift.19 These industries have experienced significant industries are investing heavily in technology, the benefits increases in competition and corresponding declines in are short-lived, accruing only until a firm’s competitors do profitability. A middle tier, representing the majority of U.S. the same. industries, is experiencing the early effects of the Big Shift. A third tier consists of two industries that have, so far, The breadth and magnitude of disruption to U.S. been insulated from the forces of the Big Shift. industries, and a trajectory that suggests more disruption to come, call into question the very rationale for today’s In the Eye of the Storm companies. Do they exist simply to achieve ever-lower While most U.S. industries have experienced declining costs by getting bigger and bigger — “scalable efficiency”? ROA, only 4 of the 14 industries evaluated have also Or can firms turn the forces of the Big Shift to their endured a significant increase in Competitive Intensity 15 For further discussion of these metrics, see the metrics section. advantage by focusing instead on “scalable learning” —the (see Exhibit 14). These early entrants into the Big Shift 16 See John Hagel III, John Seely ability to improve performance more rapidly and learn include the technology, media, and telecommunications Brown, and Lang Davison, The 2009 Shift Index: Measuring the faster by effectively integrating more and more participants and automotive industries. They embody the long-term Forces of Long-Term Change (San Jose: Deloitte Development, June, distributed across traditional institutional boundaries? forces that are reshaping the business environment and are 2009). harbingers of the changes to come in other industries. 17 More than just bits and bytes, this digital infrastructure consists U.S. firms can learn two key lessons from the industries of the institutions, practices, and protocols that together organize experiencing early disruption. First, the assumption that In the technology industry, customers have gained power and deliver the increasing power productivity improvement leads to higher returns is flawed: as open architectures and commoditization of components of digital technology to business and society. industries with higher productivity gains do not necessarily have intensified competitive pressure. As a result, the 18 See the metrics section for further discussion experience improvement in ROA. This is the performance industry has experienced a significant deterioration in 19 For further information regarding paradox mentioned earlier. Second, customers and return on assets. survey scope and description, please refer to the Shift Index talented employees appear to be the primary beneficiaries Methodology section.

28 Cross-Industry Cross-Industry Perspectives The media industry has become more fragmented as forms U.S. industries are currently more productive of content proliferate and the long tail becomes ever richer with options. In a very real sense, customers — supported than ever, as measured by increases in Labor by digital infrastructures that enable convenient, low-cost production and distribution of their own content — are Productivity. Yet those improvements have not emerging as competitors to traditional media companies. translated into financial returns.

The telecommunications industry has experienced dramatic Entering the Storm changes over the past two decades. Wireline service, the The industries in this tier have not yet felt the dual impact former mainstay of the industry, is being supplanted by of intensifying competition and declining ROA, but are wireless and voice over Internet protocol (VOIP). Driven by likely to soon. Because these industries were already regulatory changes and increased competition, firms have very competitive in 1965, as measured by industry improved Labor Productivity, but have not realized better concentration (see Exhibit 15), the initial fragmenting financial returns. impact of the Big Shift may have been muted. On the other hand, many of these industries did experience erosion The Automotive industry has struggled with increased of ROA, suggesting that other forms of Competitive global competition as a result of trade liberalization and Intensity were increasing. As we will discuss, the metric robust digital infrastructures that facilitate global for Competitive Intensity does not capture competition production networks. Over the long term, Asset Profitability from other parts of the value chain. One of the pervasive in this industry has decreased as asset growth has themes of the Big Shift is the growing power of customers surpassed income growth. However, following the financial and creative talent and the effect on firms’ profitability as crisis of 2007-2008, we have seen an upward spike in Cross Industry these two constituencies capture more of the value being the industry’s Asset Profitability due to a rise in industry created. Many firms in this tier are subject to this type of Perspectives 1 income. competition. Updated Exhibit 14: Changes in Competitive Intensity and ROA, (1965-2010) Exhibit 14: Changes in Competitive Intensity and ROA (1965-2010)20 20 Insurance and Health Care ROA data is from 1972-2010. Data from 1965-1972 was from a very small 21 Competitive Intensity number of companies for these industries and therefore not truly Decrease Static Increase indicative of market dynamics. Health Care and Aerospace Defense ROA data display some Aerospace & Health Care cyclicality. The increases discussed Defense here are derived from a line fit. Note: industries are classified using Aerospace & self-reported SIC codes and the Increase data is provided by Standard & Defense Poor’s Compustat. 21 Static Competitive Intensity is defined as a change of less than 0.01(+/-) in the HHI. Note that Life Consumer Sciences and Energy are on the 22 Products cusp of increasing Competitive Static Intensity based on actual values ROA versus a line fit. HHI is used in competitive and antitrust law to Energy assess concentration of market Banking & power and is a proxy for competitive intensity (with the notion Securities that markets where power is Aviation Insurance more widely dispersed are more Retail Life Sciences Automotive competitive). As a result, HHI is an

Decrease Process & Media imperfect measure of competi- Industrial Technology tive intensity because it does not Products Telecom. attempt to measure competitive action (such as price wars) between players in an industry. 22 Static ROA is defined as a change Source:Source: Compustat Compustat,, Deloitte Deloitte analysis Analysis of less than 5% (+/-). 2011 Shift Index Measuring the forces of long-term change 29

Updated Exhibit 15: Competitive Intensity, All Industries, (1965-2010) Exhibit 15: Competitive Intensity, All Industries (1965-2010)23

Absolute Industry 1965 Actual 2010 Actual change Industries that began Process & Industrial Products 0.01 0.01 0.00 at higher levels of Consumer Products 0.01 0.02 0.01 Competitive Intensity Banking & Financial 0.02 0.03 0.01 Institutions Aviation & Transport Services 0.03 0.03 0.00 Energy 0.03 0.03 -0.01 Retail 0.03 0.06 0.02 Insurance 0.04 0.04 0.00 Aerospace & Defense 0.04 0.11 0.07 Life Sciences 0.04 0.04 -0.01 Media & Entertainment 0.07 0.02 -0.05 Technology 0.15 0.03 -0.13 Industries that began at lower levels of 0.16 0.08 -0.09 Automotive Competitive Intensity Health Care Services 0.32 0.08 -0.24 Telecommunications 0.37 0.03 -0.34

Source: Compustat, Deloitte analysis Source: Compustat, Deloitte Analysis

The aviation, consumer products, and retail industries all markets surveyed by the American Medical Association in experienced decreasing Competitive Intensity as measured 2010, 99% were dominated by one or two health plans. by industry concentration, although aviation and retail also Limited competition, reinforced by regulatory protection, experienced a decline in ROA.24 Historically, the consumer has sustained Asset Profitability in this industry. products and retail industries were highly competitive; both have experienced significant consolidation among Aerospace & defense appears to be an anomaly, the large firms to combat the margin pressures driven, in only industry that shows no impact from the Big Shift. part, by greater customer power. The consolidation of Improvements in Asset Profitability can be attributed to these two industries is related. As retailers became more consolidation and related scale efficiencies and Labor concentrated, consumer products companies began to Productivity measures as well as a movement from consolidate as a defensive measure to preserve bargaining hardware to software as a source of value. ROA has power with the retailers. Conversely, as consumer products peaked in recent years as a result of historic highs in companies consolidated, retailers felt additional pressure to revenue resulting from wartime spending. The ability of consolidate in order to preserve bargaining power against companies in this industry to capture and retain value has 15 © 2011 Deloitte Touche Tohmatsu the larger consumer products companies. The aviation been supported by the industry consolidation (leading to industry was also competitive, but has recently seen a a decline in one key measure of Competitive Intensity) and spate of consolidation following the economic downturn. high barriers to entry, including technology and capital requirements. Subsidies to incumbents act as a further The Calm Before the Storm barrier to entry, as do burdensome qualifying requirements, This last tier is composed of just two industries that have which require significant upfront investment by new bucked the overall trend and have seen Asset Profitability players just to bid on government contracts. Collectively, increase. The aerospace & defense and health care these factors limit the effects of broader public policy 23 Insurance and Health Care data is from 1972—2010. Data from industries have actually improved ROA to 8.0% and 4.6%, trends towards economic liberalization and enable the 1965—1972 was from a very small respectively. As we will discuss, regulation and public relatively small number of industry participants to achieve number of companies for these industries and therefore not truly policy have played a significant role in shielding these two higher Asset Profitability. indicative of market dynamics. 24 Retail ROA data display some industries from the effects of the Big Shift. cyclicality. The decline discussed For health care, ROA increased while the Competitive The future is uncertain for these two industries. Of the two, here is derived from a line fit. Note also that Consumer Products, with Intensity metric was also increasing. As described in the health care is perhaps more exposed to changes that could a 6% change in ROA, is on the cusp of increasing ROA but is not health care industry section, however, the health plans dramatically reshape the industry: changing legislation, as pronounced as either Aerospace subsector is still dominated by six plans that account medical tourism, new provider delivery and alternative care & Defense or Health Care. for two-thirds of all enrollees. Of the 313 metropolitan options are just a few. In an intriguing parallel, greater 30 Cross-Industry Cross-Industry Perspectives emphasis on prevention of both of these industries may to be, deeply affected by regulation and government represent a major catalyst to accelerate change. In the spending at the national and state levels. Varying state aerospace & defense industry, the rise of asymmetric regulations create a barrier to entry for health plans warfare driven by a new generation of “competitors” will to provide national coverage. Providers too are largely make the industry increasingly susceptible to the Big Shift. regulated at a state level and only a few have a national Success may no longer be achievable through incremental reputation (such as the Mayo Clinic) or a national network improvements and scalable efficiency, but through product (such as some laboratory companies). innovation. The increasing emphasis on advanced software capabilities in intelligence, surveillance, and reconnaissance Thus public policy appears to be the primary determinant perhaps sets the stage for a more fragmented and of the extent to which industries are affected by the Big competitive software-driven industry. Shift. The exponential advances of the digital infrastructure and its broader adoption across the business landscape Technology or Public Policy as Key Differentiators create the potential for competition. Whether or not that This brings us to the question of why industries are potential is realized, however, depends on the regulatory affected by the Big Shift sooner rather than later? All of environment and, in particular, the degree to which public the industries in this report have access to the increasingly policy actively increases barriers to entry (or movement) or ubiquitous digital infrastructure, so the infrastructure helps to reduce them. itself does not appear to be a significant differentiator in how industries are affected. Of course, industries differ in Lessons From The Disrupted terms of how they use the digital infrastructure and how All industries, whether part of the first wave of impact or creatively they rethink their own operations relative to the not, should take note of the trends driving the first tier potential of this infrastructure. In this regard, intensifying of industries. The performance paradox — decreasing competition appears to motivate firms to make the most of profitability in the face of improving productivity — is the infrastructure. A 2002 study found that the impact of prevalent in technology, media, and telecommunications IT investment on productivity growth depended upon the and automotive (see Exhibit 13). presence of one or more competitors that had used IT to develop fundamental innovations in business practices or At an industry level, there appears to be a relationship processes, putting pressure on all companies to replicate between productivity and competition: Industries that have the innovations.25 At the same time, while the digital faced significant increases in Competitive Intensity have infrastructure reduces barriers to entry and movement and also improved their Labor Productivity. For example, the enhances the likelihood that a disruptive innovator can technology industry has experienced one of the greatest change the game, other factors can dampen these effects increases in Competitive Intensity and has improved Labor in an industry. Productivity through advances in technology and business innovations. Industries that are typically on the leading In fact, our findings suggest that public policy significantly edge of innovation and adoption of new practices are most determines the extent to which a given industry is affected likely to experience higher increases in productivity. by the Big Shift. It is not coincidence that aerospace & defense and health care are the least affected industries Unfortunately, productivity is not translating into profits. and are also associated with high levels of regulation and The old assumption that improvements in productivity lead government purchasing. Since 1989, the U.S. government to higher returns turns out to be flawed. An unremitting has accounted for between 40 and 60% of total annual focus on efficiency is no longer sufficient for success. sales in the aerospace & defense industry.26 Procurement Our research suggests that companies are struggling to policies and national security considerations have a retain the value they are creating through productivity profound influence on this industry and its relationship improvements. Some of the most significant increases in with its largest customer — the U.S. government. productivity occurred in industries like telecommunications and technology, where productivity increased upwards 25 "How IT Enables Productivity Growth," McKinsey Global of 800%, yet ROA still declined (see Exhibit 15). These Institute, November 2002. Similarly, the health care industry has been, and continues industries are prime examples of innovation and 26 "Global Military Aerospace Products Manufacturing," IBIS World Industry Report, March 26, 2009. 2011 Shift Index Measuring the forces of long-term change 31 Perspectives Cross-Industry

productivity improvement that did not translate into The Economy Wins but Firms are Losing improved firm performance. The economy, as a whole, is benefitting from greater value creation. In his book, The Power of Productivity,27 Bill Lewis At the other end of the spectrum, we find aerospace & makes a connection between a country’s wealth and its defense. The capital requirements associated with aircraft productivity, but firms are unable to retain the value. As construction and the restrictions tied to manufacturing competition intensifies across all industries, productivity and sales of advanced weapons systems create a unique gains are competed away, and consumers and talented ecosystem within which this industry has managed to workers are reaping the benefits. Consumers and talent improve its ROA. have been able to increase their share of value largely through participation in information flows, which provide While productivity improvements seem to be necessary, greater information and access to alternatives than ever especially in competitive markets, alone they cannot before. sustain, much less improve, profitability. In fact, the rate of ROA deterioration seems to be unrelated to the rate Armed with information and alternatives, consumers of Labor Productivity improvement (see Exhibit 16). There are less loyal than in the past. The digital infrastructure were no industries that experienced both an increase in enables consumers to access a wider range of vendor ROA and a high increase in Labor Productivity. The Big Shift and product options , and to gain information about, requires that companies broaden their focus to include compare, and switch between vendor and product other operating metrics if they want to thrive in an era of options. Choices abound, information is plentiful, and increasing economic pressure. brand loyalty is declining. Want a camera? There are many independent online resources that provide news, reviews, Cross Industry But if improvements in productivity are not showing up and information about digital photography. Need a on the companies’ bottom lines, where are all those gains programmer? Buyers can gain instant access to thousands Perspectives 3 going? What are the implications for industries that are of professionals who offer technical, marketing, and trying to reverse the trend of declining profitability? business services. Updated Exhibit 16: Changes in ROA and Labor Productivity, (1987-2010) Exhibit 16: Changes in ROA and Labor Productivity (1987-2010)

Labor Productivity 28

Moderate Low Increase High Increase Increase

Aerospace & Defense Increase 29 Consumer

ROA Products Static

27 William Lewis, The Power of Aviation Productivity (Chicago: the Energy University of Chicago Press, 2994). Automotive Life Sciences 28 Labor Productivity increase is clas- Banking & Technology Media sified as low, 0 to 50; moderate, Securities Telecom. 50 to 100; or high, >100. Labor Process & Decrease Retail Productivity data is not available Industrial for the Health Care and Insurance Products industries. 29 Static ROA is defined as a change of less than 5% (+/-). Source:Source: Compustat Compustat,, Deloitte Bureau Analy of Labor sis Statistics, Deloitte analysis

1 © 2011 Deloitte Touche Tohmatsu Cross-Industry Cross-Industry Perspectives Similarly, talented workers today are less loyal to their One of the pervasive themes of the Big Shift is employers, often viewing jobs as transactional. Workers use the digital infrastructure to participate in both the growing power of customers and creative information and knowledge flows. For example, where employees once would have used a software program's talent and the effect on firms’ profitability as built-in help function, they now search online to find a these two constituencies capture more of the solution. If a solution is not apparent, a worker can post a question and small communities develop to suggest ideas. value being created. Through participation in these knowledge and information flows, talented workers are learning at a faster pace than pressure for firms as they work harder to meet consumer ever before. In addition, talented workers use the digital demand and attract and retain talent. We expect that infrastructure to connect with their professional network growth in Consumer Power will have a direct effect on to generate and explore job opportunities, including Competitive Intensity within an industry. In this regard, developing new ventures of their own. Talent, particularly Consumer Power and Returns to Talent could be viewed as creative talent, looks for jobs that provide them with the leading indicators of Competitive Intensity. In this context, greatest benefit. In today’s environment, benefits take the Herfindahl-Hirschman Index (HHI), a traditional measure form of fast-paced learning environments and monetary of competition, is more of a lagging indicator. Executives rewards. Talented employees are also gaining power as would be well-served to look at consumer and talent a result of their crucial role in developing and sustaining trends, in addition to direct competitors, to preview the the intangible assets that increasingly drive competitive competitive dynamics of their industries. differentiation and profitability. Our 2010 Shift Index survey offers interesting insights These changing power dynamics will affect all industries, related to the power consumers and talent have today. The including those that were historically less competitive. following sections provide some highlights. As traditional industry boundaries dissolve, competition will emerge from unexpected edges. Consumers will Consumers move fluidly across industry boundaries, looking beyond The Shift Index Consumer Power and Brand Disloyalty traditional providers to find the solutions that meet their survey indicates that few sectors have been spared in any needs. Talent will also look beyond traditional firms for of the metrics evaluated.31 The indices were normalized employment. According to the Intuit Small Business Report to a 0—100 scale — any score over 50.0 indicates that (2007), “Entrepreneurs will no longer come predominantly the majority of respondents believe they have more power from the middle of the age spectrum but instead from the as consumers or are more disloyal towards brands. The edges. People nearing retirement and their children just Consumer Power index values for the consumer categories entering the market will become the most entrepreneurial ranged from 56.3 for newspapers to 72.4 for hotels. 30 generation ever.” Talented workers today have the Similarly, the Brand Disloyalty index values range from 45.0 opportunity to take learning from one industry and apply it for soft drinks to 75.9 for airlines. to others as the digital infrastructure has lowered switching costs in the employment landscape. Consequently, The two major trends underlying Consumer Power are industries that do not offer sufficient monetary rewards more convenient access to alternatives and greater or development opportunities may lose critical talent information about alternatives. Each of these trends as employees flee to other industries. For example, is driven by consumers’ use of digital infrastructure to technology companies participating in e-commerce provide participate in information flows. The ubiquity of devices 30 Steve King, Anthony Townsend, opportunities for retail talent and offer higher monetary (desktops, laptops, mobile, etc.) to access the information, and Carolyn Ockels, "Intuit Future of Small Business Report," January rewards. the increasing richness of the information (descriptions, 2007. 31 The Consumer Power and Brand reviews, comparisons, pricing etc.), along with increased Disloyalty indices were created The power consumers and talent have gained trustworthiness of the source (independent consumers), as the aggregate responses to six questions per each index. While fundamentally changes the competitive landscape. This has destroyed the information asymmetry companies once only categories that were directly shifting power dynamic will lead to increased competitive related to consumers were studied, we assume the impact to industries and firms upstream on the value chain as the disruptions trickle up. 2011 Shift Index Measuring the forces of long-term change 33 Perspectives Cross-Industry

Cross Industry Perspectives 4

Updated Exhibit 17: Consumer17: Consumer Power and Brand Power Disloyalty and Matrix, Brand (2011) Disloyalty Matrix (2011)

100 80.00

Airline 90 75.00

Hotel 80 Home Mass Retailer 70.00 entertainment Department Store Grocery Store 70 Shipping Computer Automobile 65.00 60 Cable/Satellite TV Manufacturer Athletic Shoe Restaurant Gas Station Investment Wireless Carrier 50 60.00 Household Insurance Cleaner (Home/Auto) Gaming System

Brand Disloyalty Snack Chip Brand Disloyalty 40 Pain Reliever 55.00 Magazine

30 Banking Search engine

50.00 Broadcast TV 20 News

45.00 10 Newspaper Soft Drink Cross Industry

0 40.00 Perspectives 5 0 10 20 30 40 50 60 70 80 90 100 55.00 60.00 65.00 70.00 75.00 Consumer Power Consumer Power

Source: 2011 Deloitte Consumer Power/Brand Disloyalty Survey (n=3765); Administered by Synovate Source: 2011 Deloitte Consumer Power/Brand Disloyalty Survey (n=3765); Administered by Synovate Updated Exhibit 18: Consumer Access to Information and Availability of Choices, (2011) Exhibit 18: Consumer Access to Information and Availability of Choices (2011)

80%

60%

50%

40%

30%

20% Percentage of consumersresponding 10%

0% Hotel Airline Banking Shipping Magazine Computer Soft Drink Restaurant Investment Newspaper Snack Chip Gas StationGas Athletic Shoe Pain RelieverPain Mass RetailerMass Grocery Store Search engine Gaming System Wireless Carrier Department Store Cable/Satellite TV Household Cleaner Broadcast NewsTV Home entertainment Insurance (Home/Auto) Automobile Manufacturer There is a lot of information about brands I have convenient access to choices

Source: 2011 Deloitte Consumer Power/Brand Disloyalty Survey (n=3765); Administered by Synovate

34 18 © 2011 Deloitte Touche Tohmatsu Cross-Industry Cross-Industry Perspectives enjoyed. Consumers can now easily compare products and In the future, we expect to see a cross-industry war prices when making a purchase decision. These trends are for more and more categories of talent. This poses a also leading to a lower reliance on brands as an indicator special challenge for those industries that are currently of value and reliability with trusted flows trumping brand in lagging in rewarding talent through faster-paced learning purchasing decisions. environments or higher compensation.

The numbers indicate that consumers perceive themselves Knowledge Flows are Key to Converting Challenges to have significant power in all categories and are relatively to Opportunities disloyal to brands in many categories as well (see Exhibit As the source of economic value creation shifts from stocks 17). The few categories that fall below the midpoint to flows of knowledge, participation in these flows is value for Brand Disloyalty (Newspapers and Soft Drinks) essential if firms are to convert challenges to opportunities. are low-cost items where consumers may not invest a lot Currently, the value that firms create is being captured of time exploring options (see Exhibit 18).32 Some of the by consumers and creative talent: They have harnessed higher-cost categories (Hotel, Airline, Home Entertainment) knowledge flows ahead of the firms and they are reaping fall on the high end of the spectrum for both Consumer the benefits. Firms have an opportunity to participate in Power and Brand Disloyalty. For these categories, the same knowledge flows and networks and to rebalance consumers are participating in information flows to gauge that equation. Participating in knowledge flows will also value and reliability and are consequently becoming more "grow the pie" and move firms away from the zero-sum brand-agnostic. game mindset that drives much of their behavior today.

Talent Participating in knowledge flows can be mutually beneficial The second group of winners from the Big Shift is talented for firms, talent, and consumers. The greater the firm’s employees. The Center for the Edge research shows that participation in knowledge flows, the more value they average total cash compensation to creative talent in the can create. This value will be distributed between firms, United States grew 22% — from $87,000 to $107,000 — talent, and consumers, but as they start offering more from 2003 to 2010. This pattern repeated in all industries, non-monetary value to talent and consumers, firms with growth in total cash compensation for creative talent have an opportunity to retain an increasing share of ranging from 18% in the consumer products and process the monetary value. Talent, particularly the creative and & industrial products industries all the way to 28% in the passionate talent, is attracted to firms that are rich in banking & financial services industry. relationships, generate knowledge flows, and provide tools and platforms to support employee growth and The gap between compensation for creative and non- achievement. A large part of Google’s attraction is its creative workers is also growing.33 Based on the Returns to reputation for allowing employees to grow; special Talent metric, the gap increased 28% over the past eight programs, such as “20% time,” which allows engineers years across the entire U.S. talent pool. Looking at the gap one day a week to work on projects that are not in their across industries provides an equally compelling picture: 12 job descriptions, are magnets for passionate talent. The of the 15 industries had gap increases of 20% or greater. Center for the Edge research shows that, in their quest to learn and create, passionate workers participate in more In a world where industry boundaries are blurring and knowledge flows than their peers. It follows that firms disruptions can come from outside traditional industry that attract the creative and passionate will participate lines, firms are also competing across industry boundaries in increasing volumes of knowledge flows and create for the best talent. Talented employees are likewise more value. Consumers too are attracted to firms that are searching for opportunities across industry boundaries, continuously creating value for them, either in product often applying their learning from one industry to careers features or expanded services, and may be willing to pay a in another. premium for the value. Apple’s ability to maintain a price premium in otherwise commoditized product categories is 32 Although the survey focused primarily on B2C consumer catego- one example. ries, similar trends hold true in B2B categories as well. 33 As defined by Richard Florida; The Rise of the Creative Class (New York: Basic Books, 2003). 2011 Shift Index Measuring the forces of long-term change 35 Perspectives Cross-Industry

Cross Industry Perspectives 6

Updated Exhibit 19: Average Compensation and Compensation Gap, All Industries, (2003-2010) Exhibit 19: Average Compensation and Compensation Gap, all industries (2003, 2010)

Non- Creative Gap Creative Creative Non-Creative Non-Creative Creative Gap Industry Growth Gap (2003) Growth (2003) (2010) (2003) (2010) Growth (2010) (2010) (2010) (2010) Aerospace & Defense $92,885 $115,009 24% $51,753 $61,499 19% $41,132 $53,510 30% Automotive $89,347 $107,439 20% $44,023 $54,679 24% $45,324 $52,760 16% Aviation & Transportation $77,525 $95,739 23% $41,883 $48,498 16% $35,642 $47,241 33% Banking & Financial Services $86,974 $111,090 28% $39,005 $45,605 17% $47,970 $65,485 37% Consumer Products $81,772 $96,484 18% $37,112 $42,910 16% $44,660 $53,575 20% Energy $98,174 $120,708 23% $45,745 $56,174 23% $52,430 $64,534 23% Health Care Services $71,624 $90,047 26% $32,469 $41,689 28% $39,155 $48,358 24% Insurance $83,102 $100,792 21% $49,113 $44,984 -8% $33,989 $55,808 64% Life Sciences $101,269 $126,184 25% $45,254 $52,597 16% $56,015 $73,588 31% Media & Entertainment $82,631 $101,322 23% $38,565 $37,500 -3% $44,066 $63,822 45% Process & Industrial Products $89,395 $105,442 18% $42,377 $50,808 20% $47,018 $54,634 16% Professional Services Firms $88,538 $107,165 21% $38,432 $50,381 31% $50,106 $56,784 13% Retail $67,081 $80,312 20% $33,188 $39,122 18% $33,893 $41,189 22% Technology $105,059 $128,598 22% $48,742 $57,414 18% $56,317 $71,184 26% Telecommunications $94,747 $114,803 21% $50,662 $56,243 11% $44,085 $58,560 33%

Source: US Census Bureau, Richard Florida's "The Rise of the Creative Class,“ Deloitte Analysis Source: US Census Bureau, Richard Florida's "The Rise of the Creative Class,“ Deloitte Analysis

Two of the Shift Index metrics, Inter-firm Knowledge Flows Worker Passion and Worker Passion, attempt to measure the rates of flow Worker Passion, different from employee satisfaction, and passion by industry. denotes an intrinsic drive to do more and excel at every aspect of one’s profession. The 2011 survey of Worker Inter-firm Knowledge Flows Passion found that 21% of the overall U.S. workforce is The Shift Index survey of Inter-firm Knowledge Flows for passionate about their work. the overall U.S. workforce revealed a 2011 index score of 19 © 2011 Deloitte Touche Tohmatsu 14.34 This score ranged from 11 for the retail industry to U.S. workers are generally not passionate about their 17 for the media & entertainment and insurance industries professions: 79% of the U.S. workforce (ranging from (see Exhibit 20). Employees in the media & entertainment 70 to 85% depending on the industry) reported not industry are more likely to connect with other professionals being passionate about work. In nearly every industry, via social media, phone, or lunch meetings than peers in more employees were disengaged or passive than were other industries. Individuals in the insurance industry are engaged or passionate with most employees falling more likely to engage through membership in community into the “passive” category. Even in the highest scoring and professional organizations. Employees in the retail industry (Health Care), only 30% of employees reported industries are least likely to participate in any type of being passionate about work. The highest incidence of interfirm knowledge flow, either virtual or physical. In disengagement was in the Insurance, Automotive and absolute terms, though, the current levels of knowledge Telecommunications industries. sharing across firm boundaries are very low in all industries, and we expect participation in Inter-firm Knowledge Flows While the factors contributing to Worker Passion are to increase as competition intensifies. complex, there is a clear need for companies to foster passionate employees in the coming years. Firms will

34 Inter-firm Knowledge Flows scores were calculated based on communication levels between firms across eight categories of knowledge flows. See the metric discussion for further information.

36 Cross Industry Perspectives 7

Updated

Exhibit 20: Inter-firm Knowledge Flow Index Value, All Industries, (2011) Cross-Industry Perspectives Exhibit 20: Inter-firm Knowledge Flow Index Value, All Industries (2011)

Media & Entertainment 17%

Insurance 17%

Energy 16%

Life Sciences 15%

Telecommunications 15%

Banking & Financial… 15%

Technology 15%

Health Care Services 15%

Consumer Products 14%

Aerospace & Defense 14%

Aviation & Transport… 14%

Process & Industrial… 14%

Automotive 12%

Retail 11%

Average Inter-Firm Knowledge Flow Index Value

Note:Note: IFKF IFKFparticipation participation was updated was updated in 2011 toin include 2011 toparticipation include participation in discussion in groups/forums discussion groups/forumsSource: 2010 Deloitte Worker Passion/Inter-firm Source: 2011 Deloitte Worker Passion/Inter-Firm Knowledge Flow Survey (n=3108); Administered by Synovate Source: 2011 Deloitte Worker Passion/Inter-Firm Knowledge Flow Survey (n=3108); Administered by Synovate

need to tap into the passion of their employees to stay a longer-term view. In fact, the first tier of industries to competitive in a globalized labor market, which requires be affected by the Big Shift has been unable to overcome constant renewal and enhancement of professional skills performance pressures. While firms in these industries and capabilities. The Center for the Edge research indicates have improved their efficiency, these improvements have that passionate workers participate in more knowledge delivered diminishing returns. Today’s business environment flows in all but two industries (see Exhibit 22). Therefore, requires a focus on value creation and capture. Knowledge the firms that attract and retain passionate workers will flows are the key to surviving and thriving through likely benefit from participating in more flows and creating these tough times and beyond. The good news is that more value. knowledge flows are proliferating and becoming richer 20 © 2011 Deloitte Touche Tohmatsu on a global scale as a result of the increasing capability of Efficiency is no longer sufficient digital infrastructure and public policy initiatives to remove The performance pressures on U.S. industries will regulatory barriers to knowledge flows. In order to improve continue well past the current downturn. Today’s business performance and retain a greater share of the value environment has been fundamentally changed by the created, firms must amplify Inter-firm Knowledge Flows underlying shifts in practices and norms as a result of and instill greater Worker Passion. Without more effective advances in digital infrastructure and public policy playing participation in knowledge flows, firms will be unable to out over decades. respond successfully to the Big Shift.

While conventional wisdom would suggest a greater focus on efficiency and investments in a time of growing economic pressure, the findings of the Big Shift suggest

2011 Shift Index Measuring the forces of long-term change 37 Perspectives Cross-Industry

Cross Industry Perspectives 8

Updated Exhibit 21: Worker Passion, All Industries, (2011) Exhibit 21: Worker Passion, All Industries (2011)

Health Care Services

Energy

Media & Entertainment

Retail

Aerospace & Defense

Aviation & Transport Services

Insurance

Banking & Financial Institutions

Process & Industrial Products

Technology

Automotive

Telecommunications

Consumer Products

Life Sciences

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Disengaged Passive Engaged Passionate

Source: 2011 Deloitte Worker Passion/Inter-Firm Knowledge Flow Survey (n=3108); Administered by Synovate Source: 2011 Deloitte Worker Passion/Inter-Firm Knowledge Flow Survey (n=3108); Administered by Synovate

38 Cross Industry Perspectives 9

Updated Cross-Industry Perspectives ExhibitExhibit 22:22: Inter Inter-firm-firm Knowledge Knowledge Flows byFlows passion by Type,Passion All Industries,Type, All Industries(2011) (2011)

Insurance

Media & Entertainment

Telecommunications

Aerospace & Defense

Energy

Banking & Financial Institutions

Technology

Process & Industrial Products

Life Sciences

Health Care Services

Professional Service Firms

Consumer Products

Automotive

Aviation & Transport Services

Retail

0 5 10 15 20 25 30 Average Inter-firm Flow Index value Disengaged Passive Engaged Passionate

2011 Shift Index Measuring the forces of long-term change 39 Practice Shift Index in Shift Index in Practice

Companies could generate actionable insight by better understanding flow dynamics

While there has been a modest improvement tools, such as social media and collaboration platforms that scale flow and enable ongoing bi-lateral interations. Both in ROA over the past couple of years as the virtual and physical flows are amplified by technology and downturn eases up, we believe that this is platforms that cross geographical and time disparities. simply a short-term adjustment similar to Examples of flow metrics include: measurement of access to knowledge flows, depth of flow engagement, virtual the improvements in ROA seen in previous and physical closeness to colleagues, the connectedness of the organization, business unit and individual, and economic cycles. the correlation of flows to profit and revenue. As with operating and financial metrics, the flow metrics In response to growing interest from executives, the Center that matter most to an individual organization would for the Edge is further researching which flow metrics at vary depending on the industry, corporate goals, and the individual firm level, could be drivers of performance, organizational structure. ultimately captured in operating and financial metrics. In particular, we are investigating the ability of companies to Companies could generate actionable insight by better participate effectively in a larger and more diverse range of understanding flow dynamics. Because flow participation knowledge flows, with the intent of identifing a set of flow and performance is a continuum and the quality of flow metrics that can be drivers of performance metrics for the participation drives performance, a key management firm to monitor on an ongoing basis. challenge could be identifying and encouraging quality participation in information flows through policy, tools, and Flows in a firm are the result of social and working culture. practices, manifested in three ways: virtual flows, physical flows, and flow amplifiers. Virtual flows are the The insights derived from this research may inform thinking communication of information through virtual means around how organization can be better equipped to such as phone, internet, and video. Virtual flows are operate with more flexibility and agility in response to the enabled by advancing digital infrastructure and increasing pressures of The Big Shift. virtual connections. Physical flows are the movement and connectivity of individuals. Flow amplifiers are enabling

40 Shift Index in Practice

2011 Shift Index Measuring the forces of long-term change 41 Numbers and Trends Shift Index: The The Shift Index: Numbers and Trends

Shift Index Structure we could find or generate to directly measure the forces There is no shortage of indicators for measuring today’s underlying the Big Shift, we have not attempted to prove cyclical events, but what we often need is a way to quantify causality, although we have not refrained from offering long-term trends. Our Shift Index, a composite of 25 metrics hypotheses regarding potential causal links. In this regard, tracking a variety of concepts, is a way to measure the deep, we hope the Shift Index will catalyze research by others to secular forces underlying today’s cyclical change. test and refine our findings.

The Shift Index consists of three indices — the Foundation The Three Indices: A Comparative Discussion Index, Flow Index, and Impact Index — that quantify the Findings from the 2009, 2010 and 2011 Shift Indices three waves of the Big Shift. Exhibit 23 summarizes these suggest that deep changes in our economic foundations indices and describes the specific indicators included in each. continue to outpace the flows of knowledge they enable and their impact on markets, firms, and people. Fitting The current Shift Index Report focuses on the U.S. a trend line to each of the three indices, we see that the economy and U.S. industries, although the detailed analysis Foundation Index has moved much more quickly in the of industry-level data. past 17 years (with a slope of 8.63) relative to the Flow Index (6.48) and the Impact Index (1.63). These compara- The choice of metrics above was the result of a robust tive rates of change are shown in Exhibit 24. selection process. Many metrics are directional proxies chosen in the absence of ideal alternatives. Some are Tracking these relative rates of change helps us to drawn from secondary data sources and analytical meth- determine the economy’s position in the Big Shift as a odologies; others are proprietary. Given the limited data whole. This initial release of the Shift Index suggests that Exhibit 23: Shift Index Indicators Exhibit 23: Shift Index indicators

Competitive Intensity: Herfindahl-Hirschman Index Markets Labor Productivity: Index of Labor Productivity as defined by the Bureau of Labor Statistics Stock Price Volatility: Average standard deviation of daily stock price returns over one year

Asset Profitability: Total ROA for all U.S. firms ROA Performance Gap: Gap in ROA between firms in the top and the bottom quartiles Firms Firm Topple Rate: Annual rank shuffling amongst U.S. firms Shareholder Value Gap: Gap in the TRS1 between firm in the top and the bottom quartiles Impact Index Consumer Power: Index of 6 Consumer Power measures Brand Disloyalty: Index of 6 consumer disloyalty measures People Returns to Talent: Compensation gap between more and less creative occupational groupings2 Executive Turnover: Number of top management terminated, retired, or otherwise leaving companies

Inter-firm Knowledge Flows: Extent of employee participation in knowledge flows across firms Virtual Flows Wireless Activity: Total annual volume of mobile minutes and short message service (SMS) messages Internet Activity: Internet traffic between top 20 U.S. cities with the most domestic bandwidth

Migration of People to Creative Cities: Population gap between top and bottom creative cities2

Flow Index Physical Travel Volume: Total volume of local commuter transit and passenger air transportation3 Flows Movement of Capital: Value of U.S. foreign direct investment (FDI) inflows and outflows

Worker Passion: Percentage of employees most passionate about their jobs Amplifiers Social Media Activity: Time spent on social media as a percentage of total Internet time

Computing: Computing power per unit of cost Technology Digital Storage: Digital storage capacity per unit of cost Performance Bandwidth: Bandwidth capacity per unit of cost

Infrastructure Internet Users: Number of people actively using the Internet as compared to the U.S. population Penetration Wireless Subscriptions :Percentage of active wireless subscriptions as compared to the U.S. population Foundation Index Foundation Public Policy Economic Freedom: Index of 10 freedom components as defined by the Heritage Foundation

TRS —– Total Total Return Return to Shareholdersto Shareholders Creative occupations occupations and and cities cities defined defined by Richard by RichardFlorida's Florida's"The Rise "Theof the CreativeRise of the Class." Creative 2004 Class." 2004 Measured by by the the Bureau Bureau of Transportation of Transportation Statistics Statistics Transportation Transportation Services Index Services Index Source: Deloitte Deloitte analysis analysis

Updated Exhibit 24: Component index trends, (1993-2010) The Shift Index: Numbers and Trends Exhibit 24: Component Index trends (1993-2010) Slope: 8.63

Slope: 6.48

Slope: 1.63

1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Linear (Foundation Index) Linear (Flow Index) Linear (Impact Index) Source: Deloitte analysis

Source: Deloitte analysis the United States is still largely in the first wave of the Big Our initial findings show that the Flow-Impact Shift, although specific industries vary in their positions and are moving at different rates. gap is substantially larger than the Foundation-

We expect that companies, industries, and economies in Flow gap, meaning that participants are the earliest stage of the Big Shift will see the highest rates relatively more successful at generating new of change in the Foundation Index. Over time, as the Big Shift gathers momentum and pervades broader sectors of knowledge flows than at capturing their value. the economy and society, the Flow Index and Impact Index will likely pick up speed, while the rate of technological relevant future. But it can be narrowed by a substantial 24improvement and penetration captured by the Foundation increase in the rate at which businesses innovate and learn. © 2011 Deloitte Touche Tohmatsu Index will likely begin to slow. Insight also emerges from relative changes in the gaps Comparing the relative rates of change and magnitudes between the Foundation Index and the Flow Index of the three indices reveals telling gaps. The gap between and between the Flow Index and Impact Index. The the Foundation Index (190) and the Impact Index (101), for Foundation-Flow gap measures the degree to which flows example, defines the scope of the challenges and opportu- have grown through new social and business practices, nities that arise from rapidly changing digital infrastructure. relative to the growth in digital infrastructure. The Flow- Essentially, it measures the economic instability that results Impact gap measures the impact upon market participants, from performance potential (reflected by the Foundation relative to the growth of flows in the economy. Index) rising more quickly than realized performance (reflected in the Impact Index). If realized performance is Our initial findings show that the Flow-Impact gap significantly lower than potential performance, there is is substantially larger than the Foundation-Flow gap, growing room for disruptive innovation to narrow this gap. meaning that participants are relatively more successful at In this sense, the gap is also a measure of the opportunity generating new knowledge flows than at capturing their awaiting creative companies that determine how to more value. Relative changes in these gaps over time will provide effectively harness the capabilities of digital infrastructure. executives with an important measure of where progress Given the sustained exponential performance increases is being made, where obstacles exist, and where manage- in digital technology, this gap is unlikely to close in the ment attention needs to be paid.

2011 Shift Index Measuring the forces of long-term change 43 Numbers and Trends Shift Index: The

2010 Foundation Index Our findings show that the rate of change in the perfor- The Foundation Index, with an index value of 190 in 2010, mance of technology building blocks substantially exceeds has increased at a 10 percent compound annual growth the rate of change of the two other foundational metrics rate (CAGR) since 1993.35 This index, shown in Exhibit 25, — adoption rates and public policy shifts. It remains the Numbers & tells the story of a swiftly moving digital infrastructure primary driver of the strong secular change captured by the Trends 3 propelled by unremitting price performance improvements Foundation Index as a whole. in computing, storage, and bandwidth that show no signs of stabilizing.

Exhibit 25: Foundation Index trends, (1993-2010) Exhibit 25: Foundation Index trends (1993-2010)

200 190

180 168

160 153 143 140 132 121 120 110 100 100 92 83 Index value Index 80 74 64 59 54 60 50 46 41 38 40 Numbers &

20 Trends 4

0 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Source: Deloitte analysis Source:Exhibit Deloitte 26: Foundation analysis Index drivers, (1993-2010) Exhibit 26: Foundation Index drivers (1993-2010)

200

180

160

140

120

35 For further information on how 0 the Foundation Index is calculated, 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 please refer to the Shift Index Technology performance Infrastructure penetration Public Policy Methodology section. Source: Deloitte analysis 44 Source: Deloitte analysis

Exhibit 27: Flow Index, (1993-2010) The Shift Index: Numbers and Trends Exhibit 27: Flow Index (1993-2010)

180

160 155 145 139 140 128 117 120 104 97 100 89 83 77 Index value Index 80 72 65 61 57 60 51 54 47 49

0 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Source: Deloitte analysis Source: Deloitte analysis

As Exhibit 25 demonstrates, Technology Performance rely on proxies like Migration of People to Creative Cities metrics (e.g., Computing, Digital Storage, and Bandwidth) and Travel Volume to provide indirect measures of this have been driving the changes in the Foundation Index kind of activity. Social media use, conference and webcast since 1993. These metrics have been increasing rapidly attendance, professional information and advice shared at a 25% CAGR as a result of technological innovations by telephone and in lunch meetings — all of these serve and decreasing costs. Infrastructure Penetration metrics as suggestive proxies of various kinds of knowledge flows. (e.g., Internet Users and Wireless Subscriptions) have been As Exhibit 28 demonstrates, Virtual Flow metrics (e.g., growing slower, but at a still significant CAGR of 17%. Inter-Firm Knowledge Flows, Wireless Activity, and Internet Public policy has maintained a relatively constant position Activity) have been driving the index, increasing at an 10% in the Foundation Index for the past 17 years. CAGR. 27 © 2011 Deloitte Touche Tohmatsu However, policy is still a key wild card. There is consider- However, policy is still a key wild card. There is considerable risk that policy responses to the current economic able risk that policy responses to the current economic downturn may increase barriers to entry and movement. downturn may increase barriers to entry and movement. The Shift Index will represent this trend over time relative The Shift Index will represent this trend over time relative to the changes in the other foundations. to the changes in the other foundations.

2010 Flow Index While virtual flows are gaining importance as a result of The Flow Index, with an index value of 155 in 2010, has technological advancements, physical flows are still a key increased at a 7% CAGR since 1993.36 The Flow Index, to knowledge creation and transfer. As a result, Physical shown in Exhibit 27, measures the rate of change and Flow metrics (e.g., Movement of Capital, Migration of magnitude of knowledge flows resulting from the advances People to Creative Cities, and Travel Volume) maintain a in digital infrastructure and public policy liberalization. significant contribution to the Flow Index, increasing at a 6% CAGR since 1993. Flow Amplifiers (e.g., Worker When considering the Flow Index, it is important to bear Passion and Social Media Activity) have also been gaining in mind that the face-to-face interactions driving the most importance and are expected to be a major driver of the 36 For further information on how valuable knowledge flows — resulting in new knowledge index in the future. the Flow Index is calculated, creation — are difficult to measure directly, forcing us to please refer to the Shift Index Methodology section. 2011 Shift Index Measuring the forces of long-term change 45 Numbers & Numbers and Trends Shift Index: The Trends 6

Exhibit 28: Flow Index drivers, (1993-2010) Exhibit 28: Flow Index drivers (1993-2010)

180

160

140

120

100

Index value Index 80

40 Numbers & 20 Trends 7 0 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Virtual Flows Physical Flows Amplifiers Source: Deloitte analysis Source: Deloitte analysis Exhibit 29: Impact Index, (1993-2010) Exhibit 29: Impact Index (1993-2010)

120 111 106 104 105 101 100 100 101 99 98 98 100 93 95 88 84 81 78 78 80

0 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Source: Deloitte analysis Source: Deloitte analysis

2010 Impact Index attempts to determine how effective they are as consumers The Impact Index, with an index value of 101 in 2010, has and creative talent at harnessing the benefits of knowledge grown at a 1.5% CAGR since 1993. This index, shown in flows unleashed by advances in the core digital infrastruc- Exhibit 29, captures the dynamics of firms’ performance as ture. Because they are already good at doing this — and they respond to increasing competition and productivity, as are only getting better at it — the index is set to increase well as powerful new classes of consumers and talent.37 as they derive more value from the Big Shift.

This index is designed to measure the rate of change and At least in the short term, however, markets and firms 37 For further information on how magnitude of the impact of the Big Shift on three key appear to be moving in the opposite direction. Partly at the Impact Index is calculated, please refer to the Shift Index constituencies: markets, firms, and people. For people, it the hands of the consumers and talent who are doing so Methodology section. 29 © 2011 Deloitte Touche Tohmatsu 46 Numbers & Trends 8

Exhibit 30: Impact Index drivers, (1993-2010) Exhibit 30: Impact Index drivers (1993-2010)

120 The Shift Index: Numbers and Trends

100

60 Index value Index

0 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Markets Firms People Source: Deloitte analysis

Source: Deloitte analysis well, pressures on returns are unparalleled, and the tradi- There is considerable risk that policy responses tional way of doing business is increasingly under siege. So as markets grow more volatile, competition intensifies, to the current economic downturn may and firm performance declines, the Impact Index will also increase. increase barriers to entry and movement.

Albeit small shifts in the Impact Index are indicative of We must note that the Impact Index is more susceptible to powerful trends. For example, Exhibit 30 shows that where economic cycles than the other two indices, and, as such, we are today (an index value of 101) is the result of parallel the three drivers show much more volatility. The recessions growth in the impact of the Big Shift on all three constitu- in 2001 and 2008 particularly moved the needle, repre- 30encies. The markets driver, for example, has gone up more senting much greater pressures on firms, consumers, and © 2011 Deloitte Touche Tohmatsu than 33% since 1993, at a CAGR of 1.7%, indicating that talent during those times. As one would expect, competitive pressures are rising steeply. Strikingly similar firm performance metrics (e.g., Asset Profitability, ROA is the increase in the firms driver which measures the Performance Gap, Firm Topple Rate, and Shareholder Value negative effect of these pressures on corporate perfor- Gap) are affected most by these economic events. mance and returns. This driver has increased by 20% since 1993, itself just at a CAGR of 1.1%. This relation- To limit the extent to which cyclical fluctuations can ship between growth in market pressures and deteriora- sway the Impact Index, we have used data smoothing to tion of firm performance, which is nearly one to one, is put the focus on long-term trends instead of short-term particularly revealing with regard to the mismatch between movements (for further information on data smoothing, today’s management approaches and the forces of the please refer to the Shift Index Methodology section). Big Shift. Finally, while we are forced to make assumptions when it comes to the impact of these forces on people, Once peaks and valleys are removed, we see clearly that because our way of measuring this through a recent survey the growing power of creative talent and consumers, a precludes us from assessing historical trends, we intui- driving force behind Competitive Intensity, is sapping value tively know that technological platforms and knowledge from corporations at the same time that Labor Productivity flows tend to change the world first on a social level, well is on the rise. before institutions catch on. So while we cannot accurately calculate how it has changed for them over time, we can reasonably assume that people have been most affected by the Big Shift and the most consistently.

2011 Shift Index Measuring the forces of long-term change 47 2011 Foundation Index

Technology Performance 53 Computing 55 Digital Storage 58 Bandwidth

Infrastructure Penetration 60 Internet Users 64 Wireless Subscriptions

Public Policy 66 Economic Freedom

48 2011 Shift Index Measuring the forces of long-term change 48 2011 Foundation Index Tab Title Here Tab 2011 Foundation Index The fast moving, relentless evolution of a new digital infrastructure and shifts in global public policy are reducing barriers to entry and movement.

The Foundation Index quantifies the first wave of the Big • Wireless subscriptions have grown dramatically since Shift, which involves the fast-moving, relentless evolution 1985, jumping from 1% of the U.S. population to of a new digital infrastructure and shifts in global public more than 90% in 2010, creating another medium policy that have reduced barriers to entry and movement. for connectivity and knowledge flows. As core digital Key findings include: technology continues to improve, the line between the Internet and wireless media will continue to blur, further • The exponentially advancing price/performance capability enhancing our abilities to connect regardless of physical of computing, storage, and bandwidth is contributing to location. an adoption rate for the digital infrastructure that is two • U.S. Economic Freedom has shown an upward trend to five times faster than previous infrastructures, such as from 1995 to 2010, increasing 5% over that period electricity and telephone networks. while consistently staying above the world average. Over • The cost of 1 mm transistors has steadily dropped the past 15 years, it was primarily driven by investment from over $222 in 1992 to $0.13 in 2010, leveling freedom (a 14% increase), financial freedom (a 14% the playing field by reducing the importance of scale increase), trade freedom (an 11% increase), and business and thus increasing opportunities for innovation. Intel freedom (an 8% increase). While there is no prospect technologists anticipate this trend to continue for at least for a near-term leveling of improvements in digital the next four generations of processors. technology, the trend toward increasingly open public • The cost of 1 gigabyte (GB) of storage has been policy is uncertain moving forward. The current turmoil decreasing at an exponential rate from $569 in 1992 in world markets has created a very real potential for a to $0.06 in 2010. The increase of both storage and policy backlash and a rebuilding of protectionist barriers. bandwidth has helped to enable the boom in user- These barriers would detract from the benefits created generated content, which has helped to break down by advances in the digital infrastructure and its adoption information asymmetries between vendors and by market participants. It is encouraging, however, customers who now have easier access to product price that while a move to protectionist policies is certainly and quality information. The cost of 1,000 megabits possible, it would be difficult to sustain unless large parts per second (mbps), which refers to data transfer speed, of the world followed suit. dropped 10 times from over $1,197 in 1999 to $47 in 2010, allowing for cheaper and more reliable data Advances in computing, storage, and bandwidth, coupled transfer. with wireless networks and powerful devices, such as • The percentage of the U.S. population using the Internet smartphones and netbooks, have created an increasingly has grown from 1% in 1990 to 68% in 2010, taking robust platform for users to connect and communicate less time to penetrate 50% of U.S. households than anywhere and anytime. Meanwhile, access to this platform any other technology in history. As access continues to has become easier and more affordable, creating a new spread and as content and services improve, we expect foundation for the ways we interact and participate in the Internet to become an increasingly dominant enabler knowledge flows. of the robust knowledge flows central to economic value creation.

2011 Shift Index Measuring the forces of long-term change 49 Index Tab2011 Foundation Here Title

As computing power grows and becomes companies and institutions can harness the powerful potential brought about by the Big Shift and progressively ubiquitous, today’s highly complex problems, turn mounting challenges into growing opportunities.

in fields ranging from medical genetics to The Foundation Index nanotechnology, are expected to become the The Foundation Index, as shown in Exhibit 31, has a 2010 value of 190 and has increased at a 11% CAGR building blocks of future innovation. since 1993.38 Its metrics capture the price/performance trends in technology, its adoption by the U.S. population, These foundational changes define a new performance and corresponding advances in public policy. The potential and thus reflect both new possibilities and Foundation Index is a leading indicator: Advances in core challenges. This new potential refers to the opportunity technologies and their adoption define the potential for companies have to precipitate, participate in, and profit firm performance. However, this potential will take quite from knowledge flows enabled by an ever-improving some time to materialize in performance, as institutions digital infrastructure and the reduction in interaction costs lag behind at developing practices that truly leverage the that make it easier to coordinate complex activities on a digital infrastructure. global scale. At the same time, these foundational changes also represent significant and growing challenges for firms. We have built the Foundation Index around three key Technological advances and economic liberalization have drivers, shown in Exhibit 32: systematically and significantly reduced barriers to entry and movement. This, in turn, has substantially increased • Technology Performance: Core digital performance competitive intensity (see the Competitive Intensity trends that enable knowledge flows, creating pressures metric in the Impact Index) and has generated growing and opportunities for market participants. This driver Foundation Index performance pressure (see the firms metrics in the Impact consists of three metrics: Computing, Digital Storage, Drivers 1 Index). However, by adjusting institutional architectures, and Bandwidth. governance structures, and operational practices,

Exhibit 31: Foundation Index trends, (1993-2010) Exhibit 31: Foundation Index Trends (1993-2010)

200 190

180 168

160 153 143 140 132 121 120 110 100 100 92 83 Index value Index 80 74 64 59 54 60 50 46 41 38 40

0 38 For further information on how 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 the Foundation Index is calculated, please refer to the Shift Index Source: Deloitte analysis Methodology section. Source: Deloitte analysis 50

31 © 2011 Deloitte Touche Tohmatsu Foundation Index Drivers 2 Tab Title Here Tab 2011 Foundation Index Exhibit 32: Foundation Index drivers, (1993-2010) Exhibit 32: Foundation Index drivers (1993-2010)

200

180

160

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120

100 Index value Index 80

0 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Technology performance Infrastructure penetration Public Policy Source: Deloitte analysis

Source: Deloitte analysis • Infrastructure Penetration: The adoption of innovative As key technologies, such as the Internet, approach a satu- products and technologies brought on by the advances ration point, growth in the Infrastructure Penetration driver in the core digital infrastructure. This driver consists of is expected to slow. However, advances in the technologies two metrics: Internet Users and Wireless Subscriptions. themselves are expected to continue at a rapid pace in the • Public Policy: Technological advances and adoption near future. This slowdown in adoption does not mean rates can be either dampened or amplified by public that participation in knowledge flows will slow or stop; policy initiatives; this driver represents the concept that on the contrary, saturation will indicate a robust installed the liberalization of economic policy removes barriers to base equipped to fully engage in knowledge flows. As the the movement of ideas, capital, products, and people. It digital infrastructure continues to improve, users will be consists of one metric: Economic Freedom. able to engage with it in new and innovative ways, further 32 enhancing their abilities to connect and learn. © 2011 Deloitte Touche Tohmatsu Consistent with its role as a leading indicator of the Big Shift, the Foundation Index has grown most rapidly over Public policy liberalization, measured by the degree of the last 16 years. This growth has primarily been driven Economic Freedom, has remained at a very high level by accelerating improvements in the performance of relative to the rest of the world, but has improved only technology, represented by the Technology Performance modestly in recent years, growing at a 1% CAGR (see driver, which has grown at a 25% CAGR since 1993 Exhibit 35). (see Exhibit 33). The penetration of these technological infrastructures, represented by the Infrastructure Penetration driver, has also been increasing, albeit at a slower 17% CAGR (see Exhibit 34), confirming that adoption of technology advances somewhat lags behind the rate of innovation.

2011 Shift Index Measuring the forces of long-term change 51 Foundation Index Drivers 3

Exhibit 33: Technology Performance, (1993-2010) Exhibit 33: Technology performance (1993-2010) Index 2011 Foundation

120

100

60 Index value Index

40 Foundation Index 20 Drivers 4

0 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Source: Deloitte analysis Exhibit 34: Infrastructure Penetration, (1993-2010) Source: Deloitte analysis Exhibit 34: Infrastructure penetration (1993-2010)

0 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Source: Deloitte analysis Exhibit 35: Public Policy, (1993-2010) Source:Exhibit Deloitte 35: analysis Public policy (1993-2010)

60 The chart (right) represents the combined movements of 50 the underlying metrics in the index, after data adjustments and indexing to a base year of 40

0 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Source: Deloitte analysis 52 Source: Deloitte analysis

Introduction Once the engineers, scientists, and architects develop Computing has gone through a number of transformations a working proof of concept, equipment vendors invest The Computing metric in the last 30 years, moving from mainframe to client billions of dollars creating the manufacturing equipment measures the vendor cost server and, today, into the cloud. The driver of these required to produce the new semiconductor specification. associated with putting transformations has been the remarkably consistent drop in These investments continue apace, even during recessions, one million transistors computing cost/performance. This exponential decline, first as vendors position themselves for the resumption of on a semiconductor. The described in 1965 by Gordon Moore who predicted that economic growth. metric provides visibility the number of transistors on an integrated circuit would into cost/performance double every 24 months and the cost would decrease The Shift Index will look for changes in computing cost/ associated with the by half, has proven to be one of the most enduring performance curves over time, however, we expect this computational power at technology predictions ever made. It also serves as a metric to be highly predictable. Over the past 40 years, the core of the self-fulfilling prophecy as semiconductor vendors seek to there have been times when Moore’s Law appeared in Big Shift. maintain the trend. danger of failing, yet in each case Moore’s Law persisted as a result of human ingenuity to extend Moore’s Law into a A decline in this metric To maintain the downward progression in computing cost/ relevant future. represents a decrease in performance, semiconductor vendors invest in ever-more the cost of computing research and development (R&D) and capital equipment Observations and Implications power. to develop new semiconductor designs. Engineers shrink As Exhibit 36 shows, the cost of transistors has steadily transistors down to the atomic level, materials scientists dropped, from over $222 dollars per 1MM in 1990 to explore the electrical properties of the exotic materials $0.13 in 2010, a negative 66% CAGR. used in chips, physicists employ quantum mechanics to Computing 1 build atomic computers, and process engineers improve One recent innovation that promises to both extend manufacturing throughput and quality. Increasingly, Moore’s Law and reduce semiconductor energy computer architects are part of the equation, employing requirements is 3-D architecture. While today’s chips are multiple computing cores to achieve processing efficiency. built in three dimensions, they operate in a planar fashion Updated– add to Exhibit 36: Computing Cost Performance, (1992-2010) Exhibit 36: Computing Cost Performance (1992-2010) write up

1000

$222

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10 $ per 1 MM transistorsMM 1 $ per

1 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

0 $ per 1 MM transistors $0.13 Source: Leading technology research vendor 2011 Shift Index Measuring the forces of long-term change 53 Source: Leading technology research vendor

— electrons move in two dimensions across the chip. Intel’s new Tri-Gate architecture allows electrons to Are You a Fraud? move “up, left, and down.”41 This translates to higher ebruary 4, 2011 — Multiple arrests were made in relation to a credit performance with less power. Intel estimates that card fraud ring that affected at least 57 people. The arrests come after individual Tri-Gate transistors at 22 nm will show a 37% members of the Louisiana Financial Crimes Task Force concluded a three- increase in performance and require half the power of a month investigation into numerous credit card fraud complaints from St. planar transistor built on a 32-nm architecture. If Intel’s TammanyF Parish residents. It was discovered that all of the victims had one thing estimates hold, that virtually guarantees that Moore’s in common, they had all used their card at the same fast food outlet in Mandeville. Law will extend well past 2020. Police discovered during their investigation that Christopher M. Brumfield, 25, of Mandeville recruited Todd Pea Jr., who worked the drive-thru at a Mandeville fast “For years we have seen limits to how small transistors food outlet, to collect credit card and debit card numbers using a separate credit can get," Moore said in an Intel Press Release. "This card swiping device. Pea would swipe cards once on the restaurant’s machine change in the basic structure is a truly revolutionary and then on a separate machine. He would then pass on the electronic credit approach, and one that should allow Moore's Law, and 42 card information to members of the criminal organization, who transferred the the historic pace of innovation, to continue." information to counterfeit credit cards. Once transferred to the counterfeit cards, members of the criminal network, used the credit card information to purchase a Even if architectural and process innovation cannot variety of merchandise within a short period of time.39 overcome the next limit to Moore’s law, Moore points out that it will “not be the end of the world … You 43 In order to reduce chances of credit card fraud such as this, Visa announced just make bigger chips.” Semiconductors are built on dramatic improvements to its security capabilities early in 2011. Visa Advanced wafer-thin slices of silicon crystal. Today, cutting-edge Authorization is better able to detect "high speed fraud," where criminals fabs manufacture 300-mm wafers. The next step is attempt multiple transactions within a very short time period — minutes or even 450-mm wafers. Taiwan Semiconductor Manufacturing seconds apart. Because Visa's network is not only able to process thousands of Company Limited (TSMC), one of the largest transactions per second, but also instantly recall and analyze millions of pieces of independent semiconductor foundries in the world, information in its memory, Visa is able to identify emerging fraud trends as they has announced plans to launch a 450-mm pilot line in 44 happen — not hours or days later. An analysis of past global transactions suggests 2013-2014 and production in 2015-2016. Visa's enhancements could help identify $1.5 billion in fraud, representing a 29% performance improvement from 2009. In particular, fraud detection rates on the As computing power grows and becomes ubiquitous, riskiest transactions improved by 122% over the previous model. today’s highly complex problems, in fields ranging from medical genetics to nanotechnology, are expected to This increase in fraud identification is the result of an enhancement to the become the building blocks of future innovation. Those underlying processing platform that powers Visa's Advanced Authorization — a who use computing to analyze, arrange and apply security technology that analyzes and scores every Visa transaction for its fraud these building blocks will likely usher in new waves of potential. VisaNet is the foundation of Visa Advanced Authorization, a modular innovation. One thing seems clear: success will depend processing platform that handles more than 10,000 transactions per second and upon having the talent and organizational ability to contains a significant amount of processing memory. A new operating system effectively harness this processing power to deliver new implemented earlier this year allows more information to be analyzed at once innovations to market. and performs more complex processing functions in milliseconds. This provides 41 Dadi Perlmutter, Executive Vice President and General Manager for the Intel Architecture Visa with a more comprehensive view into the global payments system, spending Group patterns and better positioning the company to detect and prevent fraud in near 42 “Intel Reinvents Transistors Using New 3D Storage” http://newsroom.intel. real time.40 com/community/intel_newsroom/ blog/2011/05/04/intel-reinvents-transistors-using-new-3-d-structure 43 Quoted in Ed Sperling, “Gordon Moore on Moore’s Law,” Electronic News, September 39 Multiple Arrests Made in Credit Card Fraud 40 Visa Advances Cardholder Security Through 19, 2007, http://www.electronicsnews. Ring. February 7, 2011. Tech Talk Seattle. Improved Fraud Detection. Jan. 6, 2011. com.au/Article/Gordon-Moore-on- Department of Information Technology. Visa Corporation. < http://investor.visa. Moores-Law/74412.aspx. newsArticle&ID=1513794&highlight=> Morris Chaing CEO, TSMC. January 27th 2011.

54 Digital Storage 2011 Foundation 2011 Foundation Index Plummeting storage costs accelerate the creation of information and the need for data filters

Introduction Observations and Implications The Digital Storage Beginning with the introduction of magnetic drum Over the past 19 years, the compounding effects of metric measures the technology for early mainframe computers in 1955, technology innovation, competitive pressures, market vendor cost associated storage cost/performance has decreased exponentially, demand and the substitute effect (storage as utility) have with producing 1 GB of making storage globally ubiquitous. These cost/ driven storage costs down dramatically and contributed digital storage. performance improvements are described by Kryder’s to exponential increases in performance. The cost of 1 Law which predicts that storage capacity (on a unit basis) GB of storage has decreased from $568.9 in 1992 to The metric provides doubles every 12 to 18 months. And while Kryder’s Law $0.06 in 2010 as shown in Exhibit 37. To put this trend in visibility into the cost/ was an observation after the fact, it has proven remarkably perspective, without the improvements in storage capacity performance curve descriptive of the trend in storage capacity since 1955. and related drop in costs since 1992, it would cost $3.4B associated with digital Today, more than 50 years after the application of to store all of the information available on the Web today. storage allowing for the magnetic storage to digital computing, users can store on Instead, storing all of the information on the Web today computational power at a thumb drive what formerly required thousands of square costs only a fraction of that, $0.4M!46 the core of the Big Shift. feet. Experts believe that cost/performance will continue to The Digital Storage metric tracks changes in the storage decrease at its current pace in the foreseeable future.47 cost/performance curve over time. We expect this metric However, in the long term, innovation will depend on new to be relatively stable as innovation and increased usage of technologies, including nanotechnology, 3-D holographic the devices and applications that create and capture digital storage, carbon nanotubes, and heat-assisted magnetic information drive growth and innovation in the devices recording.48 and applications used to store information. “Information Digital Storage 1 creation” and available storage are the yin and yang of the The demand for storage is expected to continue to grow digital universe.”45 over the next three years, but while on-premise growth stagnates, cloud-based storage is experiencing massive Updated– add to Exhibit 37: Storage Cost Performance, (1992-2010) Exhibit 37: Storage Cost Performance (1992-2010) write up

1000 $569

45 John F. Ganz et al., The Diverse and Exploding Digital Universe 100 (Framingham, MA: IDC, 2008), http://www.emc.com/collateral/ analyst-reports/diverse-exploding- digital-universe.pdf. 46 Based on Google estimates of 10 average web page size of 320KB < http://code.google.com/speed/ articles/web-metrics.html >and 18.56 billion indesed pages as of July4, 2011< http://www.world- $ per Gigabyte (GB)Gigabyte $ per 1 widewebsize.com/>. 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 47 Mark H. Kryder and Chang Soo Kim. “After Hard Drives-What Comes Next?” IEEE Transactions on Magnetics, Vol. 45, No. 10, October 2009. http://www. 0 dssc.ece.cmu.edu/research/pdfs/ After_Hard_Drives.pdf 48 Burt Kaliski, “Global Research $0.06 Collaboration at EMC Corporation,” http://www.emc.com/leadership/ 0 tech-view/innovation-network.htm $ per GB (updated 2009). Source: Leading technology research vendor 2011 Shift Index Measuring the forces of long-term change 55 Source: Leading technology research vendor

e-discovery Redefines the Legal Paper Chase

n the trial of Green vs. Blitz USA Inc. March 2011, Mrs. Green alleged that her husband’s death was caused, in part, by the lack of a flame arrestor on gas cans manufactured by Blitz USA Inc. Although the lawsuit had been settled a year earlier, Mrs. Green sought to reopen her lawsuit upon learning that the defendant had failed to produce relevant documents. Obtained through manual collection processes, Ithe information discovery process failed to identify documents critical to the trial. Finding that the defendant had committed information discovery abuses, including failing to disclose relevant evidence , the court ordered the defendant to pay the plaintiff $250,000 in addition to other punishments. The trial of Green vs. Blitz USA Inc. is the latest in a line of cases that have been highly critical of manual (or self) information collection efforts by legal counsel and individual custodians, the limitations of which could be overcome through electronic discovery.49

In the past, law firms deployed large numbers of junior associates and paralegals to conduct discovery to determine which documents were relevant. In fact, discovery is 80% of the cost of litigation. Historically, this manual collection process was largely deemed defensible provided the information collection process was closely monitored. However, lately, this behavior of manual collection of information and discovery is being considered simply too risky for any conservative enterprise.

Over the past decade, the troves of digital information in litigation have exploded right along with inexpensive storage & search technology. Today, a case with 20 GB, more than 40,000 documents, is considered small. Enabled by this rapid progress in technology, throwing junior lawyers at information discovery is no longer feasible. The better practice is to leverage the custodians to point out where relevant electronically stored information (EST) might exist and utilize software tools to conduct broad collections from key players. For example, Jill Kirila, a partner with the litigation firm Squire Sanders & Dempsey in Columbus uses Equivio (Relevance) for e-discovery. “We reduced one project that was estimated to cost more than $500,000 in human review. We were able to do it for under one third of that using Equivio,” said Partner Jill Kirila.50

Solutions from Equivio (Relevance) and Xerox (CategoiX) are helping to maximize the value of human input in the process by applying new filtering and predictive indexing technologies to accelerate discovery beyond keyword search. Once an expert lawyer completes discovery on a set of documents, typically a few thousand, the system is “trained” and can analyze an immensely large set of documents for the case. The idea is not to remove lawyers from the process, but to allow them to focus on what they are trained to do.

While low-cost storage has enabled the document overload, storage, and cloud computing play a role in the delivery of e-discovery solutions as well. Customers can pay software license fees for gigabyte analysis limits or can hire hosted solutions which simply apply a per GB charge when analysis is needed. This provides a scalable solution for law firms with variable discovery demands.

49 GREEN v. BLITZ U.S.A., INC. CIVIL e-discovery solutions have yet to be challenged in court and the consensus at legal conferences seems to be ACTION NO. 2:07-CV-372 (TJW). favorable. At the rate of information storage growth, it is only a matter of time before throwing bodies at the Filed in the United States District Court for the Easter District of problem, even low-cost domestic and international talent, becomes unworkable. Texas Marshall Division 50 Electronic discovery software helps lawyers sort through digital troves. Robert Celaschi. Business First. http://www. bizjournals.com/columbus/print- edition/2011/04/08/litigators-lean- on-automated-doc.html?page=all

56 2011 Foundation 2011 Foundation Index

adoption51. Cloud-based storage is expected to play a It is not unusual for a technological innovation to provide significant role in meeting the demand at lower costs by dramatic benefits to either individuals or businesses (think migrating storage away from on-premise solutions and iPhones and client/server). The difference with cloud onto shared cloud servers. storage is the wide relevance of its value proposition around simplicity, efficiency, and dependability. Cloud Although cloud-based storage is expected to be storage has a unique potential to address both individual increasingly important to both individuals and businesses, and businesses storage needs and overcome previous these groups are at different levels of understanding cloud- limitations. based storage and the benefits it offers. Several cloud based products and services are emerging for individuals. In solving our storage limitations, we create a new For example, the cloud may provide individuals with challenge: the proliferation of digital data. As the cloud ubiquitous access to data with the same safeguards against enables vast and accessible storage, our attention becomes failure that businesses have enjoyed for years. Individuals increasingly scarce. More and more documents, emails, are also experiencing the cloud through emerging cloud- videos, blogs, papers, comments, articles, advertisements, based services, such as Apple’s iCloud (a combination etc., will vie for our limited attention. While participating of iTunes/hard drive cloud storage solution that allows in and sampling from streams of data, information and individuals to access content from any device) and Dropbox knowledge is increasingly important in the Big Shift,52 (which allows dragging and dropping family photos), the proliferation of digital data makes it more difficult to however, they may not consider themselves users of the separate the valuable signal from the valueless noise. cloud nor understand the real value it is providing.

For businesses, the value proposition is more evident. Cloud storage is scalable; it can efficiently accommodate variable data flows, such as when a retailer is in the midst of the Christmas rush. Cloud storage also locates data near scalable computing resources, allowing businesses to access massive computational power without having to invest in computing assets. Because it is scalable, cloud- based storage can be more cost effective, avoiding the need to invest in expensive on-premise storage that may be underused. Business concerns with the cloud center primarily around security and risk of failure.

51 ”Cloud Computing Takes Off.” Morgan Stanley Research. 52 The role of knowledge streams in the Big Shift is discussed in greater detail in the Flow Index section. 2011 Shift Index Measuring the forces of long-term change 57 Index 2011 Foundation Bandwidth

Low-cost bandwidth bolsters connectivity, enabling consumption of richer data

Introduction switches. Although the standard was adopted in 2003, The Bandwidth Nearly two decades after the beginning of the boom the early 10-GbE solutions were premium, low-volume metric measures the in commercial internet traffic, the internet continues to solutions, and, thus, expensive to manufacture. As vendor cost associated revolutionize the way people communicate, consume more data centers adopted the 10-GbE technology, with producing gigabit content, and conduct commerce. The consistent decline in manufacturers became more adept at producing them Ethernet/fiber (“GbE- bandwidth’s cost for performance is a fundamental driver until the market reached an inflection point in 2009: Fiber”) as deployed in of the growth in internet traffic and rich connectivity. volume increased substantially, competitive pressure grew, data centers. and manufacturing costs came down. The result was a We expect bandwidth’s cost/performance curve to dramatic reduction in price to the customer. These costs This metric provides continue to decline. Innovations in the underlying are expected to continue to drop for the next couple of visibility into the cost/ technology and progressive industry standards have years before flattening as the cycle begins again with performance curve improved bandwidth performance significantly. First, adoption of the next new standard. that allows for the enhanced computational power that allows content to be computational power further compressed and improved cable technology have With widespread deployment of the new standard at at the core of the Big increased the capacity of fiber. Additionally, the standard Internet service providers (ISPs), greater bandwidth is Shift. setting bodies and the processes required to deploy new available at lower costs; the world is increasingly connected bandwidth technology have been successful in maintaining through infrastructure capable of delivering faster, richer the trend of increased speed and performance. The cost and more mobile user experiences. In prior years, the efficiencies come from manufacturing and deployment bandwidth cost/performance trends pointed toward of the latest standard. In each successive round of cheap and reliable connectivity becoming the norm. Now, deployment, the cost to deploy the new standard drops improved bandwidth is enabling new applications and to a point where carriers rush to upgrade technology business models, from high definition videoconferencing in an effort to grow revenue through new services and to cloud computing, which were previously limited by applications. Combined, these trends suggest that the bandwidth constraints. decline in bandwidth cost/performance curve will persist into the foreseeable future. The decline of bandwidth cost/performance is highly disruptive for many established markets. Optical fiber into Observations and Implications the home, for example, threatens video rentals. Cable and In 2010, the delivered cost represented by the bandwidth digital television face the threat of disintermediation in metric declined markedly. This decline in costs for the end an age where bandwidth enables consumers to pick and user correlated with increased adoption of 10-GbE choose content, often selecting specific Web content over multichannel packages.

58 2011 Foundation 2011 Foundation Index

More broadly, improved bandwidth makes it easier to Putting the ‘Net’ in Netflix collect and transfer data, providing both consumers and companies access to more information to help make etflix founder Reed Hastings is often quoted as saying, “there decisions, and unlocks new opportunities that hinge on is a reason we didn’t call the company DVDs by mail…”. Two the availability of bandwidth. For instance, employees independent events — a $40 video rental late fee and a gym can participate in problem solving remotely through membership pricing scheme — inspired Reed to contemplate telepresence capabilities and transmission of video in a better pricing and distribution model for entertainment content that led N a way that is not possible via simple teleconferencing. to the birth of Netflix in 1998. Netflix is now the #1 consumer of bandwidth Individuals can listen to music streaming from their in the United States. It surpasses Web surfing, Facebook, and iTunes combined. In 2010, the “Net” in Netflix finally became a reality as streaming laptops or watch videos. Neither videoconferencing or video, enabled by relatively low-cost bandwidth, surpassed DVD mailers as music streaming would have been possible without the the primary distribution mechanism. availability of cheap and fast bandwidth. The speed of information sharing among consumers and the ability Netflix is disrupting more than just the media industry. Recently, a Netflix for consumers to connect with relevant parties within content delivery director posted the bandwidth performance of all the a company has increased transparency and decreased major ISPs. The release and discussion thread helped consumers (especially arbitrage opportunities that existed with past ‘lumpiness’ Netflix fans) make purchasing decisions on ISPs and highlighted those of information sharing. ISPs lagging in bandwidth performance. In addition, Netflix also helps subscribers work with bandwidth constraints levied by ISPs that have Declining bandwidth cost/performance is changing the bandwidth limits or tiered pricing by allowing customers to select the quality way we work, interact, and organize commerce. As of their content streaming. Netflix bandwidth selection enables consumers Bandwidth 1 to decide the trade-off between high-definition streaming and buying bandwidth becomes increasingly commoditized, we expect additional bandwidth-customers can elect to receive lower quality digital connected businesses and individuals to reap the benefits streams in order to maximize the content they receive under any data limits. through new applications that make use of it. Updated– add to Exhibit 38: Bandwidth Cost Performance, (1999-2010) Exhibit 38: Bandwidth Cost Performance (1999-2010) write up

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1 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

$ per 1,000 Mbps 2011 Shift Index Measuring the forces of long-term change 59 Source: Leading technology research vendor

Source: Leading technology research vendor

Accelerating internet adoption makes digital technology more accessible, increasing competitive pressure, as well as creating opportunity

Introduction service vendors could create and exchange knowledge, The Internet Users The rate at which more people are actively using the increasing the productivity of all the participants in its metric measures the Internet indicates how rapidly this digital infrastructure is ecosystem in the process. The relatively low cost and number of “active” being adopted. The Internet is itself the sum total of all the nearly instantaneous sharing of ideas, knowledge and skills Internet users in the functionality and technological advancements underlying facilitated by the Internet is making collaborative work United States as a it—the advances in reliable broadband and mobile Internet considerably easier. percentage of total infrastructure, the vast “server farms” that support search U.S. population. engines and the countless Internet applications that run comScore’s State of the Internet Report is the basis of the “Active” users are on browsers. Use of the Internet is also significant to the data for this metric.53 comScore defines active “Internet defined as those who Big Shift because the Internet provides users with instant Users” as persons using the Internet at least once during access the Internet at access to the breadth of information and resources needed the month-long period in which they are surveyed. Data least once a month. to fuel innovation, collaboration, and efficiency. for personal computer (PC) and mobile Internet users were provided in this report, but only the PC Internet user The Internet Users As access becomes more widespread and services figures were incorporated into the index given the very metric is a proxy for continue to improve, the Internet will increasingly high overlap of mobile and PC Internet users in the United adoption of the core become a dominant medium for the knowledge flows States. The overall usage figures were normalized against technology. that are central to economic value creation. Consider the U.S. population to provide a penetration value for this how LinkedIn, Facebook, and Twitter enable individuals installed base. to post news articles, videos, photos, white papers, and other media to audiences of followers, friends, and Internet Users 1 professional colleagues. Or how the German software maker SAP used the Internet to create a virtual platform in which customers, developers, system integrators, and Updated Exhibit 39: Internet Users, (1990-2010) Exhibit 39: Internet Users (1990-2010)

80%

70% 68%

60%

50% Population 40% U.S. U.S.

30%

20% Percentageof

10%

53 For further information, 0% please refer to the Shift Index 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Methodology section. Internet Users 60 Source: comScore, Deloitte analysis

Source: comScore, Deloitte analysis

Updated 2011 Foundation 2011 Foundation Index Exhibit 40: Technology adoption - U.S. households Title Here Tab Exhibit 40: Technology adoption - U.S. households

50 46 45

U.S. households 20 17 16 15 12 9 10

Number of years technology took to penetrate 50% of 5

0 Telephone Electricity Computer Cellphone Color TV Internet

Years to reach 50% penetration Source: Deloitte analysis Source: Deloitte analysis

Observations and Implications Mobile Internet users are also gaining critical mass. In In the United States, approximately 212 million individuals 2010, more than 60% of U.S. households had at least were actively using the Internet by December 2010. Over one mobile broadband device and more than 25% of the past 20 years, Internet users as a percentage of the households had two or more such devices.56 Technological U.S. population have grown rapidly, from 1% in 1990 to improvements, such as third generation of wireless 8% in 1995 to 68% in 2010 (see Exhibit 39). networks (3G) and advances in smartphone and tablet device capabilities have allowed for easy remote Internet To put these numbers in context, consider that it took less access. The Apple iPhone, iPad, and iPod Touch products time for the Internet to penetrate 50% of U.S. households exemplify this trend: Globally, over 200 million products than any other technology in history (see Exhibit 40). The sold and over 15 billion application downloads from the 40Internet achieved 50% penetration of U.S. households in Apple App Store to date.57 © 2011 Deloitte Touche Tohmatsu 9 years, whereas it took the telephone, electricity, and the

computer 46, 19, and 17 years, respectively, to reach the The mobile Internet demographic skews toward younger 54 “Consumption Spreads Faster same milestone.54 users and provides a hint of the future. According to a Today,” New York Times, http:// www.nytimes.com/imagep- recent study, when given a choice of consumer electronic ages/2008/02/10/opinion/10op. graphic.ready.html (updated 2008), One of the drivers for the increase in Internet Users has devices, Boomer Internet users (ages 45+) overwhelmingly Deloitte analysis been the constant improvement in technology cost/ chose PCs over mobile phones (51% and 21%, 55 “Forecast Analysis: PCs, Worldwide and North America 1Q10 Update” performance discussed elsewhere in the Foundation respectively), while the opposite held true (47% and 38%, Standard & Poor’s, http://www. 58 netadvantage.standardandpoors. section. Both Internet access and PCs have become respectively) for Gen Y users (ages 18-24). Pew Center com/NASApp/NetAdvantage/ increasingly affordable, making it possible for more people research revealed that 91% of Gen Y users go online; this showIndustrySurvey.do?code=coh (updated 2009). to get online. For example, Gartner reported that the number gradually falls off for older audiences, hitting 30% 56 “Survey Analysis: A Map of Mobile 59 Broadband Consumer and Rate of average system price for PCs fell from $832 in 2008 to for users over 74 years old. We are well into a trend Adoption” Gartner $657 in 2010, with prices expected to hit $482 by 2014.55 toward mobility, accessibility, and the convergence of the 57 “Apple’s App Store Downloads Top 15 Billion ” Apple, physical and virtual. http://www.apple.com/pr/ library/2011/07/07Apples-App- Store-Downloads-Top-15-Billion. html (created July 7, 2011). 58 Accenture 'Get Ready: Digital Lifestyle 3.0' report in late 2008. 59 “Generations Online 2010, Pew Internet and American Life Project 2011 Shift Index Measuring the forces of long-term change 61 Internet Users 3 Index 2011 Foundation

Exhibit 41: Total Number of Unique Viewers (Millions), October 2009 & October 2010 Exhibit 41: Total Number of Unique Viewers (Millions), (October 2009 & October 2010)

200

180

160

140

120

100

Unique Viewers, (Millions) 40

Oct 2009 UVs Oct 2010 UVs Source: comScore, Deloitte analysis

Source: comScore, State of The Internet Report, October 2010 The relatively low cost and nearly several prominent new markets are rapidly emerging — for example, online gambling tripled in size to hit 33 million instantaneous sharing of ideas, knowledge, UVs, while training & education doubled in size to hit 10 million UVs. Collectively, these growing user bases and skills facilitated by the Internet is making represent rich commercial opportunities and platforms for collaborative work considerably easier. exchange of information.

On a monthly basis, 84% of users viewed at least one online video; 94% of users conducted at least one search User behavior trends are both shaping, and shaped by, the with the average searcher conducting 123 searches. In evolving information-sharing capabilities of the Internet. addition, the U.S. Department of Commerce estimated that 41The October 2010 comScore State of the Internet Report © 2011 Deloitte Touche Tohmatsu total e-commerce spending in 2010 was $165 billion, up provides a snapshot of Internet user behavior in the 14.8% from 2009. As users spend more time and become United States: The average user was online 24.8 days in more comfortable on the Internet, they discover and the month, for a total of 31.7 hours, and viewed 2,620 create more diverse and robust ways to connect and share pages. Of the time spent online, the categories driving information.60 usage were search portals (6.5 hours per month per user), conversational media (4.3 hours per month per At the same time, societal trends and advances in the user) and entertainment (3.9 hours per month per user). digital infrastructure are also fostering new ways for users In addition, the content categories which attracted the to engage with the Internet—and with each other via the greatest numbers of unique visitors (UVs) per month were Internet. For instance, online games and game systems and community (180 million UVs), photos (142 million UVs), online music platforms have helped increase the number of sports (132 million UVs), and Newspapers (130 million active Internet users and will continue to fuel that growth. UVs). The content categories that experienced the greatest growth in absolute terms were Photos, Newspapers, As new segments of the population come online and and Sports, which each garnered 50, 46, and 37 million creative ways to engage emerge, there will likely be additional UVs, respectively. In terms of relative growth, substantial opportunities for sales, advertising, and

60 comScore, The State of the Internet in the U.S. in Q4 2010.

62 2011 Foundation 2011 Foundation Index Tab Title Here Tab A Safe Place for Kids to Play Online n 2005, Lance Priebe and Lane Merrifield, two game designers at New Horizon Productions in Kelowna, Canada, were looking for social networking sites for their 6-year-old children. They quickly realized the research. Take, for example, the growth of massively dearth of options — Facebook and MySpace were targeted at older multiplayer online role-playing games (e.g., World of Iaudiences and had yet to include any age-appropriate games for the 6-14 Warcraft) or the ecosystem of social networks (e.g., range. The pair decided to create their own. Out of the gap was born Club Facebook) and social game developers (e.g., Zynga) Penguin, one of the world’s most popular multiplayer online role-playing which cater to both mass market audiences and niche games. Introduced to the public in October 2005 with 15,000 initial beta segments. More than just consumers, new Internet users users, less than a year later Club Penguin had 2.6 million members. By late are influencers of purchase decisions and producers of 2007, when the Walt Disney Company purchased New Horizons Productions content. For instance, in recognition of the influence for $350 million, Club Penguin had 12 million user accounts.61 Now, in 2011, that children have on food and beverage purchase the game boasts a user base of 150 million children worldwide with multiple decisions, General Mills runs “Create A Comic” (a Web language versions.62 site where children can create animation starring patented characters) to promote its Honey Nut Cheerios cereal Club Penguin allows players to control avatars (cartoonish penguins) and brand.64 Likewise, the growth of online marketplaces like explore a winter-set virtual world. Like Second Life, players at Club Penguin Craigslist demonstrates how widespread Internet adoption spend most of their time interacting with each other and connecting through enables a significant number of individuals to partake in safe chat features. The world of the game includes multiple gathering spots, transactions which would previously have been impossible. shops, monthly parties, a theater where players can help stage a monthly The business opportunities afforded by Internet adoption play, costumes, and an in-game newspaper (The Penguin Times) offering will also carry risks, as users choose to engage in ways that comics, puzzles, and advice columns. Each penguin (user) has an igloo which may be unexpected or uncontrollable. they can personalize and invite friends to. Players also use in-game currency to buy virtual clothing, costumes, igloo decor, and to care for virtual pets. Internet-enabled collaboration has changed the game Players earn currency by playing a variety of fun mini-games and multiplayer during the past 20 years for pursuits as diverse as scientific games. Items, such as pins, flags, and stamps are either found hidden in the research, software development, conference planning, game or earned through mini-games and are used to display status. political activism, and fiction writing to name a few. We will continue to keep a close eye on how these changes Club Penguin works on a “freemium” model: All users can join Club Penguin bring utility and value to both customers and businesses and play for free, but paid monthly memberships drive most of the revenue. over time. Leveraging the creativity and collaboration of When Disney bought Club Penguin, approximately 90% of users were free, Internet users will be a key to businesses trying to keep up however, the game has increasingly tilted toward paid memberships with with a constantly changing future. an array of exclusive options and opportunities for paid subscribers in the game. Reviews note that options are limited for those who do not pay for membership, however, many children seem to continue to enjoy coming to Club Penguin into their teenage years. To maintain the appropriateness and safety for the target audience, the site includes filters, paid monitors, and multiple parental control features.63 Club Penguin’s success has led to video game spin-offs for Nintendo as well as several mobile applications. 61 http://www.clubpenguin.com/ company/news/070801-the-walt- disney-company.htm, The Walt Disney Company While the tremendous growth in Club Penguin’s user base has stalled 62 http://www.prnewswire.com/ recently (by April 2008, Nielsen reported that traffic to the site had shrunk by news-releases/club-penguin-gets- more-social-with-debut-of-new- 7%), multiple competitors have come on the scene. As long as the options features-132774688.html, PR Newswire for online entertainment and social media, targeted specifically at children 63 http://www.commonsensemedia. continue to evolve, internet use among the young shows no sign of abating. org/website-reviews/club-penguin 64 “In Online Games, a Path to Young Consumers.” New York Times, Apr 20, 2011 2011 Shift Index Measuring the forces of long-term change 63 Index 2011 Foundation Wireless Subscriptions

Explosion in wireless communication expands knowledge flow and reach

Introduction were approximately 340,000 Wireless Subscriptions; by The Wireless The network of mobile devices in America creates a platform 2010, this number was approximately 289.2 million. While Subscriptions metric for broad, robust, location-specific knowledge flows Wireless Subscriptions have increased at an 83% CAGR captures the number and drives increased connectivity among individuals and since 1985, reflecting the widespread adoption of the digital of active Wireless institutions. Together with the Internet Users metric, the infrastructure, this growth may begin to flatten or even Subscriptions as a Wireless Subscriptions metric represents the adoption of the decline as carriers attempt to better accommodate their percentage of the digital infrastructure. subscribers’ use of multiple devices. U.S. population based on CTIA’s Wireless Widespread adoption of the digital infrastructure enables In the past few years, consumers have become increasingly Subscriber Usage two- and multiway communication and the sharing of data, dependent on mobile devices to communicate. The nature Report. information, and knowledge from nearly any geographic of their communications is changing as well. Text messaging, location. People now have the ability to participate data services, applications, location-based services, and This metric is a proxy in knowledge flows anytime and anywhere, putting cloud storage are driving Wireless Subscriptions, evidenced for core technology information literally at their fingertips. With the ubiquity of by the proliferation of smartphone devices and rise of adoption. wireless connections, the proliferation of wireless devices media tablets. Like the smartphone before it, the tablet is and the development of new applications designed to transforming consumers’ use of wireless, from simple voice exploit wireless capabilities, carriers will be challenged to and text applications to email, word processing, games, manage capacity and to develop innovative pricing plans mapping, and social media. that will accommodate changing customer needs. However, even as tablets penetrate the market, they are Wireless Observations and Implications not cannibalizing mobile phones. Voice traffic was down As shown in Exhibit 42, the number of Wireless only 1.4% in 2010 and SMS/text traffic increased 22.9% Subscriptions 1 Subscriptions as a percentage of the population has grown with carriers reporting over 2.05 trillion text messages on rapidly, from 10% in the mid-1990s to to 92.7% in 2010 their networks.65 This combination of form factor, new In absolute terms, the numbers are striking. In 1985, there applications, and mobility is driving a completely new Updated Exhibit 42: Wireless subscriptions, (1985-2010) Exhibit 42: Wireless subscriptions (1985-2010)

100% 93%

90%

80%

70%

60%

50%

40% % of U.S.Population 30%

20%

10%

0% 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009

65 CTIA Wireless Data Useage Wireless Subscriptions Report 2011 Source: CTIA

64 Source: CTIA

demand for Wireless Subscriptions as shown in the almost 3% Cell Phone for all Folks uptick in subscribtions between 2009 and 2010. 2011 Foundation 2011 Foundation Index Tab Title Here Tab As consumers increasingly use more than one mobile device, hen Emily Connor moved out of her mom’s house during her second year of college companies are trying to create a standardized, interchangeable and started working part-time with four user experience across these multiple devices. For example, families, she knew it was time to get her internet search and social media are now available on the ownW cell phone, maybe even a smartphone. She was missing computer, smartphone, tablet, and even television. Similarly, connections with friends, missing important scheduling companies are creating applications designed to engage their changes for the families she babysat, getting lost driving in customers across all devices. These efforts will further reinforce unfamiliar neighborhoods and not making use of her time the trend toward using multiple devices. when her charges were sleeping. But the 21-year old college student did not have much of a credit history and she did Moreover, as wireless devices proliferate and new applications not have much cash to spare. Earning her money in cash are developed, Wireless Subscriptions, and the quantity of jobs, on paper she looked like the sum of her debt—student digital data, will continue to grow, requiring greater amounts of loans and delinquent payments on a store credit card. bandwidth, storage, and computing. The digital technology that At 68 years old, Cheryl Henry had heard all the horror stories allows for this ubiquitous connectivity has created an invisible about families getting hit with thousand-dollar cell phone infrastructure which is now enabling applications to work bills and she swore she was not interested. But when her together, such as personal health devices, parking meters, global husband’s health required her to begin making daily trips to positioning system (GPS), individual users, and giant databases. the VA hospital 60 miles away and she could never find a pay For business leaders, this invisible infrastructure has a profound phone and barely had time to email her children at night to effect on the ability to open up new markets, utilize new business keep them updated, she cautiously began to consider getting models, and reach parts of the world previously unreachable. a cell phone. When her son visited for a week, he had been able to pull all sorts of useful information off his phone The current generation of wireless devices is more useful and before they met with the doctor. She was spending hours at technologically advanced than any previous generation. In a time in hospital waiting rooms and often wished she could look up more information about what the doctors were the past two years, the number of devices with three or more telling her, just like her son did. But she was still intimidated transmitters — accommodating Bluetooth, Wi-Fi, and other types by a complex contract and the fear of running up expensive of connections in addition to cellular — has increased by 700%. phone bills every month. She did not want anything too But this explosion in the use of wireless technology is testing the fancy or complicated — just a functional phone that could capacity of our current networks. Not only are there more and help her meet her connectivity needs. more wireless devices, but each of them is consuming more and more data. A few years ago, both of these women would have had trouble getting a phone, and a plan, that met their needs. With the increase in subscribers who use multiple devices, carriers With prepaid cell phones, mobile providers hit upon an are exploring ways to streamline plans across these devices. innovative business model which allowed them to take European carriers are leading the way, offering shared data a minimal risk on new customers who do not have an established history, or who want to restrict their cost of plans that allow a user to share a data allotment across multiple usage, such as students, recent immigrants, or retirees. devices, such as an iPhone or iPad. The new shared plans target customers instead of SIM cards, consolidate subscriptions, Prepaid carriers, such as Metro PCS and Boost Mobile, have and remove one barrier to increased data flow. Similar plans now entered the smartphone market with low, all-inclusive are emerging in other countries, with the basic premise that a prices; smartphones are accessible not only to customers customer pays a small fee each month for each additional device without an established credit history, but also to newer that shares data. Recent announcements from Verizon indicate price-conscious customers who are unwilling to spend that carriers within the United States are also considering these on expensive smartphones. Today, Metro PCS customers plans — similar to existing plans that allow families or businesses can choose from 5 smartphone styles, the cheapest of to share minutes across multiple phones. Wireless routers, such which is $79 with no contract. As wireless communication as Novatel’s MiFi, allow customers to connect up to five wireless becomes more intrinsic in our lives; carriers are innovating the technology, equipment, and services to enable more devices to their own personal Wi-Fi hotspot. Should this trend individuals to receive and share information more freely. This toward consolidation of Wireless Subscriptions continue, we connectivity will scale further as technology advances and expect growth of this metric to slow or even decline. becomes even more accessible for all price bands.

2011 Shift Index Measuring the forces of long-term change 65 Index 2011 Foundation Economic Freedom

Increasing economic freedom intensifies competition while at the same time enhancing the ability to collaborate.

Introduction governments allow labor, capital and goods to move The Economic Changes in public policy also play a foundational role in the freely, and refrain from coercion or constraint of liberty Freedom metric Big Shift. Broadly speaking, policy trends toward economic beyond the extent necessary to protect and maintain measures how free liberalization on a global scale have been driving down liberty itself.” a country is across barriers to the movement of products, money, people, ten components of and ideas, both within countries and internationally. These Observations and Implications freedoms, which are flows intensify competition, putting pressure on margins, Globally, economic freedom suffered in 2010 due to the drawn from the Index and speeding the rate at which companies gain and lose financial crisis and global recession. The global average of Economic Freedom market leadership. Economic Freedom score for the 2010 Index is 59.4 produced by the (out of a possible 100), a 0.1 point decrease from 2009. Heritage Foundation The Economic Freedom metric represents the degree Exactly half of the world’s major economies curtailed and copublished to which public policies in a country support economic economic freedom to some degree by introducing various with The Wall Street liberalization. A higher Economic Freedom index for a interventionist measures. This was the first time in the Journal. country indicates more open policies regarding trade, history of the index that average economic freedom investment, finance, and business practices which further declined for consecutive years. This metric is a proxy catalyze and accelerate the foundational changes of the for openness of Big Shift. For the U.S., economic freedom (see Exhibit 43) has public policy and the trended upward from 1995 to 2006, increasing from an degree of economic The 2010 Index of Economic Freedom produced by the index value of 76.7 to 81.2 in 2006. However, since 2006 Economic liberalization. Heritage Foundation and copublished with The Wall Street U.S. economic freedom has fallen 3.2 points, ranking 8th Journal, described economic freedom as the “right of every out of 179 countries. This decline in economic freedom is Freedom 1 human to control his or her own labor and property… attributable to decreases in financial freedom, monetary with that freedom both protected by the state and freedom, and property rights. The recent passing of the unconstrained by the state. In economically free societies, Dodd-Frank Act introduced broad-sweeping regulations Updated Exhibit 43: Index of Economic Freedom (U.S.), (1995-2010) Exhibit 43: Index of Economic Freedom (U.S.) (1995-2010)

82 80.9 81

78 value 76.7 78.0 77 Index Index

76 75.7 75

72 1995 1997 1999 2001 2003 2005 2007 2009

Index of Economic Freedom (Overall Score) Linear (Index of Economic Freedom (Overall Score)) 66 The Heritage Foundation & the Wall Street Journal, 2011 Index of Economic Freedom Source: Heritage Foundation's 2010 Index of Economic Freedom

to the financial sector, including capital holding requirements which impact Fighting for the Right a bank’s lending capabilities.The United States remains above the world to Braid average in all but the government spending and fiscal freedom components, with labor freedom and business freedom scoring the highest at 94.8 and oday, Melony Armstrong of Tupelo, 91.3, respectively. Mississippi, runs her own African hair braiding business and a school where she teaches the art. However, Melony does not take Historically, the primary drivers of economic freedom in the United States (in Ther teaching for granted. In all but a handful of states, terms of percentage increases since 1995) have been: trade freedom (8.5%), performing African hair braiding professionally without a business freedom (6.3%), investment freedom (5%), and fiscal freedom government-issued license is illegal. Until 2005, regulations (3.5%). set by Mississippi’s State Board of Cosmetologists required that Melony complete 3,200 hours of coursework to be Open labor markets enhance overall employment and productivity growth. allowed to teach African hair braiding. Even though the There is a positive correlation between labor freedom and Migration to coursework had little to do with African hair braiding, the “Creative Cities,” Travel Volume, and Labor Productivity. Open labor markets requirements allowed practicing cosmetologists to keep enable individuals to pursue jobs of choice and to congregate in “spikes,” barriers to entry into their industry high. This all changed geographies where talent is concentrated, such as Silicon Valley and when Melony Armstrong took on the state’s costmetology establishment, joining with two aspiring hair braiders and Boston. Our case research shows that these spikes are expected to foster the Institute for Justice to file a lawsuit against the state to opportunities for rich and serendipitous connections that help to accelerate contest these regulations. talent development and improve productivity. Additionally, we would expect that workers who are free to select jobs of choice will be more passionate The Institute for Justice is a pro bono law firm that about their work and eventually more productive. engages “in cutting-edge litigation and advocacy both in the courts of law and in the court of public opinion Business freedom has a strong positive correlation with Competitive Intensity on behalf of individuals whose most basic rights are and GDP. The greater the business freedom, the more competitive the denied by the government — like the right to earn an environment and the greater the overall economic output of the country. honest living, private property rights, and the right to The U.S. regulatory environment supports the freedom to start a business, free speech, especially in the areas of commercial and which lowers barriers to entry and facilitates rich entrepreneurial activity. Internet speech.”66 Even with a high rating for Economic Freedom in the United States, there are still regulatory According to the Heritage Foundation’s report and the World Bank’s Doing 67 barriers that make it difficult for struggling entrepreneurs Business study , starting a business in the United States. takes six days to enter many business arenas. Through organizations like compared to the world average of 38. The United States also has some the Institute for Justice, these remaining barriers are being of the most straightforward bankruptcy proceedings in the world, which challenged and overcome. The Institute for Justice selects may encourage more businesses to take the calculated risks that can spur cases where government-imposed licensing requirements innovation and competition. make it impossible for entrepreneurs to start their own businesses with the intent of laying a broad foundation for Compared to other countries, the labor, financial, and business markets in future litigation to free other industries and occupations. the United States are some of the most open and modern in the world. As The effects of such licensing restrictions are starkest for other countries adopt more open policies, the competition and disruption businesses that require little capital or education. The we have described will increase. We should note, however, that, unlike the licensing laws for braiding hair seemed a perfect example. persistance of digital technology performance trends, continued trends Melony’s efforts paid off when the the Mississippi Senate toward economic liberalization are much less certain. The current economic voted to amend the Board of Cosmetology’s regulations turmoil in world markets creates real potential for a public policy backlash, around hair braiding licenses. Now, African hair braiders thus potentially driving some countries to erect protectionist barriers. While are only required to register with the Department of protectionist public policies could temporarily constrain some of the forces Health, post basic health and sanitation guidelines at driving the Big Shift, they would be difficult to sustain unless large parts of their places of work, and complete a self-test on that the world followed suit. information. Thanks to their efforts, thousands of 66 Institute for Justice Website. Ij.org. entrepreneurs across Mississippi can now be free to pursue 67 Doing Business 2009, World Bank their career of choice. Group, http://www.doingbusiness.org/ ExploreEconomies/?economyid=197 (updated 2009). 2011 Shift Index Measuring the forces of long-term change 67 2011 Flow Index

Virtual Flows 74 Inter-Firm Knowledge Flows 79 Wireless Activity 82 Internet Activity

Physical Flows 86 Migration of People to Creative Cities 90 Travel Volume 92 Movement of Capital

Flow Amplifiers 96 Worker Passion 102 Social Media Activity

68 2011 Shift Index Measuring the forces of long-term change 68 2011 Flow Index Tab Title Here Tab 2011 Flow Index Sources of economic value are moving from “stocks” of knowledge to “flows” of new knowledge

Remote communications today are easier than ever. both kinds of flows, making them even more meaningful. Wireless connectivity and Internet access are virtually Some of the findings from our inaugural research are given ubiquitous in the United States, and there is rarely a below: moment today that we are not connected to the rest of the world. What may seem commonplace today • Talent migrates to the most vibrant geographies and was a luxury little less than two decades ago. As the institutions because that is where it can improve its digital infrastructure penetrates ever more deeply performance more rapidly by learning faster. Our analysis into the social and economic domains, practices from shows that the most creative cities tend to grow much personal connectivity are bleeding over into professional faster than the least creative cities; in fact, between connectivity: Institutional boundaries are becoming 1990 and 2008, the top 10 creative cities grew more increasingly permeable as employees harness the tools than twice as fast as the bottom 10. This migration to they have adopted in their personal lives to enhance their creative cities is not only beneficial for the cities and professional productivity, often without the their economic livelihood; it also correlates with an knowledge, and sometimes despite the opposition, of their increase in Returns to Talent. By better understanding the employers. drivers of the disproportionate growth in creative cities, business leaders can create organizations that mimic the With the Flow Index, we measure the changes in social environment that makes those cities so creative. and working practices that are emerging in response to • Companies appear to have difficulty holding onto the new digital infrastructure. More and more people are passionate workers. Workers who are passionate about adopting practices that utilize the power of the digital their jobs are more likely to participate in knowledge infrastructure to create and participate in knowledge flows. flows and generate value for their companies — on Our approach to measuring these knowledge flows average, the more passionate participate twice as much includes measuring flows of capital, talent, and knowledge as the disengaged in nearly all the knowledge flows across geographic and institutional boundaries. activities surveyed. We also found that self-employed people are more than twice as likely to be passionate The Flow Index measures Virtual Flows, Physical Flows, about their work as those who work for firms. The and Flow Amplifiers. Virtual Flows occur as a direct result a current evolution in employee mindset and shifts in strong digital infrastructure. As computing, digital storage, the talent marketplace require new rules on assessing, and bandwidth performance improve exponentially, managing and retaining talent. virtual flows are likely to grow more rapidly than the other • Knowledge flows across companies are currently in drivers of the Flow Index. However, Physical Flows will their infancy. But our survey-based research indicates not be fully replaced by Virtual Flows. As people become that increased interest and participation in new types of more and more connected virtually, the importance of knowledge flows available through the current digital tacit knowledge exchange through physical, face-to-face revolution, such as participation in social media and use interactions will only increase, leading to more physical of Internet knowledge management tools, will likely flows. Both Virtual and Physical Flows are enriched by Flow drive a marked increase in knowledge flows across firm Amplifiers. These amplifiers enhance the robustness of boundaries. 36% of those surveyed this year currently

2011 Shift Index Measuring the forces of long-term change 69 Tab2011 Flow Index Here Title

Internet traffic in North America is expected to better understanding the role travel plays in a Big Shift world, business leaders can more strategically consider almost quadruple from 2010, increasing at a the trade-offs when making decisions about travel. • Historically, FDI has been viewed as a way to improve 26% CAGR to hit 22,000 petabytes per month efficiency, obtain resources, participate in labor arbitrage, by 2015. and enjoy privileged access to local markets, which often favors local manufacturers. However, increasingly, firms are taking a more strategic long-term view by participate in social media in the professional sphere approaching FDI opportunities as ways to identify and across firms and will likely drive significant growth in access pockets of talent and innovation across the knowledge flows in coming years. This assumption is also globe. U.S. FDI flows (both inflows and outflows) have supported by our research on the growth of social media increased steadily over the past few decades, with capital platforms: Between 2007 and 2008, the total minutes movement in 1970 being only 3% of what it is today. spent on social media sites increased 27, while the • Wireless Activity (mobile phone usage in minutes talked same metric increased 48% between 2009 and 2010. and SMS text messages sent) and Internet Activity Moreover, the average daily visitors to social media sites continue to grow exponentially. Ten years ago, the grew to 94 million in 2010, up 52% year over year from average user spent 64 minutes per month on his or 62 million in 2008. her mobile phone; today, the average user spends over • Residents of the United States. travel more and more 600 minutes per month on their mobile phone. SMS each year. And as people’s movement increases, Big text messages, which are a more recent phenomenon, Shift forces are amplified and opportunities for rich have shown similar growth: in Q1 2009, the average and serendipitous connections are more likely. Travel U.S. mobile subscriber sent/received 486 text messages within the United States has increased 56% over the per month. By the end of 2010, the average number past 19 years. This rise in travel also correlates with of text messages sent/received grew to over 600 per labor productivity, suggesting that the amount people user per month. On the Internet, traffic across the 20 travel can directly affect the way they work. One highest-capacity routes has grown 37% in the past year. plausible explanation for this is that people benefit in The on-demand rich media experiences offered by the Flow Index multiple ways from the physical interactions that are ever-improving modes of virtual communications will more likely as a result of higher travel volume. Face-to- Drivers 1 continue to shape how we interact with the world, both face interactions will always play a role in promoting personally and professionally. productive and trust-based business relationships. By

Exhibit 44: Flow Index trends, (1993-2010) Exhibit 44: Flow Index (1993-2010)

180

160 155 145 139 140 128 117 120 104 97 100 89 83 77 80 72 Index value Index 65 61 57 60 51 54 47 49

0 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Source: Deloitte analysis

70 Source: Deloitte analysis

Exhibit 45: Flow Index drivers, (1993-2010) Exhibit 45: Flow Index drivers (1993-2010)

180 Title Here Tab 2011 Flow Index

160

140

120

100

80 Index value Index

0 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Virtual Flows Physical Flows Amplifiers Source: Deloitte analysis Source: Deloitte analysis

Taking a step back, we can see the interrelated nature structure, this index will likely serve as a lagging indicator of many of the foundation and flow metrics discussed of the Big Shift, trailing behind the Foundational Index. As in this report. The results of our research have shown such, we track the degree of lag over time. that as economic freedom increases, people are freer to take control over their careers and lives. This leads to an Eight metrics within three key drivers are included in the increased likelihood of mobility and a profound increase in Flow Index: population growth within creative cities. These epicenters of creativity, with a high concentration of talent, have • Virtual Flows: Knowledge flows enabled by advancing helped to propel recent growth in GDP and power much of digital infrastructure and its impact on increasing virtual the increase in productivity. We attribute this, in part, connections. This driver consists of three metrics: Inter- 45to the increased opportunity for rich and serendipitous Firm Knowledge Flows, Wireless Activity, and Internet © 2011 Deloitte Touche Tohmatsu encounters. Activity. • Physical Flows: Knowledge flows enabled by the The Index movement of people and capital, strengthening virtual The Flow Index, shown in Exhibit 44, has a 2010 score connections with physical interaction. This driver consists of 155 and has increased at a 7% CAGR since 1993.68 of three metrics: Migration of People to Creative Cities, The Flow Index measures the velocity and magnitude Travel Volume, and Movement of Capital. of knowledge flows resulting from the adoption of • Flow Amplifiers: Knowledge flows amplified and practices that take advantage of the advances in digital enriched as people’s passion for their profession infrastructure and public policy liberalization. increases and technological capabilities for collaboration improve. This driver consists of two metrics: Worker The metrics in the Flows Index capture physical and virtual Passion and Social Media Activity. flows as well as elements that can amplify a flow — examples of these “amplifiers” include social media use and Historically, the Flow Index has grown at an increasing rate, the degree of passion with which employees are engaged reflecting faster and faster growth in its underlying metrics. 68 For further information on how with their jobs. Given the slower rate with which social and Exhibit 44 shows the contribution of each metric to the the Flow Index is calculated, please see the Shift Index professional practices change relative to the digital infra- overall index value, and Exhibits 46 through 48 show the Methodology section. Note that because several metrics in the Flow Index are indexed to 2008 due to limited- data availability, the value in 2003 (the base year) does not equal 100. 2011 Shift Index Measuring the forces of long-term change 71 Flow Index Drivers 3

Exhibit 46: Virtual Flows, (1993-2010) Exhibit 46: Virtual Flows (1993-2010) Tab2011 Flow Index Here Title

40 Index value Index 30

20 Flow Index

10 Drivers 4

0 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Source: Deloitte analysis Exhibit 47: Physical Flows, (1993-2010) Source: Deloitte analysis Exhibit 47: Physical Flows (1993-2010)

The charts (right) represent the 60 combined movements of the underlying metrics in the index, 50 after data adjustments and indexing to a base year of 2003. Due to data availability, certain 40 Flow Index metrics were indexed Index value Index © 2011 Deloitte Touche Tohmatsu to 2008. For more information 46 30 on the index creation process, see the methodology section of 20 the report. Flow Index

10 Drivers 5

0 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Source: Deloitte analysis Exhibit 48: Flow Amplifiers, (1993-2010) Source:Exhibit Deloitte 48: analysis Flow Amplifiers (1993-2010)

0 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Source: Deloitte analysis 72 Source: Deloitte analysis

growth of each index driver. Comparing the three, it is A key challenge for companies in the 21st evident that the Virtual Flows and Amplifiers have been driving the increasing rate of the change of the Flow Index. century is to become more open to ideas from

As shown in Exhibit 46, Virtual Flows have grown at a the outside and to make use of resources consistently accelerating pace with an overall CAGR of wherever they may be located, internally or 11%. This has been powered by the exponential growth of wireless and Internet Activity. We expect this trend to externally. continue if not accelerate, as the above metrics continue growing exponentially, and knowledge flows between Therefore, the more recent curvature of the graph is a companies start increasing exponentially as well. In reflection of the recent exponential growth in Social Media contrast, Physical Flows, as shown in Exhibit 47, have Activity. grown fairly linearly, with a CAGR of 6%. We expect this trend to continue at a steady pace, reflecting the long-term Overall, we expect the Flow Index to grow at an ever- secular trends in capital flows, Migration of People to increasing pace in the coming years. With more people Creative Cities, and travel. adopting new conventions and practices that take advantage of the advances in digital infrastructure, it is Exhibit 48 depicts Flow Amplifiers, which were flat initially, very likely that the growth rate of this index may eventually but started growing near the millennium; this is a function surpass that of the Foundation Index. of both the metrics and the methodology. The initial period reflects the two metrics in this category (Worker Passion and Social Media Activity) both being relatively new (one is based on a custom survey, and the other represents a recent phenomenon). With no prior data for Worker Passion, we assumed a flat trend for passion for the past years using job satisfaction trends as a rough proxy.

2011 Shift Index Measuring the forces of long-term change 73 2011 Flow Index Inter-Firm Knowledge Flows

Individuals are finding new ways to reach beyond the four walls of their organization to participate in diverse knowledge flows

Introduction The Inter-firm As the digital infrastructure and public policy shifts While it would be impossible to quantify the core and Knowledge Flows undermine stability and accelerate change, the primary richness of the types of flows that harness the greatest metric is a normalized sources of economic value are shifting. “Stocks” of value, we have attempted to look at the drivers of rich, measure of how much knowledge—fixed and enduring know-how and personal interactions as a proxy for interfirm knowledge workers participate experience—were once what companies accumulated flows. In our survey-based study, each respondent was in eight categories and exploited to generate profits. Think of the proprietary scored based on how frequently the individual participated of activity in their formula for baby foods or the patents protecting in each of eight activities that suggested the potential professional lives, blockbuster drugs in the pharmaceuticals industry. for knowledge flows. Some of the activities, such as ranging from the use of conference attendance, represent more traditional social media to connect In a less predictable and faster changing world, however, professional networking while others, such as social media, with other professionals stocks of knowledge depreciate more quickly. The value are relatively new to the professional world. Over time, we to attendance at of what we know at any one point in time diminishes. As expect to be able to see trends regarding participation in conferences. one simple example, consider the rapid compression of various kinds of interfirm knowledge flows and the impact product life cycles occurring in most industries. Even the of that activity on organizations. This metric is a proxy for most successful products are quickly supplanted as new knowledge flows across generations come through the pipeline faster and faster. Observations and Implications firms. In the past, companies had time to exploit what they The Inter-firm Knowledge Flow score is an index value learned and discovered and could generate value from that of participation in knowledge flow activity; thus it is best knowledge for an indefinite period. Not anymore.69 understood relative to other years or compared across industries or job types rather than as an absolute number. To succeed now, companies (and individuals) have to For the past three years, the Inter-Firm Knowledge Flow continually refresh what they know by participating in Index value has remained the same. This means that, on relevant “flows” of knowledge that extend beyond the average, workers are participating in knowledge flow four walls of the firm. Tapping into these flows, especially activities at about the same frequency they were three those that create new knowledge, increasingly defines years ago, and that overall, there is still opportunity for one’s competitive edge. Technological advances that allow workers to become more active in connecting with others people to connect virtually enable greater participation in in their professional lives. flows. By enabling individuals to seek new perspectives, keep While research suggests a high correlation between abreast of innovative approaches and learn from seasoned interfirm knowledge flows and innovation70, a critical practitioners, interfirm knowledge flows serve two key subtlety is that some types of flows result in greater purposes: refreshing organizational knowledge and benefits. We believe the most valuable knowledge is infusing worker passion. The stagnation in the Inter- tacit knowledge — the knowledge which resides in our Firm Knowledge Flow value suggests that individuals are heads and which cannot easily be codified or abstractly not seeking out external sources of information or that aggregated. Tacit knowledge often embodies critical companies are failing to equip their employees with access insights about processes or nuances of relationships to interfirm flows. This limits the organization to the stocks 69 Deloitte Research and is best communicated through stories and personal of knowledge amassed by current employees. 70 See, for instance, Alessia Sammarra and Lucio Biggiero, connections—modalities that are discounted in most “Heterogeneity and Specificity of enterprises. Inter-Firm Knowledge Flows in Innovation Networks,” Journal of Management Studies 45, no. 4 (2008): 800-29.

74 Inter-Firm Knowledge Flows Tab Title Here Tab 2011 Flow Index

Although the overall level has not changed, respondents’ has declined, while use of social media is trending up participation in each type of knowledge flow activity is over three years, indicating increased acceptance of slowly changing (see Exhibit 49). Physical events, such as new platforms and methods of tapping into knowledge IFKF 1 conferences and lunches, persist as the most common type flows. The marketing, human resources (HR), and sales of interfirm knowledge flow — 46% of those surveyed functions lead in use of social media, while customer reported attending at least one conference per year. service, accounting/finance, and manufacturing lag. Participation in online forums and community organizations While newer methods of interaction like social media are Updated Exhibit 49: Percentage participation in Inter-Firm knowledge flows, (2011-2009) Exhibit 49: Percentage participation in Inter-Firm knowledge flows (2011-2009)

100%

90%

80%

70%

60%

48% 50% 46% 47%

39% 37%37% 37% 38%37% 38% 40% 35% 36% 33%33% 33% 34% 31% 32% 32%

Percentage participation 30% 26%25% 22% 19% 19% 20% 10%10% 10% 0 0% IFKF 2 Email alerts Online Community Lunch Web Casts Professional Telephone Social media Conferences groups/forums organizations meetings organizations

2011 (n=3108) 2010 (n=3108) 2009 (n=3201) *2011 Email Alerts redefined

Source:Note: 2011 Synovate Email Alerts 2011, redefined 2010, 2009 ExhibitWP/IFK Measurement50: Inter-Firm = Significantly knowledge higher flow at participation 95% confidence and interval frequency, (2011) Source: Synovate 2011, 2010, 2009 WP/IFK Measurement = Significantly higher at 95% confidence interval Exhibit 50: Inter-Firm knowledge flow participation and frequency (2011)

60%

50%

40%

10%

0% Using social Email alerts Conferences Web Casts Telephone Lunch Community Professional Online media meetings organizations organizations discussion Daily Several times a week Weekly forums A few times a month Monthly Once every few months Once a year Less often than once a year Source: Synovate, Deloitte analysis Source: Synovate , Deloitte analysis 2011 Shift Index Measuring the forces of long-term change 75

IFKF 3

Would like to shorten the y-axis to 10% to 70%

Exhibit 51: Social media usage by employee function, (2009-2011) Exhibit 51: Social media usage by employee function (2009-2011)

70%

60%

50%

40%

30% by employeeby function

20% Percentage of employeesusing socialmedia, 10% 2009 2010 2011 IFKF 4 Marketing Human Resource Sales Management Supply Chain/Logistics IT/Technology Accounting/Finance Other Manufacturing Customer Service Source: Synovate, Deloitte analysis Source: Synovate , Deloitte analysis Exhibit 52: Percentage participation in Inter-Firm knowledge flows by user age, (2011) Exhibit 52: Percentage participation in Inter-Firm knowledge flows by user age (2011)

60% 56% 52% 52% 49% 49% 49% 50% 38% 36% 47% 42% 42% 32% 40% 48% 39% 40% 36% 37% 31% 35% 35% 37% 34% 33% 33% 46% 32% 10% 33% 34% 37% 32% 10% 35% 29% 28%

30% 27% IFKF Metric 39% 33% 38% 33%

20% 17% 17% Percentage participation 19% 19%

10%

0% Email alerts Online Community Lunch Web Casts Professional Telephone Social media Conferences groups/forums organizations meetings organizations

0-24 25-34 35-44 45-54 55-64 65+ *Note:*Note 2011 2011 Email Email Alerts Alerts redefined redefined Source:Source: Synovate Synovate 2011, 2011, 2010, 2010, 2009 2009 WP/IFK Measurement = Significantly higher at 95% confidence interval WP/IFK Measurement = Significantly higher at 95% confidence interval

SpiceWorks & The Guild of Sommeliers gaining acceptance in customer-facing applications, firms hat does a master sommelier have in common with seem reluctant to apply these technologies to business your office IT support staff? And what does this operations. mean for you? Of all types of flows, social media, Web forums, and alerts ChancesW are that both are connecting with other professionals in are among of the few flows that employees engage in on their fields and questing online for insights on how to improve their a daily or weekly basis. With the capability of immediate performance. If knowledge is power, then the potential for self- and iterative information and feedback loops, employees empowerment has grown tremendously with the profileration of are able to access and digest information as they need it in web-based platforms where geographically dispersed users of diverse a way that is applicable to their work. skill levels sign on to access high-value knowledge flows and build their expertise. There is a strong correlation between age and the types of flows in which employees are likely to participate. Younger The Spiceworks Community boasts a membership of 1.5 million IT employees gravitate toward social media, while employees professionals from 196 different countries who share IT best practices, older than 45 are more likely to attend conferences or how-tos, product reviews, relevant articles, and scripts and codes connect by phone, over lunch, or within a professional through a web-based forum. Part professional association and part organization. software company, Spiceworks has grown rapidly since it began in 2006 with the mission to, in the words of CEO and co-founder Scott There is a predictable correlation between an employee’s Abel, “simplify the lives of small and medium business (SMB) IT pros.” role within a company71 and participation in different Members ask questions, contribute expertise, and provide feedback types of knowledge flows. Individuals in senior roles to influence vendors. They are encouraged to form SpiceCorps, have higher participation across all types of knowledge local, member-driven groups that host in-person networking events. flows (see Exhibit 52) — though most pronounced in SpiceWorld provides an annual conference for users, community conferences, lunch meetings, phone calls, and professional members, and IT vendors to meet and exchange ideas in person. organizations. Of respondents at the executive and senior manager level in the 2011 survey, 95% indicate they The Guild of Sommeliers enables wine and hotel and restaurant participate in at least one type of interfirm knowledge flow professionals from across the globe to tap into the knowledge of the — as compared to 85% at the middle management level best wine professionals to keep members on top of new developments (increased from ~80% in 2009), and 70% at the frontline and standards. It fosters collaboration, inspiration, and ongoing level (increased from ~65% in 2009). Executive and senior education for the sommelier community through discussion forums, manager participation has remained consistent over three study groups, blogs, quizzes, and a compendium knowledge base in years of survey data. addition to live networking and enrichment events and tastings. Guild President, Fred Dame, led the founding of the U.S. Guild in 2003 to Inter-firm knowledge flows can fuel efficiency and extend the educational reach of the Court of Sommeliers (which is open innovation, benefitting the entire organization by providing only to Master Sommeliers) “to promote the knowledge and service of access to flows that are relevant to a function or position. fine wine and cuisine.” The web-based membership forum also includes Corporations have an imperative to make interfirm job postings and social networking. knowledge flows available and to train employees on how to maximize their use (e.g., identifying, digesting, Whether you are looking to solve a specific problem at work or delve deeper into your passions, online communities offer new opportunities to connect, build knowledge, and drive performance to new levels. 71 Our survey explicitly defined the administrative role as one with clerical or assistant duties and the executive role as a CEO, COO, president, senior VP, director, or VP.

2011 Shift Index Measuring the forces of long-term change 77 IFKF 5

2011 Flow Index Updated Exhibit 53: Inter-Firm knowledge flow participation by level, (2011) Exhibit 53: Inter-Firm knowledge flow participation by level (2011)

80%

70%

60%

50%

40%

30% Percentage participation 20%

10%

0% Executive Senior Middle Lower-level Non-Management Administrative Manufacturing Management Management Management Conferences Telephone Professional Organization Web Casts Lunch Meetings Social Media Community Organization Google Alerts

Source: Synovate, Deloitte analysis Source: Synovate , Deloitte analysis

By enabling individuals to seek new flows to impact firm performance. As engagement and collaboration platforms profilerate, understanding how to perspectives, keep abreast of innovative use these flows will be increasingly important.

approaches and learn from seasoned While many executives pursue the supposed nirvana of practitioners, interfirm knowledge flows serve a frictionless economy, we believe that aggressive talent development inevitably and necessarily generates friction. IFKF Metric two key purposes: refreshing organizational A key challenge for companies in the 21st century is to 53 become more open to ideas from the outside and to make © 2011 DeloitteWrite Touche-Tohmatsuup knowledge and infusing worker passion. use of resources wherever they may be located, internally or externally. Enabling and encouraging participation in and filtering). As Sun Microsystems co-founder Bill Joy interfirm knowledge flows, while providing appropriate observed, "There are always more smart people outside guidance, governance, and training programs, will your company than within it." Companies should look help create a robust network of internal and external for ways to increase participation in interfirm knowledge relationships, providing opportunities for the “productive flows at all levels of the organization, while also better friction” that results when people with different harnessing the knowledge of all employees inside the firm. backgrounds and skill sets engage with each other on real problems.73 Friction forces people out of their comfort Increasingly, “socialytic” tools72 enable firms to monitor zones and often involves confronting very different flows with customers and partners, as well as flows views as to the right approach to a given challenge or within the enterprise, to improve performance. Currently, opportunity. This friction will shape the learning of the socialytics are most often used to understand customer individual and the organization. behavior or to measure the efficacy of marketing campaigns; however, a potentially more exciting use is to evaluate employee interpersonal engagement relevant to performance. In our preliminary socialytics analysis of

72 Socialytic tools are business flows within the enterprise (including use of Web, email, applications that apply analytics social media, and VOIP) we gained substantial insight into against social and collaborative networks. Defined by IDC in the effective use of interfirm and intrafirm knowledge "Predictions 2010: Recovery and Transformation" report. 73 John Hagel III and John Seely Brown, “Productive Friction: How Difficult Business Partnerships Can Accelerate Innovation,” Harvard Business Review, February 1, 2005.

78 Wireless Activity 2011 Flow Index Wireless Activity is surging due to demand for mobile data and a growing ecosystem of applications and services

Introduction although the strong upward trend began to flatten by Wireless telephones and mobile internet are increasingly 2009. Text messaging volume also increased exponentially, The Wireless Activity vital communication channels which enable knowledge from 14 million in 2000 (the earliest year for which data metric measures flows. Measuring knowledge flows directly is difficult, are available) to 173 billion in 2010. The growth rates the total number of if not impossible, however, wireless minutes and text for these two activities highlight the shift in how users wireless minutes and messaging volume provide suggestive proxies for are engaging wireless technology to connect with and total number of SMS knowledge flow activity on mobile devices. Together, they share information with one another. Wireless minutes messages in the United represent the increasing degree to which connectivity have grown at a CAGR of 32% over the past 19 years as States per year. and mobility are becoming essential in both personal and compared to SMS messages (see Exhibit 54), which grew professional life. at a CAGR of 156% over the past ten years. SMS volume This metric is a proxy rose more than four times as quickly as wireless minutes for connectivity and Wireless Activity is highly correlated to the technological did in its first ten years. This rapid growth of SMS volume knowledge flows. advancements of the digital infrastructure that enable could be attributed to technological advancements, such users to leverage mobile phones in a multitude of ways. as intercarrier texting, as well as shifting social norms. As a platform for knowledge flows, Wireless Activity will continue to grow as technology metrics, such as While both forms of wireless activity have boomed, Exhibit Computing, Digital Storage, and Bandwidth evolve at 55 suggests that mobile phone calls are losing ground exponential rates. to text messaging, particularly in younger demographics. According to a Neilsen survey, The typical teenaged mobile Observations and Implications subscriber (age 13-17) in the United States now sends or As shown in Exhibit 54, both wireless minutes and text receives 2,779 text messages per month and uses only Wireless Activity messaging volume have risen sharply over the past decade 631 voice minutes.74 We expect this trend to continue as 1 despite competing connectivity applications, such as the short and simple SMS medium gains popularity among computer-based instant messaging. Total wireless minutes other demographics. have grown from 11 billion in 1991 to 2.24 trillion in 2010, Updated Exhibit 54: Wireless Activities: Wireless minutes, (1991-2009) vs. SMS volume, (2000-2009) Exhibit 54: Wireless Activities: Wireless minutes (1991-2009) vs. SMS volume (2000-2009)

2,500 200 2,241 180

2,000 173 160

140 )

1,500 120

100 Volume (Billions 1,000 80 SMS SMS

Wireless Minutes (Billions) 60

500 40

0 0 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009

Wireless Minutes SMS Volume 74 The Neilson Company, April 2009- Source: CTIA, Deloitte analysis March 2010 and Deloitte Analysis 2011 Shift Index Measuring the forces of long-term change 79 Source: CTIA, Deloitte analysis

Wireless Activity 2

Updated Exhibit 55: Average Number of Monthly Phone Calls and Text Messages by Age Group Exhibit 55: Average Number of Monthly Phone Calls and Text Messages by Age Group

2,779 <18 631

1,299 18-24

592 25-34 952

441 35-44 896

234 45-54 757

80 55-64 587

32 65+ 398

0 500 1000 1500 2000 2500 3000

Texts sent/received Voice Minutes Used Source: CTIA, April 2009-March 2010, Deloitte Analysis

Source: CTIA, April 2009-March 2010, Deloitte Analysis Mean data consumption increased from about that more than 10 billion applications had been downloaded from the App Store, ranging from games to 90 MB per month during the first quarter of travel applications to social media.76 The explosive growth in applications has spurred data consumption and allowed 2009 to 298 MB per month during the first users to participate in knowledge flows in many different quarter of 2010. ways.

Increased wireless activity both reflects and enhances In recent years, the rapid growth of data consumption the frequency and richness of virtual connections. has marked another fundamental shift in how individuals Improvements to wireless technology and mobile internet communicate and disseminate information via their 55 access have empowered individuals to connect — through © 2011 Deloitte Touche Tohmatsu wireless devices. Mean data consumption increased from email, social media, blogging, etc. — at all times and in all about 90 MB per month during the first quarter of 2009 places. to 298 MB per month during the first quarter of 2010.75 This growth is concentrated amongst the heaviest users; in 2010, the top 10% of data users generated approximately 90% of all traffic. Smartphones, and more recently media tablets, have driven this data-centric usage by making mobile browsing easy for the user.

75 “Quantifying the Mobile Data Tsunami and its Implication”. Meanwhile, the robust application marketplace is June 30, 2010 The Nielson Company. http://blog.nielsen.com/ fundamentally changing the way customers engage with nielsenwire/online_mobile/quantifying-the-mobile-data-tsunami- their mobile devices; in January 2011, Apple announced and-its-implications/ 76 “Apple App Store Reaches 10 Billion Downloads” http:// news.cnet.com/8301-13579_3- 20029267-37.html

80 2011 Flow Index

Apps Help Clean an Oil Spill

n April 20, 2010, the explosion of Deep Water Horizon caused the largest marine oil spill in history, releasing up to 4.9 million barrels of oil and causing economic and ecological distress in the Gulf Coast region.O In the wake of this cataclysmic event, citizens were angry and concerned—they saw oil seeping into their fishing grounds, waterways, marshes, and beaches and wanted to make sure that everyone understood their reality and that someone cleaned it up. Meanwhile government agencies and civic organizations scrambled to deploy resources effectively across a vast and dynamic spill zone. There were hotlines and other outlets to report spill activity, but these methods had two weaknesses: inaccuracy and the high level of effort required for a citizen to file a report. Enter wireless technology and applications.

Using smartphone applications, such as SpillMap77, regular citizens could tag a location and submit content-rich incident reports complete with text, photos, and video. This geo-aware and open-source application tapped into the power of crowd sourcing and mobile activity, allowing users to tag incidents in seconds, without logging in or waiting on hold. With over 15,000 posts, SpillMap (and the corresponding Web site, spillmap.org) made real-time conditions publicly available to government agencies, civic organizations, and other interested parties. Not only did the volume of incidents reported on SpillMap exceed the volume of incidents reported on many hotlines, but the geo-specific and image-rich posts often provided greater value, helping volunteer organizations prioritize and deploy resources, and allowing users all over the country to receive updates in real time. The success of Spillmap is just one example of how wireless communication options have transformed not only how we connect with one another but also with the world.

77 SpillMap App. Android Market. https://market.android.com/ details?id=com.spillmap.android 2011 Shift Index Measuring the forces of long-term change 81 Tab2011 Flow Index Here Title Internet Activity

Broader availability of internet access enables “connected-ness” with a growing range of people, resources, and rich content

Introduction Observations and Implications The Internet Activity Over the past decade, the channels that support Internet Activity has grown exponentially in the last metric measures connection over the Internet have continued to grow. From 20 years. For the top 20 routes (in terms of capacity), Internet traffic for the email to instant messaging to streaming video to social average Internet traffic increased 58% between 2009 and 20 highest capacity media—there are ever-increasing ways for people to share 2010. Some of the most rapid growth was found along U.S. domestic Internet information, communicate, and view content. The richness the following routes: Chicago-Denver, New York-San routes in gigabits/ and magnitude of the data transmitted across these Francisco, and Chicago-San Francisco. As shown in Exhibit second as calculated by channels is constantly expanding as a result of the societal 56, internet traffic in North America is expected to almost TeleGeography, which and technological changes that provide the foundation for quadruple from 2010, increasing at a 26% CAGR to hit determines Internet this activity. 22,000 petabytes per month by 2015.78 Underlying this capacity and traffic growth are the rapid improvements in computational through surveys, While it is nearly impossible to quantify Internet volume as power, storage, and bandwidth that enable richer and discussions, and a whole, the rate of traffic growth on the major intercity more robust Web content. interviews with network routes in the United States provides a reasonable proxy engineering and for the country’s Internet traffic patterns. By studying this Not surprisingly, we found a high correlation between the planning staff of major trend over time, we can see the quantity of data being growth in Internet volume and the growth in the use of Internet backbone transmitted via the Internet and attempt to interpret the connectivity platforms, such as the Internet and wireless providers. effects on knowledge flows. devices. The widespread adoption of the technological Internet Activity 1 infrastructure that will drive Internet Activity is evident in The metric is a proxy for connectivity and knowledge flows. Updated Exhibit 56: Forecasted Growth in Internet Activity (U.S.), (1990-2010) Exhibit 56: Forecasted Growth in Internet Activity (U.S.) (2010-2015)

25,000 22,274

20,000

15,000

PetaByte/month 10,000 6,998 (PetaByte = 1,000 terabytes)

5,000

0 2010 2011 2012 2013 2014 2015

Average Internet Activity Source: Cisco Visual Networking Index

78 Cisco Visual Networking Index 2011 Source: Cisco Visual Networking Index

Updated Tab Title Here Tab 2011 Flow Index Exhibit 57: Total Online Music Spend ($, Millions), (2008 – 2010) Exhibit 57: Total Online Music Spend ($, Millions) (2008-2010)

7,000

5,888 6,000 5,376

5,000 4,736

4,000

3,000

2,000

Total Online Music SpendMillions) ($, 1,000

- 2008 2009 2010 Total Online Music Spend ($, Millions) Source: Gartner, Forecast: Online Music, Worldwide, 2008 — 2015

Source: Gartner, Forecast: Online Music, Worldwide, 2008 – 2015

the penetration levels: 68% for Internet Users and 90% for annually on online music grew from $4.7 billion in 2008 to Wireless Subscriptions as of 2010.79 $5.8 billion in 2010, an 11% CAGR.81

This trend is expected to continue, bolstered by The amount of video content being transmitted over the technological advances that make the Internet more Internet also continues to grow. Recent research indicates accessible. In the past year, the number of mobile Internet that U.S. consumers watch an average of 2.45 hours users increased 28%.80 No longer confined to desk or per week of over-the-top video content over broadband home, users armed with cell phones and wireless access connections (using providers, such as Netflix and Hulu).82 are now able to remotely access video, Web content, According to digital analytics provider comScore, more images, music, and other forms of information in virtually than 80% of the U.S. Internet audience watched videos 57 © 2011 Deloitte Touche Tohmatsu any location. A single laptop can generate as much data online during any given month ( 84.6% in December volume as 450 basic-feature phones (voice and SMS); 2010). a high-end handset, such as an iPhone or Blackberry, creates as much traffic as 30 basic-feature phones. These The number of content providers is also increasing, further newer-generation devices offer consumer content and spurring Internet activity. These professional sites offer applications which account for much of the richness and original content to subscribers through news, product volume of mobile internet traffic. information, blogs, reviews, games, and entertainment. With content providers vying for viewers, new players are Internet Activity is also being driven by growth in online popping up in the delivery space, where content delivery music exchanges. New business models for the sale and networks (CDNs) seek more efficient ways to deliver video sharing of music online, such as Apple’s iTunes and internet and other forms of content to end users. Advances in the radio operator, Pandora, have enabled strong growth. CDN infrastructure and business model are supporting the

As shown in Exhibit 57, the amount consumers spend increased demand for professional content. 79 For further information, please refer to the Internet Users and Wireless Subscriptions metrics. 80 ComScore, Deloitte Analysis 81 Gartner, Forecast: Online Music, Worldwide (2008 — 2015) 82 “Market Trends: Over-The-Top Video, Worldwide, 2011”, Gartner 2011 Shift Index Measuring the forces of long-term change 83 2011 Flow Index

Electronic networks and geographic spikes (concentrations Some 90% of the cities having the highest Internet volume of talent in dense urban areas) reinforce each other, were also creative cities, indicating the remarkable role helping to integrate physical and virtual connections. Our of geography in the growth of information sharing and analysis of migration to “creative cities” (as identified by Internet volume. Dr. Richard Florida) has shown large disparities between population growth in the 10 most- and the 10 least- Online communities are also flourishing. Social media creative cities in the United States.83 What is striking, but dominates this category and social networking leaders perhaps not surprising, is the high correlation between continue to gain new members. In 2010, 22% of total time Internet volume and the distinction of being a creative city. spent online globally was associated with social media and

e-Patient Dave and the Participatory Medicine Movement

n January 2007, during a routine shoulder x-ray, Dave deBronkart discovered that he had Stage IV kidney cancer. With a grim prognosis for survival, Dave turned to the Internet for information and support to supplement his treatment at Beth Israel Medical Center in Boston. IDave embarked on a variety of efforts, including participating in an expert online patient community through the Association of Cancer Online Resources (ACOR), starting an online journal and support community on the social networking site, Caring Bridge, and sharing his hospital medical records with medically knowledgeable friends and family. “It goes without saying that there’s immense value to discovering that you’re not alone. Immense value,” says Dave. “In my case, I was already at the best place in the world for my disease, and they were already planning to give me the treatment that the ACOR members recommended. However, what my doctors couldn’t give me was information on how to deal with the treatment, which is very difficult. ... There is no Web site, FDA-approved or anything, that will tell you that. But the people who have been down that road all know what they encountered, and they shared that with me.”84 Complementing his treatment regime with a wealth of online resources and support, Dave was deemed cancer-free in 2009. Today, Dave is a spokesperson for the participatory medicine movement, which advocates for the active role of patients as responsible drivers of their health.

Dave’s journey illustrates how widespread growth in Internet activity is changing multiple facets of health care. The proliferation of expert-run doctor and patient communities (e.g., WebMD and ACOR) reflects the tremendous demand for information for medical diagnosis, treatment options, and support. There is also growing Internet activity around research, marketing, and treatment. For example, the Mayo Clinic recently used Twitter to solicit feedback on its research into celiac disease. In marketing, Palomar Pomerado Health in California has partnered with Cisco and virtual world operator, Second Life, to give prospective patients virtual tours of its newest health care facility. In treatment, the emergence of fields like e-therapy (online provision of mental health services) demonstrates how greater accessibility and richness of content is allowing the Internet to become a channel for 83 For further information, please the delivery of medical services. refer to the Migration of People to Creative Cities metric. 84 http://www.inspire.com/John2/ journal/the-inspire-q-and-a-inspire- talks-with-e-patient-dave-debronkart/For further information, please refer to the Migration of People to Creative Cities metric.

84 Tab Title Here Tab 2011 Flow Index

social networks had reached 72% of all active users in the at the right time for the right purposes will be one of the United States.85 Facebook, Twitter, and LinkedIn claimed great challenges in the Big Shift—both for individuals and 500-,86 100-,87 and 60-million users, respectively, and institutions. social network advertising exceeded $1.5 billion in 2010. This explosive growth has continued into 2011.88 These platforms offer new ways for businesses to participate in, and create, social networks on the Internet. Emerging Some 90% of the cities having the highest Internet practices, such as open source software, that leverage the Internet through networks, communities, and other volume were also creative cities, indicating the connectivity platforms hold great promise for companies.89 remarkable role of geography in the growth of With the growth in Internet Activity, filtering the signal information sharing and Internet volume. from the noise becomes even more difficult. Society’s information overload should only increase, for better and for worse, as more and more data is exchanged virtually. The capability to filter and amass the right information

85 Nielsen, http://blog.nielsen.com/ nielsenwire/online_mobile/social- media-accounts-for-22-percent-of- time-online 86 Facebook, http://www.facebook. com/press/info.php?statistics#!/ press/info.php?timeline 87 TechCruch, http://techcrunch. com/2010/04/14/twitter-has- 105779710-registered-users- adding-300k-a-day/ 88 TechCrunch, http://techcrunch.com/2010/02/11/ linkedin-now-60-million-strong/ 89 John Hagel III and John Seely Brown, "Creation Nets: Harnessing the Potential of Open Innovation," Journal of Service Science 1, no. 2 (2008): 27-40. 2011 Shift Index Measuring the forces of long-term change 85 2011 Flow Index Migration of People to Creative Cities

Increasing migration suggests virtual connection is not enough — people continue to seek rich and serendipitous face-to-face encounters as well

Introduction to make serendipitous connections with people from outside The Migration of When it comes to creating flows of new, tacit knowledge, their own firm. As creative talent congregates, innovation People to Creative face-to-face interactions are by far the most valuable. and economic growth can be expected to ensue. Cities metric measures Yet these interactions and the knowledge flows they can the increase in generate are difficult to measure directly and we must turn In designating cities as “creative,” Richard Florida assigns population in cities instead to proxies. each U.S. region92 a score based on the region’s technology, ranked “most creative” talent, and tolerance. Cities with a high creative index score as compared to the One of these is the growth in population, as provided by the have high concentrations of creative class workers (talent), increase in population U.S. Census Bureau, within the “creative cities” defined by high concentrations of high-tech companies, and innovative in cities ranked “least Richard Florida.90 As a greater number of creative individuals activity (technology) and are demographically diverse creative.” (including professions, such as computer engineers, health (tolerance). We extend Florida’s work by tracking migration care professionals, and architects)91 gather in one place, patterns across “creative cities” and the rate at which the The metric serves as one can reasonably assume that they will likely have a population gap between the 10-most and 10-least creative a proxy for the ability greater number of face-to-face interactions with each cities (cities are identified in Exhibit 58) widens.93 of people to access other — and more new knowledge will likely be created. Migration 1 knowledge flows more Cities that attract creative talent are rich spawning grounds We see this metric as a proxy for the level of tacit effectively and intimately for knowledge flows, especially across firms. As people knowledge, geographic spikiness, and mobility to areas most where they live. congregate in these creative epicenters, they are more likely likely to have rich knowledge flows. As the migration of UPDATED (No change

Exhibit 58: Top 10 Creative Cities and Bottom 10 Creative Cities, (2004) since 2009 report) Exhibit 58: Top 10 Creative Cities and Bottom 10 Creative Cities (2004)

Creative Cities / Creativity Overall (all Technology Talent Tolerance Rank Regions Index regions rank) Rank Rank Rank 1 Austin 0.963 1 2 9 22 2 San Francisco 0.958 2 6 12 20 3 Seattle 0.955 3 21 15 3 4 Boston 0.934 5 35 11 12 5 Raleigh-Durham 0.932 6 5 2 52 6 Portland 0.926 7 12 45 7 7 Minneapolis 0.900 10 47 22 17 8 Washington -Baltimore 0.897 11 41 1 45 9 Sacramento 0.895 13 15 27 47 10 Denver 0.876 14 61 18 25

90 Richard Florida, The Rise of the 40 Norfolk 0.557 113 130 90 149 Creative Class (New York: Basic Books, 2004). 41 Cleveland 0.550 118 139 95 139 91 Ibid. 42 Milwaukee 0.539 124 155 108 120 92 Metropolitan Statistical Areas (MSA) and Consolidated 43 Grand Rapids 0.525 131 102 206 86 Metropolitan Statistical Areas (CMSA) as defined by the U.S. 44 Memphis 0.524 132 78 135 183 Census: Robert Bernstein, 45 Jacksonville 0.498 143 224 107 88 “Statistical Brief,” Bureau of the Census, http://www.census.gov/ 46 Greensboro 0.492 145 148 159 113 apsd/www/statbrief/sb94_9.pdf 47 New Orleans 0.490 147 211 99 113 (created May 1, 2009). 93 The list of creative cities was pulled 48 Buffalo 0.483 150 148 104 175 from Florida’s The Rise of the 49 Louisville 0.409 171 189 160 143 Creative Class Source: Richard Florida, “The Rise of the Creative Class” 86 Source: Richard Florida, “The Rise of the Creative Class”

people to creative cities relative to other cities maintains an the population growth of the top 10 creative cities (with Title Here Tab 2011 Flow Index upward trend, society can be perceived to be more “spiky” population greater than one million) against the bottom and more likely to engage in tacit knowledge creation and 10. The top 10 cities show an upward trend in population exchange—at least in creative areas of the country. growth (see Exhibit 59) and an increasing gap relative to the bottom 10.94 Migration 2 Observations and Implications Increasing returns appear to be at work here—cities that On average, the population growth of the top 10 creative have higher concentrations of creative talent are growing cities has outpaced growth in the bottom 10 since 1990. By faster than those with lower concentrations. Consider 2009, the growth gap between the two comparative sets Updated Exhibit 59: Migration to Creative Cities growth and gap, (1990-2009) Exhibit 59: Migration to Creative Cities growth and gap (1990-2009)

50%

45%

40%

35% 25% 30% from 1990 25%

20% 14% 15%

Percentage growth 10%

5% Migration 3

0% 1990 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

Top Ten Creative Cities Growth from 1990 Bottom Ten Creative Cities Growth from 1990 Source: US Census Bureau, Richard Florida's "The Rise of the Creative Class", Deloitte analysis Updated Source:Exhibit US 60: Census Correlation Bureau, Richard between Florida's Migration "The Rise of of the People Creative Class",to Creative Deloitte analysisCities and Economic Freedom, (1993-2009) Exhibit 60: Correlation between Migration of People to Creative Cities and Economic Freedom (1993-2009)

82.0 25%

Correlation: 0.92 80.0 20%

78.0

15%

5% 72.0 Gap in percentage growth between top ten and

0% 70.0 94 Deloitte analysis based on “Creative 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 Cities” from Richard Florida’s The Rise of the Creative Class and population data from the U.S. Index of Economic Freedom Migration of People to Creative Cities Census Bureau. Source: US Census Bureau, Heritage Foundation, Richard Florida's "The Rise of the Creative Class“, Deloitte analysis 2011 Shift Index Measuring the forces of long-term change 87 Source: US Census Bureau, Heritage Foundation, Richard Florida's "The Rise of the Creative Class“, Deloitte analysis

4 © 2011 Deloitte Touche Tohmatsu had increased to an absolute 25% (from 14% in 2000). In groups, increases in economic freedom make it easier 2011 Flow Index other words, the growth of the top 10 creative cities has for people from around the world to travel and gather in been more sustained than that of the bottom 10. Between geographic “spikes.” These spikes represent concentrations 1990 and 2009, the top 10 cities grew by 45%, whereas of talent in dense geographic settlements, like Silicon the bottom 10 grew by only 20%. The absolute number Valley and Boston (see Exhibit 60). The share of the world’s of people is also telling: 38 million people live in the top population living in urban areas has grown from 30% in creative cities, approximately 12% of the U.S. population, 1950 to about 50% today. As we have seen, much of this as compared with the 15 million, 5% of the U.S. population growth is into the cities and regions that drive the world’s living in the bottom 10 creative cities. economy, causing them to grow much more rapidly than Migration 4 less creative cities. At a time when the world is increasingly Although Big Shift forces are significantly driven by flat, the world is also paradoxically becoming increasingly technological advances, not all of the connections are spiky.95 virtual. While the internet helps to connect people in virtual These spikes are becoming more important as individuals Updated Exhibit 61: Correlation between Migration of People to Creative Cities and GDP, (1993-2009) Exhibit 61: Correlation between Migration of People to Creative Cities and GDP (1993-2009)

30% $14,000

25% Correlation: 0.99 $12,000

$10,000 20%

$8,000 15%

$6,000

10% Billions) ($, GDP, (U.S.

bottom ten Creative Cities $4,000

5% $2,000 Gap in percentage growth between top ten and Migration 5 0% $0 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

GDP Migration of People to Creative Cities Source: US Census Bureau, Bureau of Economic Analysis, Deloitte analysis Source: US Census Bureau, Bureau of Economic Analysis, Deloitte analysis Updated Exhibit 62: Correlation between Migration of People to Creative Cities and Returns to Talent, (1993-2009) Exhibit 62: Correlation between Migration of People to Creative Cities and Returns to Talent (1993-2009)

25% $70,000

$60,000 Correlation: 0.99 20%

$50,000

15% $40,000

Gap in percentage growth between top ten and $10,000

0% $0 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

Returns to Talent Migration of People to Creative Cities

Source: US Census Bureau, Bureau of Labor Statistics, Richard Florida's "The Rise of the Creative Class“, Deloitte analysis

95 Richard Florida, “The World is Spiky,” The Atlantic Monthly, October 2005: 48-51. Source: US Census Bureau, Bureau of Labor Statistics, Richard Florida's "The Rise of the Creative Class“, Deloitte analysis

6 © 2011 Deloitte Touche Tohmatsu Fort Collins, CO: Burgeoning Epicenter of Clean Technology n the developed world, technological advances that save and improve lives are evident everywhere: Hereditary propensities can be uncovered with a personal genome mapping, artificial heart transplants are viable, major surgeries can be performed noninvasively. ButI in the developing world, perils like indoor air pollution, which takes the lives of an estimated 2 million people each year, have gone largely unaddressed. That is the challenge that Nathan Lorenz and Tim Bauer set out to solve in 2003 when they Title Here Tab 2011 Flow Index founded EnviroFit, which develops clean-burning cookstoves and other technologies that are intended to reduce pollution and promote energy efficiency.

Lorenz and Bauer, who were named “Heros of the Environment” in 2009 by Time Magazine, met as students in Colorado State University’s Engines and Energy Conservation Laboratory during the SAE Clean Snowmobile Challenge, a contest to create an energy-efficient snowmobile. EnviroFit, which is based in Fort Collins, Colorado, is one of many new companies and incubators, made possible by the rich ecosystem of clean energy talent and resources.

The non-profit Colorado Clean Energy Cluster was founded in 2006 to bring together academics, corporate innovators, and the public sector in order to develop Northern Colorado into an internationally recognized center for clean energy initiatives and projects. From 2006 to 2009, employment in clean energy companies in the Cluster grew 31% despite a 9% contraction nationally.96

As companies are drawn by the physical proximity that allows for joint R&D efforts and resources, so is the creative talent. People are increasingly moving to creative cities where they can engage in the rich face-to-face interactions. EnviroFit and the other companies of the region will continue to draw people to the clean energy spike city of Fort Collins.

and companies face more pressure to develop talent. Spikes of creative talent likely contributed to the recent growth in are seen to offer more opportunities for talent development. GDP and played a role in productivity increases. The flip side is that individuals seek out spikes out of fear, driven to congregate, or risk being marginalized. There is a simple but powerful reason that, in the past two decades, talented people have moved to creative cities at The spike phenomenon is expected to become stronger as an increasingly higher rate. They are migrating because they connectivity improves. Connectivity enables specialization likely believe they can learn faster and better there.97 And within a spike and coordination of activities across with interfirm knowledge flows98 becoming increasingly spikes. For example, Silicon Valley was able to specialize vital to economic value creation, talented workers are going in technology innovation and commercialization, while where these flows are most likely to occur. moving manufacturing activities to other spikes. At the same time, China has developed a series of spikes specializing The same self-reinforcing dynamic may hold true for in manufacturing for technology companies. Serendipity talented workers who “migrate” to companies that within spikes is enhanced by wireless technology that more have high concentrations of creative talent. Like cities, effectively integrates physical and virtual presence. companies that do not attract top talent now will find it 96 Colorado Clean Energy Cluster. ever harder to do so in the future. Innovation today requires “Attacting, incubating and Our analysis found a high correlation between the growth extensive pooling of knowledge and other resources and growing Colorado’s clean energy companies.”www.colorado- of creative cities and the growth of GDP, suggesting that as is accelerated by tacit knowledge gained through face- cleanenergy.com. Accessed Aug 11, 2011. the population found in creative cities grows, there may be to-face interactions. Despite the tremendous increase in 97 We acknowledge that this is not a significant positive impact on economic value creation (see virtual flows, companies still need physical proximity to the the only factor to creative city growth — creative cities also tend Exhibit 61). talent and resources that are required for extreme growth. to be pleasant places, and creative people may just like hanging out By better understanding the disproportionate growth in with other “creative people” or The population flow to creative cities also correlates strongly creative cities, business leaders can mimic the practices that may be seeking a different way of life. with the Returns to Talent metric in the Impact Index. This attract talent in their own organizations. Practices, such as 98 For further information, please refer to the Inter-Firm Knowledge suggests that the types of talent that make up the workforce recognizing and tapping into creative talent, making the best Flows metric. in creative cities are valued higher and higher as they use of technology and striving for innovation and diversity 99 Cathy Benko and Anne Weisberg, Mass Career Customization become more concentrated in these creative epicenters (see have helped cities become creative epicenters and can be (Boston: Harvard Business School Publishing, 2007). Exhibit 62) and interact more and more within and across applied at the institutional level. Similar approaches — 100 For more information about the spikes. such as pull platforms and mass career customization strategic, organizational, and operational changes needed to attract 99 practices — will help companies adapt to the exigencies of and develop talented workers, see 100 John Hagel III, John Seely Brown, As labor freedom and economic freedom increase, people the Big Shift. and Lang Davison, “Talent is appear to have a propensity to migrate to creative cities, Everything,” The Conference Board Review, May-June 2009, http:// leading to higher concentrations of talent. These epicenters www.tcbreview.com/talent-is- everything.php. 2011 Shift Index Measuring the forces of long-term change 89 2011 Flow Index Travel Volume

Travel Volume continues to rise as virtual connectivity supplements, but does not replace in person interactions

Introduction interested in the longer-term trends in Travel Volume and The Travel Volume Steady advances in technology and physical infrastructure what these trends may indicate about knowledge flows. metric measures the during the last 20 years have increased both the reach and volume of passenger accessibility of travel.101 U.S. residents are travelling more Observations and Implications travel based on the and more each year, despite temporary declines related Travel Volume has shown a strong upward trend since monthly output of to the recent financial downturn. Not all interactions are 1990 (the year TSI was introduced). Exhibit 63 shows for-hire passenger equal. Some are more likely to result in the creation of passenger travel volume indexed off of the year 2000 transportation services. new knowledge rather than in simple knowledge transfer. (index value of 100); over the past two decades, Travel Face-to-face interactions, in particular, tend to drive the Volume has increased 57%, from a value of 71 in 1990 to The metric serves as a most valuable knowledge flows. As the movement of 111 in 2010. proxy for physical flows people increases, so do the opportunities for rich and of people and indicates serendipitous connections between them, connections that Although TSI growth has trended strongly upward, notable levels of face-to-face are vital for knowledge flows to take place. troughs have occurred:103 interactions, which are • In 2001, 9/11 and reverberations of the dot-com crash more likely to drive While we cannot measure these flows directly, metrics, caused the TSI to drop over 23% in one month. It did the most valuable such as Travel Volume, as measured by the passenger not rebound to pre-9/11 levels until June 2004, nearly knowledge flows. Transportation Services Index (TSI), provide suggestive three years later. proxies. Changes in Travel Volume over time can help • In 2003, overproduction, billions of dollars invested in to illuminate the relationship between transportation expansion, and too much debt contributed to lagging and other long-term changes in the economy. In fact, airline financial health and a reduced number of flights, in 2004, the U.S. Transportation Secretary Norman causing a decrease in revenue passenger miles. Travel Volume 1 Mineta announced the TSI as a new economic indicator, • The downturn in the economy in 2009 led to reduction using changes in passenger activity as a measure of in both personal and professional travel. Travel Volume macroeconomic performance.102 While movements in the has already begun to increase to its previous trajectory as TSI reflect economic and political pressures, we are mostly the economy recovers. Updated Exhibit 63: Transportation Services Index – Passenger, (1990-2010) Exhibit 63: Transportation Services Index-Passenger (1990-2010)

130

120 116.8

110.7 110

101 "Domestic Research: Travel Volume and Trends," U.S. Travel 100 Association, http://www.tia.org/ (2000=100) Travel/tvt.asp (created May 8, 2009). 90 102 "Remarks for the Honorable

Norman Mineta Secretary of type Index Transportation," U.S. Department of Transportation Office of Public 80 Affairs, http://www.dot.gov/affairs/ Chain - minetasp012904.htm (created May 70.6 15, 2009). 70 103 Peg Young et al., "The 68.6 Transportation Services Index Shows Monthly Change in Freight and Passenger Transportation 60 Services," Bureau of Transportation 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Statistics Technical Report, September 2007: 1-4.

90 Source: US Census Bureau, Bureau of Labor Statistics, Richard Florida's "The Rise of the Creative Class“, Deloitte analysis Source: Bureau of Transportation Statistics (BTS), the statistical agency of the U.S. Department of Transportation (DOT), Deloitte analysis

Increases in Travel Volume have been shown to be correlated with growth in GDP.104 While there is likely no City Centers Take Flight causality between the two, people’s movement on land and in air is strongly interrelated with economic expansions hroughout history, the development of cities has been and contractions. Secretary Norman Mineta noted, “A closely intertwined with trade and transportation. From transportation system that keeps the business of America the ports of Boston to the railroads stretching West, moving is vital to the strength of our Nation’s economy” and, metropolitan hubs are often dictated by the inflow and we argue, equally fundamental to Big Shift forces. Toutflow of goods, ideas, and people. In the 21st century, a new urban form has emerged: the Aerotropolis. This term, coined by John Kasarda, Indeed, there appears to be a strong positive correlation director of the Kenan Institute of Private Enterprise at the University between travel activity and broader labor productivity. One of North Carolina, refers to the pattern of development expanding plausible explanation is that people benefit from face-to-face outward from a central airport hub and reflects the increasing ubiquity physical interactions facilitated by travel and as a result are of travel and the growing importance of air routes for economic able to be more productive in their jobs. development. Airport regions, such as Kuala Lampur, Hong Kong, and Dubai, are all examples of the Aerotropolis model, with carefully Somewhat paradoxically, the growth in digital technology designed airports serving as the heartbeat and source of growth for the infrastructure is actually positively related to growth surrounding areas. in travel.105 While we might have predicted an inverse relationship, physical travel should decrease as the ability to America has lagged Europe and Asia in adopting Aerotroplis connect virtually increases, travel volume is, in fact, positively development and many U.S. airports still sit on the peripheries of cities. correlated with Internet users, Wireless Subscriptions, Memphis is America’s purest Aerotropolis (as the hub of FedEx and a wireless minutes, SMS volume and Internet volume. It major passenger airline hub, the airport pumps more than $28 billion is plausible that the frequency and ubiquity of virtual into the region’s economy and airport-related jobs employ one in every communication actually increases the propensity to travel by three residents), but other cities, such as Las Colinas, Texas, the airport creating more reasons to connect with people physically. In hub between Dallas and Fort Worth, have also emerged as burgeoning this regard, the virtual world actually scales the number of Aerotropolis regions. face-to-face interactions that one can engage in, an example of one type of knowledge flow leading to another. The move towards airport-centric development is expected to pick up substantially as physical flows of cargo and people become increasingly Travel will likely remain the primary mode for increasing crucial to economic development. China, for example, added the face-to-face interactions. Business leaders should consider equivalent of Great Britain’s air traffic during the past decade, and the trade-offs when cutting back on travel during economic according to Kasarda, “they have not yet begun to fly.” With much of downturns or thinking of technology as a substitute rather this travel coming into and out of the United States, airports and the than as a complement. Travel is not only an indicator of surrounding cities, must be developed to support the flow of people, macroeconomic factors at work, but also remains deeply things, and ideas. The emergence of the Aerotropolis underscores the intertwined with the evolving digital infrastructure. importance of air travel as a means of growth; despite the proliferation of digital infrastructure, travel still constitutes a primary form of physical and knowledge flows.

104 Peg Young et al., “The Transportation Services Index Shows Monthly Change in Freight and Passenger Transportation Services,” Bureau of Transportation Statistics Technical Report, September 2007: 1-4. 105 Correlation analysis detailed in the Shift Index Methodology section 2011 Shift Index Measuring the forces of long-term change 91 Tab2011 Flow Index Here Title Movement of Capital

Cross-border capital flows provide an efficient way to access pockets of global talent and innovation

Introduction that force companies to seek efficiency and innovation The Movement of The flow of capital across geographic and institutional outside of their home country. Capital metric measures boundaries is an important, albeit indirect, indicator of the total volume of the forces of long-term change. These capital flows can Observations and Implications FDIs into and out of the be understood as a form of arbitrage in which knowledge Between 1970 and 1999, U.S. FDI flows steadily increased, United States, without moves, via conduits created by investment, from one tracking GDP (see Exhibit 64). From 2001 to 2003, FDI netting the two, to focus country—and company—to another. flows decreased as a result of the economic downturn and on volume rather than the aftermath of the 9/11 terrorist attacks; investors faced direction of flow. Companies in emerging economies, for example, take greater uncertainty and U.S. policymakers began viewing stakes in (or buy outright) companies in developed foreign investments as a risk to national security. This metric is a proxy for countries in order to access knowledge and expertise capital flows between among other reasons (e.g., brand equity). Companies from In 2004, the United States regained its status as the world’s the countries at the core developed countries, on the other hand, have traditionally principal destination for direct investments, a position it and countries at the invested in emerging market companies to acquire local held for most of the last two decades (see Exhibit 64). As edge. knowledge, such as the most efficient distribution channels a provider of FDI, the United States also showed a sharp in local markets. Thus, capital flows enable some of the increase, although in 2005 U.S. parent companies acted to knowledge flows that drive economic value creation. take advantage of a one-time tax provision, resulting in a drop in FDI.106 Although FDI measures both flows of capital (e.g., equity investments and intracompany loans) and stocks of capital The upward trend that began in 2004 peaked in 2007, Movement of (e.g., reinvested capital and retained earnings), the Shift with the financial crisis of 2008 ending FDI growth. Index considers only capital flows. The total flow represents According to the United Nations Conference on Trade Capital 1 the movement of capital between countries triggered by and Development (UNCTAD), flows to the United States, both public policy liberalization and competitive pressures the largest host country in the world, declined by 60% Updated Exhibit 64: Foreign direct investment flows ($, Billions), (1970-2010) Exhibit 64: Foreign direct investment flows (1970-2010)

$700 $16,000

$600 $14,000

$12,000 $500

$10,000 $400 $8,000 $300 $6,000 U.S. GDP U.S. GDP ($, Billions) $200 $4,000

Total FDI Inflows and Outflows ($, Billions) $100 $2,000

106 James J. Jackson, “Foreign Direct $0 $0 Investment: Current Issues” (report 1970 1974 1978 1982 1986 1990 1994 1998 2002 2006 2010 to Congress, Congressional Record Services, Washington, DC, April 27, 2007). Total FDI Inflows and Outflows, Current Dollars GDP Source: UNCTAD, Deloitte analysis 92 Source: UNCTAD, Deloitte analysis

Movement Title Here Tab 2011 Foundation Flow Index Index of Capital 2

Updated Exhibit 65: Movement of Capital ($, Billions), (1970-2010) Exhibit 65: Movement of Capital (1970-2010)

$700

$600

$500

$400

$300

$200

$100 Movement of Total FDI Inflows and Outflows ($, Billions) Capital 3 $0 1970 1973 1976 1979 1982 1985 1988 1991 1994 1997 2000 2003 2006 2009

Total FDI Inflows and Outflows, Current Dollars Linear (Total FDI Inflows and Outflows, Current Dollars) Source: UNCTAD, Deloitte analysis Updated Source: UNCTAD, Deloitte analysis Exhibit 66: U.S. Capital inflows and outflows ($, Billions), (1970-2010) Exhibit 66: U.S. Capital inflows and outflows (1970-2010)

$450

$400

$350 $282.7 $300

$250 $228.2

$100 FDI Inflows and Outflows ($, Billions)

$50

$0 1970 1973 1976 1979 1982 1985 1988 1991 1994 1997 2000 2003 2006 2009

Flow Inward (Million USD; current) Flow Outward (Million USD; current) Source: UNCTAD, Deloitte analysis

Source: UNCTAD, Deloitte analysis

2011 Shift Index Measuring the forces of long-term change 93

New Jungles to Explore: Tata Buys Jaguar and Land Rover few years ago, Indian car company Tata was most recognized in the United States for its heavy trucks and introducing the world’s cheapest car. But despite this reputation, Tata had ambitions of expanding into a global luxury brand. And to do this, it needed to enter the extremely competitive U.S. market, which already supported a legion of domestic and imported brands. Undeterred, Tata purchased the luxury car brands Jaguar and Land RoverA from Ford Motor Company in 2008. Tata Motors’ Vice-Chairman Ravi Kant had previously stated, “The only way that I can enter the U.S. market is through mergers and acquisitions. So if I get an opportunity, then I will look at it very actively.”107 The decision to acquire Jaguar and Land Rover was a strategic move to expand Tata’s product portfolio and geographic presence, making Tata a global player in the automotive industry. It was easier for Tata Motors to buy Jaguar and Land Rover for their new technology, advanced market distribution channels and brand equity than for Tata to develop them on its own.

Caught in the slumping global automotive industry, Tata initially sustained huge losses. However, by reducing costs, improving efficiencies and managing cash flow, Tata Motors turned around the ailing companies. As the market began to rebound in 2009, so did the fortunes of Jaguar and Land Rover. In a remarkable recovery, Jaguar and Land Rover posted a $1.7 billion net profit in 2010, a huge win for Tata and its international portfolio.

in 2009.108 The decline was driven by a marked decrease of innovation across the globe. Innovation, whether in 107 Tarun Khanna et al., House of Tata: in cross-border mergers and acquisitions; mergers and product or process or management practice, is no longer Acquiring a Global Footprint (June 112 30, 2009), http://www.drclas. acquisitions picked up again in 2010. confined to developed economies. harvard.edu/files/House-of-Tata- English.pdf 108 UNCTAD, “FDI recovery in Economists argue that relative rates of growth between The level of R&D being performed for U.S. multinationals developed countries, after two-year decline, rests with the rise of economies are indicative of relative rates of returns and by overseas affiliates has been relatively flat, however, the cross-border M&A’s”< http://www. corporate profitability; thus, growth rates are a key factor regional distribution of that R&D is changing (see Exhibit unctad.org/templates/webflyer.asp? docid=13647&intItemID=1528& in the direction and magnitude of capital flows. Public 67 and 68). In 1994, an overwhelming 73% of foreign lang=1>, (created July 2010). 109 “Foreign investors view the ease policy, including relative tax rates, interest rates, inflation, affiliate R&D was performed in Europe. By 2006, Europe’s with which they can travel to the and any protectionist policies (e.g., business visas), have share decreased to 65%. At the same time, the share being United States as a key indicator of how easy it will be to make or a direct impact on FDI levels.109 Investors’ expectations performed by the Asia-Pacific region increased from 5 to administrate investment.” Visas and Foreign Direct Investment: about the performance of national economies also drive 13% and that of the Middle East increased from 1 to 3%. Supporting US Competitiveness investment trends. All these factors can be quite volatile, By placing their R&D centers in emerging markets, U.S. by Facilitating International Travel, US Department of Commerce, thus the volatility of investment trends (see Exhibit 65).110 firms are able to tap into diverse pockets of talent. http://www.commerce.gov/s/ groups/public/@doc/@os/@ Looking past this cyclical FDI volatility, the long-term opa/documents/content/ trajectory of FDI levels shows a strong upward trend over Today, developing countries in the Asia-Pacific region prod01_004714.pdf (created November 2007). time. are growing at a faster rate than developed countries 110 James K. Jackson, “Foreign Direct Investment: Effect of a ‘Cheap’ in North America and Europe and are emerging sources Dollar” (report to Congress, As U.S. FDI continues to grow, the question is for what of management talent and innovation. For example, Congressional Record Services, Washington, DC, October 24, purpose? Historically, FDI was a way to improve efficiency, both the Chinese motorcycle industry in Chongqing and 2007). 111 Vivek Agrawal, Diana Farrell, and to take advantage of opportunities for resource and labor the Hong Kong-based apparel company Li & Fung have Jaana K. Remes,”Offshoring and arbitrage, and to access local markets which often favor demonstrated the process and management practices Beyond,” The McKinsey Quarterly, 2003 special edition: Global direc- local manufacturers.111 Although most U.S. companies referred to as “process networks.” Process networks use tions: 24-35. 112 For more information about still use foreign affiliates to achieve short-term efficiency a loosely coupled, modular approach to organizing the emerging market management improvements, firms are increasingly taking a longer- activities in extended business processes that speeds time- innovation, see John Hagel III and John Seely, “Innovation term approach, using FDI to identify and develop centers to-market, cuts costs, and enhances product quality. Li & Blowback: Disruptive Management Practices from Asia,” The McKinsey Quarterly, 2005, no. 1: 35-45.

94 Movement of Capital 4

Updated Regional share of R&D performed by foreign affiliates of U.S. multinationals ExhibitExhibit 67: 67: Year Regional 1994 share of R&D performedExhibit by 68: YearExhibit 2006 68: Regional share of R&D performed by

foreign affiliates of U.S. multinationals (1994) foreign affiliates of U.S. multinationals (2006) Title Here Tab 2011 Foundation Flow Index Index

4.0% 0.8% 0.1% 3.0% 0.3% 3.2% 5.4%

13.0% 9.5%

6.3% 7.0%

9.0%

65.4%

73.0%

Europe Canada Japan Asia/ Pacific excluding Japan Latin America/ OWH Middle East Africa Source: Bureau of Economic Analysis, Survey of U.S. Direct Investment Abroad (annual series), Deloitte analysis Source: Bureau of Economic Analysis, Survey of U.S. Direct Investment Abroad (annual series), Deloitte analysis

Fung deploys a network of 515,000 specialized business Innovation, whether in product or process or partners to create a customized supply chain for each new item of apparel. The ability to build scalable networks management practice, is no longer confined to of diverse partners forms the core of this management innovation, enabling Li & Fung to participate in rich developed economies. knowledge flows that drive performance improvement. With this network, Li & Fung built a company of $16 billion in revenue while enjoying double digit revenue growth and Today, developing countries in the Asia-Pacific region 67 113 © 2011 Deloitte Touche Tohmatsu high profitability. are growing at a faster rate than developed countries While developing countries offer many reasons to invest, in North America and Europe, and are emerging U.S. companies cannot afford to overlook the bigger opportunity to learn new institutional architectures, sources of management talent and innovation. governance structures, and operational practices from foreign affiliates and partners in the developing world. Managing and scaling a flexible network of diverse partners without running into overhead complexity is just one example. At the same time, as emerging markets rebound from the global recession more quickly than the United States and Europe, powerful emerging market companies are increasingly acquiring companies in developed economies. This trend of reverse FDI offers a conduit for emerging market companies to access western expertise and expand globally.

113 Li & Fung. http://www.lifunggroup. com/eng/global/glance.php 2011 Shift Index Measuring the forces of long-term change 95 2011 Flow Index Worker Passion

Passionate workers are more likely to participate in knowledge flows and generate value for companies

What exactly is worker passion? Passion is not commonly capabilities. The effort required to increase our rate of The Worker Passion associated with work—HR departments often try to measure professional development is difficult to muster unless we are metric measures how “employee satisfaction,” which is an entirely different thing. passionately engaged with our professional activities. passionate U.S. workers Passion is when a person discovers work that they love and are about their jobs. when that work becomes more than just a mode of income. We must also consider differing generational viewpoints This metric is based on A passionate worker is fully engaged in his or her work and aspirations regarding the meaning of work. The Intuit a survey in which we and interactions and constantly strives to get to new levels Small Business Report (2008) notes rapid changes in the tested different attitudes of performance. Satisfaction, meanwhile, describes how demographics of small business ownership and postulates and behavior around content an individual is with a job. A satisfied worker can that, “entrepreneurs will no longer come predominantly worker passion— be content with a job, perhaps because it fulfills a worker’s from the middle of the age spectrum, but instead from excitement about work, income, location and scheduling needs, and yet have no the edges. People nearing retirement and their children fulfillment from work, passion for the work. just entering the job market will become the most and willingness to work entrepreneurial generations ever.” Different motivations will extra hours. From an employer’s perspective, a passionate worker is lead to similar paths; the broad spectrum of entrepreneurs talented and motivated and has a sense of unfulfilled who will be pursuing their passions as professions will drive Worker passion acts potential. Passionate workers may tend to be frustrated, a fundamental change in the way we view work. as an amplifier to the however, if they feel blocked in their efforts to achieve that knowledge flows, potential for themselves and their companies. Observations and Implications thereby accelerating In our survey-based study, respondents were categorized as the growth of the Flow A generation ago, most workers followed a similar career “disengaged,” “passive,” “engaged,” or “passionate” based Index. path: work for a single employer and rarely deviate from a on their answers to a series of questions.116 The survey also field of expertise, secure in the notion they would collect measured job satisfaction, job search behavior, and inter- a good pension after decades of loyalty. Work was less a firm knowledge flows. The overall worker passion score has pursuit of passion than a means to put food on the table hovered between 20 and 23% over the last three years (see and a roof overhead. A worker hoped to earn enough Exhibit 69), indicating that the percentage of “passionate” money to pursue their real passions after work or after employees in the workforce has not changed significantly. retiring. Over the same period, the percentage of “engaged” workers edged up, offsetting a decline in “disengaged” workers. Unlike prior generations that often enjoyed considerable While companies have not yet managed to ignite worker job stability, today’s workers no longer compete only passion more broadly, they are at least reducing the number with workers in local labor markets, but, thanks to falling of employees who would most negatively impact employee interactions costs,114 with workers across the globe. As a culture. The level of “passive” workers has stayed constant Silicon Valley billboard put it, “1,000,000 people overseas at 31%. can do your job. What makes you so special?”115 We continue to focus on passionate employees—we believe Why does passion matter? Because staying competitive this passionate segment will be best able to increase their 114 See Patrick Butler et al., “A Revolution in Interaction,” The in the newly globalized labor market requires all of us to rate of learning to keep pace with the rapid technological McKinsey Quarterly, 1997, no. 1. 115 For more about this billboard, see constantly renew and update our professional skills and evolution driving today’s Big Shift. “What Makes You So Special?: With Over 1 Million People in the World Able to Do Your Job, Altium Acts to Help More,” Reuters, http://www.reuters.com/article/ pressRelease/idUS180975+20-Apr- 2009+MW20090420 (created April 20, 2009). 116 For information regarding survey scope and description, please refer to the Shift Index Methodology section.

96 Worker Passion Worker Passion 1

Updated Exhibit 69: Worker Passion, (2011-2009) Title Here Tab 2011 Flow Index Exhibit 69: Worker Passion (2011-2009)

40%

35% 31% 31% 31% 30% 27% 25% 24% 24% 25% 23% 22% 21% 21% 20% 20% and year

15%

10% Worker Passion Percentage of employees, by Passion category 5% 2 0% Disengaged Passive Engaged Passionate

2011 (n=3108) 2010 (n=3108) 2009 (n=3201) Source: Synovate, Deloitte analysis

Source:Exhibit Synovate 70: Worker, Deloitte Passion analysis Index by Current work-life situation, (2011) Exhibit 70: Worker Passion Index by Current work-life situation (2011) 70%

60%

50% 50% 44% 39% 40% 37% life situation - 34% 32% 32% 32% WP Metric 30% 68 24% © 2011 DeloitteWrite Touche- Tohmatsuup 20% 20% and current work 15% 14% 10% 9% 10% Percentage of employees, by Passion category 5% 3%

0% DisengagedI found my passion in my professionPassive I found a professionEngaged that matches my passion Passionate I pursue my passion as a hobby I haven't found my passion Source: Synovate 2011 WP/IFK Measurement (n=3108) Source: Synovate 2011 WP/IFK Measurement (n=3108)

Workers self-reported sense of being able to pursue their When asked about whether workers had “little control passions within their professions correlates with their over the amount that they worked,” passionate workers behavior- and attitude-based worker passion score (see were twice as likely to state they very strongly disagreed Exhibit 70). The majority of passionate” workers report or strongly disagreed with this statement, as compared having found a way to connect their passion to their to disengaged workers. These results also indicate that profession, while the remaining “passionate” workers passionate employees feel the most sense of control about pursue their passion outside of work through hobbies or their contributions to the workplace. other endeavors. “Engaged” workers demonstrated similar behavior, though significantly fewer of them found their To a lesser extent than for the self-employed, workers at passion through their profession. Workers classified as smaller firms tend to be more passionate than workers “passive” or “disengaged”, by contrast, either are pursuing at larger firms. The relationship between the size of the their passions through personal hobbies or are entirely company and worker passion highlights two factors that unaware of their passions. seem to drive passion for work: autonomy and opportunities for growth. Both are provided by a less constrained work Self-employed workers tend to be more passionate about environment which is often characteristic of either self- their work. In the 2011 survey, the difference between self- employed or smaller company work environments. In employed and company-employed workers is pronounced addition, smaller companies offer more opportunities (see Exhibit 71): 45% of self-employed workers are for cross-functional interactions, which encourage tacit “passionate” (compared to 19% of company-employed knowledge sharing, and have fewer organizational workers), while only 9% of self-employed workers are boundaries, which inhibit knowledge sharing and innovation “disengaged” (compared to 26% of company-employed in thinking and work practices. workers). This is not surprising given the overlap between Still, large firms run the risk of driving people out of the Worker Passion the motivations for self-employment and the drivers of organization if they are unable to create environments that passion: autonomy, meaningfulness of work and more foster knowledge sharing across the organization. However, 3 intimate interactions in all business transactions. it is unreasonable to suggest that worker passion does not exist entirely in larger enterprises, as indicated by the survey Updated Exhibit 71: Worker Passion by employment type, (2011) Exhibit 71: Worker Passion by employment type (2011)

50% 45% 45%

40%

35% 32%

30% 28% 26% 25% 24%

20% 18% 19%

and employment type 15%

10% 9%

5% Percentage of employees, by Passion category

0% Disengaged Passive Engaged Passionate

Self Employed Firm Employed Source: Synovate, Deloitte analysis

Source: Synovate, Deloitte analysis

Updated Exhibit 72: Worker Passion by size of firm, (2011) Title Here Tab 2011 Foundation Flow Index Index Exhibit 72: Worker Passion by size of firm (2011)

40%

34% 35% 31% 30% 27% 28% 25% 25% 23%

20% 17% 16%

and size of firm 15%

10%

Percentage of employees, by Passion category 5% Worker Passion 0% 5 Disengaged Passive Engaged Passionate

1 to 99 100 to 499 500 to 999 1,000 to 4,999 5,000 or more Source: Synovate, Deloitte analysis Source: Synovate, Deloitte analysis Exhibit 73: Inter-Firm knowledge flow participation and passion, (2011) Exhibit 73: Inter-Firm knowledge flow participation and passion (2011)

50%

45%

40%

35%

15%

10% by by Passion category and participation type 5% Percentage participationin Inter 0%

Passionate Engaged Passive Disengaged 2010, 2011 Deloitte Worker Passion/Inter-Firm Knowledge Flow Survey; Administered by Synovate

Chris Anderson and DIY Drones

When Wired Magazine Editor-in-Chief Chris Anderson had to find a president for his fledgling unmanned aerial vehicle business, commonly referred to as UAVs or Drones, it was not a litany of Stanford degrees, but an online video of a helicopter operated by Wii controller that moved Jordi Muñoz’s resume to the top of the stack. Relatively untrained (Muñoz attended one year of University in Mexico before moving to San Diego with his wife), and completely untested in the world of business, it was Muñoz’s passion for Drones and prominence in amateur Drone communities that won him the job.

In 2009, Anderson and Muñoz co-founded 3D Robotics – a robot manufacturing company with factories in San Diego, California and Bangkok, Thailand. In short order, the firm had grown to 11 staffers, and in March 2011, revenues hit over one hundred and sixty thousand dollars, up from a modest five thousand their first month. Still a small player in the space, 3D Robotics is generating buzz among large clients. 3D Robotics is able to innovate so quickly in large part because of its rich participation in knowledge flows, including a 15,000-member community of enthusiasts at DIY Drones centered on the open source coding to operate UAVs.

Though Muñoz did not have the traditional credentials to lead such a fast-growing venture, his passion for the work and access to rich flows of information made him the strongest candidate. This passion has carried over into his tenure at 3D Robotics. He and Anderson share a vision of a world where drones are household entities: “Our approach,” he said in one interview, “is the personal computer.” To achieve this, Muñoz has retained the questing and connecting dispositions that helped cultivate his boyhood fascination into a deep expertise.

The partnership between Anderson and Muñoz continues, as does their rich participation in inter-firm knowledge flows. For more, see Muñoz’s blog at http://diydrones.com, the largest amateur Unmanned Aerial Vehicle community on the web.

results (16%). Large companies, because of their size, have Because passionate workers are more engaged in their work a greater potential to foster connections within and often and eager to learn and to improve their job performance, outside of the organization. The latter is particularly true as worker passion is correlated to participation in inter-firm large companies can provide individuals looking to estabilsh knowledge flows (see Exhibit 74). Inter-firm knowledge connections beyond their immediate workplace with a flows allow motivated employees to connect with, and learn ceratin level of creditibilty, acting a large amplifier. from, other motivated and talented workers, reinforcing their sense of meaning and connectedness and providing Given this trend, larger organizations at a minimum should the means for self-improvement and growth. be mindful to avoid creating information silos and look for ways to foster cross-functional knowledge sharing. Leaders Driven by the twin forces of the technology infrastructure in larger firms should consider looking for ways to enable and more liberalized public policies, companies can passionate workers to operate with greater autonomy and increasingly create value through participating in “flows” of should make readily available opportunities for continued knowledge rather than from accumulating and exploiting learning, including social software, published works, and “stocks” of knowledge. Already, the lion’s share of profits both intra-firm and inter-firm knowledge flows – to enable at big companies in the developed world is the result of passionate workers to continue to fuel their passion. talented workers monetizing intangible assets.117 Since passionate workers have a greater propensity to participate The way some of our “passionate” respondents describe in knowledge flows, it makes sense for companies to find their work environments illustrates these ideas. As one ways to increase the level of passion workers find in, and middle manager in the Media & Entertainment industry bring to, their jobs. described it, his work provides him the “freedom to express creativity and the power to present ideas without feeling A talent development value proposition is an increasingly repressed.” An executive in the Life Sciences industry finds important for companies vying to recruit and retain top passion in his work from “utilizing my skills to the most. talent. Talented workers will be attracted to organizations Enjoying the challenges and rewards that come with it.” that provide an environment where workers’ learning and

117 See Lowell Bryan and Michele Zanini, “Strategy in an Era of Global Giants,” The McKinsey Quarterly 2005, no. 4.

100 Tab Title Here Tab 2011 Foundation Flow Index Index

outlook will be enhanced through ongoing development When asked about whom they identify with most, the and easy access to knowledge flows. passionate employee was most likely to respond as someone who seeks out challenges to improve performance, even One important caveat: attracting talent and tapping in the presence of significant risks (45%). These responses employee passion is not limited to knowledge workers as indicate a willingness by the passionate employee, we conceptualize them today. Peter Drucker initially defined that they are inspired (seeing an opportunity to learn a “knowledge worker” as “one who works primarily with something new) or energized (seeing an opportunity information or one who develops and uses knowledge in for problem solving) rather than being indifferent or the workplace.” However, employees at all levels and in exhibiting negative behaviors. The disengaged employee, all roles will increasingly participate in knowledge flows by contrast, was significantly less likely to react in this way, to perform their work, essentially making every worker a which is indicative of a much more reactive approach. The knowledge worker. This transformation in the workplace passionate employee’s questing disposition also drives calls for new approaches to managing and retaining talent higher performance as passionate workers do not shy from (further described in the Returns to Talent metric). challenges and actively pursue opportunities to blend new ideas from across companies, industries and disciplines into The competitive environment has strengthened the need their current work. for firms to create and retain passionate employees. These workers are proactive, seek continual performance As the rate of change in the business environment increases, improvement, inspire innovation and possess both a the passionate worker is most apt to adjust and thrive, and “questing” disposition, which drives them to seek out new will foster those behaviors within their companies. They sources of knowledge, and a “connecting“ disposition. view challenges as exciting opportunities to drive themselves This connecting disposition then drives them to build to a new level of performance. Employees who are not relationships within the organization and outside of its walls passionate tend to experience unexpected challenges as a to tap into the latest thinking and insights. source of stress and are increasingly likely to burnout and become a drain on the organizational vitality.

Exhibit 74: Inter-Firm knowledge flow participation and passion, (2011)

Exhibit 74: Passion and worker self-identification (2011)

100%

80%

61% 58% 57% 60% 48% 45%

40% 32%

and attitude and 27% 22% 17% 20% 15% 11% 7%

0% Percentage participation, bycategory Passion Percentage Disengaged Passive Engaged Passionate Someone who seeks out challenges to improve performance, even in the presence of significant risks

Someone who tackles challenges when they are presented because they are opportunities to improve performance

Someone who deals with challenges when they are presented because they are unavoidable 2010, 2011 Deloitte Worker Passion/Inter-Firm Knowledge Flow Survey; Administered by Synovate

Source: 2010, 2011 Deloitte Worker Passion / Inter-firm Knowledge Flow Survey; Administered by Synovate

2011 Shift Index Measuring the forces of long-term change 101

Social media activity creates scalable ways to connect and tap into knowledge flows

Introduction a network of people as much as a network of information. The Social Media Hundreds of millions of people around the world are online This network is changing how people connect and interact Activity metric measures and a significant portion of them are engaged in trying to with one another, blurring the lines between personal and how many minutes enrich both personal and business relationships. As more professional, and forcing business leaders to rethink how Internet users spend and more people use the Internet, the ability for individuals best to engage employees and consumers. on social media Web to easily find and communicate with others around sites relative to the total common interests, regardless of geography, continues to Observations and Implications minutes they spend on reshape and transform the way knowledge flows. Social Consumption of social media has exploded in the past the Internet. media sites, the virtual communities within Internet Web few years. The average number of daily visitors on social sites, organize these interests and enable participants to networking sites doubled from 46M per month in 2007 The metric is a proxy for connect and exchange information using a variety of tools: to nearly 90M per month in 2011.118 Similarly, the total two- and multiple-way email, voice, chat, instant messages, videoconference, minutes spent by U.S. users on social networking sites grew communication, which blogs, etc. Because it supports and organizes information 236%, from 25B in 2007 to 59B in 2011. amplifies knowledge sharing and rich interaction, social media is an important flows by offering the amplifier of knowledge flows and thus an essential metric in The growth in social media activity is the direct result of ability to collaborate. the Shift Index. both the technological changes (discussed elsewhere in this report) that have made the Internet more widely accessible Society has embraced social media as a means of and changing social behaviors. Every month, more than expression and a creative outlet, while technological 250 million people engage with Facebook on external advancements have allowed social media platforms to Web sites and more than 2.5 million Web sites integrate serve as catalysts for open innovation. The use of social with Facebook.119 Mobility has also had a huge impact, Social Media 1 media will continue to be driven by societal as well as giving individuals the ability to check in anywhere, anytime, technological changes. The increasing amount of time on social media. More broadly, social media platforms spent on social media as a percentage of time spent on the have spurred new technologies, including blogs, picture Internet reflects how the World Wide Web is evolving into sharing, vlogs, wall postings, email, instant messaging, Updated Exhibit 75: % of Internet time spent on Social Media, (2007-2010) Exhibit 75: Percentage of Internet time spent on Social Media (2007-2010)120 16% 14.4% 14%

12%

10%

7.4% 8%

4% Percentage of internet timespent on socialmedia 2%

118 comScore and Deloitte analysis 0% 119 http://www.facebook.com/press/ 2007 2008 2009 2010 info.php?statistics Time Spent on Social Media 120 comScore and Deloitte analysis Source: comScore, Deloitte analysis 102 Source: comScore, Deloitte analysis

74 © 2011 Deloitte Touche Tohmatsu Social Media Activity Social Media 2 No Updates Exhibit 76: Social Technographics Ladder Needed Exhibit 76: Social Technographics Ladder Tab Title Here Tab 2011 Flow Index • Publish a blog • Publish your own Web pages Creators • Upload video you created • Upload audio/music you created • Write articles or stories and post them

Conversation- • Update status on social networking site alists • Post updates on Twitter

• Post ratings/reviews of products or services Critics • Comment on someone else’s blog • Contribute to online forums Groups include • Contribute to/edit articles in a wiki customers participating in at • Use RSS feeds least one of the Collectors indicated activities at • “Vote” for Web sites online least monthly • Add “tags” to Web pages or photos

Joiners • Maintain profile on a social networking site • Visit social networking sites

• Read blogs • Listen to podcasts Spectators • Watch video from other users • Read online forums • Read customer ratings/reviews

Inactives • None of the above

Source: Forrester Research Inc. Source: Forrester Research Inc.

musicsharing, crowd sourcing, and VOIP, to name a few. ladder to illustrate the concept of Social Technographics® These technologies amplify knowledge flows by making (benchmarking consumers by their level of participation in 75them richer and more personalized. social computing)— the higher the rung, the more involved © 2011 Deloitte Touche Tohmatsu the participation (see Exhibit 76). According to Forrester, A recent study by iStrategylabs indicates growth in users U.S. consumers people are playing an increasingly active across all age groups. Between 2010 and 2011, the 18-24 role in their social media experience as creators — writing age group showed the highest growth on social networking blogs, making Web pages and updating content — as site, Facebook, with a 74% increase. Surprisingly, the indicated by increases from 2007 to 2010 in all “rungs” second highest growth came from the 55+ age group, with except for “inactives” (those who do not participate in a 59% increase in users.121 A separate study of penetration social media at all). The number of “inactives” decreased rates across age groups indicates that while the younger from 44% in 2007 to 19% in 2010 (see Exhibit 77) and we 121 “71% of All U.S. Web Users generation (below 24 years of age) built critical mass on expect this trend to continue. are On Facebook” http://www. allfacebook.com/71-percent-of-u-s- social networking sites first, continued growth is now web-users-are-on-facebook-2011- coming from the older age groups.122 As social media becomes more pervasive, companies are 01?utm_source=feedburner&utm_ medium=feed&utm_campaign=Fe making social media an integral part of their relationship ed%3A+allfacebook+%28Faceboo k+Blog%29 The online individual is no longer a passive bystander. A with consumers, employees, and other stakeholders. 122 http://www.bzzagent.com/blog/ report published by Forrester Research in 2010 used a Forrester estimated that $716M was spent in social media wp-content/uploads/2010/09/ Pew-older-adults1.png 2011 Shift Index Measuring the forces of long-term change 103 Social Media 3 – coming from JL

Not Updated Exhibit 76: Social Technographics profile of U.S online adults, (2009)

Tab2011 Flow Index Here Title Exhibit 77: Social Technographics profile of U.S online adults (2009)

2009 24% Creators 2008 21% 2007 18%

2009 33% Conversa -tionalist 2008 2007

2009 37% Critics 2008 37% 2007 25%

2009 20% Collectors 2008 19% 2007 12%

2009 59% Joiners 2008 35% 2007 25%

2009 70% Spectators 2008 69% 2007 48%

2009 17% Inactives 2008 25% 2007 44%

Source: Forrester Research Inc. Source: Forrester Research Inc.

marketing in 2010 and expects it to reach $3.1B by 2014, to appropriately participate in knowledge flows. Companies making social media a bigger channel than email or mobile, must at least prescribe appropriate protocols for sharing though still far smaller than search or display advertising. information. However, the true value of social media Among global Fortune 100 companies: 65% use Twitter, for companies lies in their ability to use social media to 54% are on Facebook, and 50% post videos to YouTube. find new ways to interact with consumers. Collaboration Seventy-nine% of the Fortune 100 use at least one of these marketing, for example, focuses on developing a company’s social media sites and 20% use all of them.123 ability to attract (create incentives for people to seek you 76 out), assist (be as helpful and engaging as possible), and © 2011 Deloitte Touche Tohmatsu As the lines between networks blur and internal and affiliate (mobilize and leverage third parties). external audiences interact together on social media, employees need some guidance and governance on how

Core Metrics Creating New Value

n 2009, CareOne already knew that its online community of 1.4 million people was a valuable source of information. The debt relief company wanted to explore social media channels to further develop its relationships with these customers. “Our primary goal with social media was customer retention,” said team leader Nichole Kelly. But the team soon realized that many of the online community members were prospective customers who needed help rather than existing customers and a larger opportunity was at hand. I 124 The team retooled its social media plan to reach out to these potential customers.

Kelly discovered that the personal connection generated through social media contact had a tremendous impact on the company’s core metrics. Although the social media prospects had a longer buying cycle (24-28 123 http://webbiquity.com/ days versus as low as 30 minutes), there was an incredible jump in successful conversions through the sign-up social-media-marketing/best- process and ultimately the point of purchase. The volume of leads generated was 179% higher, and social social-media-stats-facts-and- marketing-research-of-2010/ media customers were 217% more likely to make their first payment. For one particular problem area (people 124 Case Study: Social Media who partially fill out the sign-up form then quit), social media prospects went back and completed the form Customers Are More Valuable Customers. Social Media Explorer. 680% more often than non-social media leads. The social media prospects also made their first payment at an http://www.socialmediaexplorer. astonishing 732% better rate. com/social-media-marketing/ social-media-customer-value/

104 Tab Title Here Tab 2011 Foundation Flow Index Index

2011 Shift Index Measuring the forces of long-term change 105 2011 Impact Index

Markets 111 Competitive Intensity 114 Labor Productivity 117 Stock Price Volatility

Firms 120 Asset Profitability 124 ROA Performance Gap 128 Firm Topple Rate 131 Shareholder Value Gap

People 134 Consumer Power 138 Brand Disloyalty 142 Returns to Talent 145 Executive Turnover

106 2011 Shift Index Measuring the forces of long-term change 106 2011 Impact Index Tab Title Here Tab 2011 Impact Index Foundations and knowledge flows are fundamentally reshaping the economic playing field.

Trends set in motion decades ago are fundamentally of scale-based corporate strategy has never been more altering the global landscape as a new digital infrastructure, clear. built on the sustained exponential pace of performance • At the same time, as returns were bifurcating but generally improvements in computing, storage, and bandwidth, on the decline, management innovations and technology progressively transforms the business environment. The have enabled workers and companies to be more Foundation Index and the Flow Index are meant to capture productive. As measured by the Bureau of Labor Statistics, this dynamic, while the Impact Index shows how and why it the productivity of labor has more than doubled since all matters. The Impact Index is a lagging indicator of how 1965. This begs a fundamental question: If not captured foundational shifts and new flows of knowledge are tangibly by firms, where did this value go? changing the way companies and consumers operate. • It appears that the bulk of it has been captured by consumers and talent, who have learned to harness the By our calculations, ROA for public companies has decreased power of digital infrastructure much more quickly than to one-quarter of its level in 1965. While their institutional counterparts. Our Consumer Power this deterioration in ROA has been particularly affected by Index indicates that consumers wield significant power trends in the financial sector, significant declines in ROA have with a 2011 score of 67 out of 100 — put simply, this occurred in the rest of the economy as well. Also, when you means that companies have to deliver more and more look at the best companies — the top value at what is often a lower price. Meanwhile, we see 25% of earners — even they have barely held their ground. that the total compensation of creative class occupations Clearly, there is a fundamental disconnect between the is, on average, more than double that of other mindset and practices of companies and the environment in occupations. Moreover, the compensation gap between which they compete. Here’s why: the creative class and the rest of the workforce has been • Aided by technology, interaction costs are plummeting, increasing, at a 4% CAGR during the past seven years, and public policy has enabled freer movement by eroding suggesting the increasing importance companies place on the barriers that once protected incumbents. At the talent. By participating in knowledge flows, creative talent same time, the economy itself has “gone digital” and is is capturing an increasingly larger share of the economic increasingly service based, meaning that companies need pie. fewer assets to effectively compete. These shifts have led to rapidly intensifying competition, which has more than Traditional, scale-based strategies have provided little doubled since 1965. sustained relief from these trends. Instead, companies are • As mentioned briefly above, this competition has taken an toppling from their leadership positions at nearly double extreme and consistent toll on profits. By comparing net the 1965 rate, and executives, using 20th-century strategies income and assets, we see that economy-wide profitability to address 21st-century problems, are seeing their tenures is significantly lower in 2010 than what it was in 1965. decline. • In addition, economic and shareholder returns are increasingly polarized. During the past 40 years, the top Taken together, these findings suggest a fundamental firms (those in the top quartile of performers) have barely rethinking of the way we do business is in order. Success held their ground, only marginally increasing their profit- in the digital era will be defined by how well companies ability and shareholder returns. The worst performers, share knowledge — how well they leverage foundations however, have seen their percentage losses for both more and participate in flows. In a constantly changing, highly than double. Today, the costs of falling behind are at their uncertain world, the value of what companies know today is highest point in decades and the purely defensive nature rapidly diminishing; new measures of success must be based

2011 Shift Index Measuring the forces of long-term change 107 Impact Index Drivers 1 Tab2011 Impact Index Here Title Exhibit 77: Impact Index, (1993-2010) Exhibit 78: Impact Index (1993-2010)

120 111 106 104 105 101 100 101 99 100 98 98 100 93 95 88 84 81 78 78 80

60 Index value Index

0 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Source: Deloitte Analysis

Source: Deloitte analysis on how fast they can learn. In this sense, we must transition metrics contribute to the index (that is, positively or nega- from scalable efficiency to scalable learning, as mentioned a tively) will have to be reassessed. number of times in this report. Our hope is that the findings above, revealed by the Impact Index, tangibly quantify the As with the Foundation Index and the Flow Index, this index imperative for this shift. is broken down into three drivers. In this case, these drivers are designed to quantify the impact of the Big Shift on three Rather than a cause for pessimism, these findings can key constituencies: be viewed as an opportunity to remake the institutional architectures of today’s corporations. Companies in the • Markets: The impact of technological platforms, open early-20th century learned to exploit the benefits of scale in public policy, and knowledge flows on market-level response to the energy, transportation, and communications dynamics facing corporations. This driver consists of three 77infrastructures of their time. Today’s companies must metrics: Stock Price Volatility, Labor Productivity, and © 2011 Deloitte Touche Tohmatsu develop and adapt institutional innovations of their own Competitive Intensity. if they are to make the most of this era’s emerging digital • Firms: The impact of intensifying competition, volatility, infrastructure. Once these innovations are sufficiently and powerful consumers and talent on firm performance. diffused through the economy, the Impact Index will turn This driver consists of four metrics: Asset Profitability, ROA from an indicator of corporate value destruction to a Performance Gap, Firm Topple Rate, and Shareholder reflection of powerful new modes of economic growth. Value Gap. • People: The impact of technology, open public policy, The Index and knowledge flows on consumers and talent, including Today, the Impact Index score is 101, as shown in Exhibit executives. This driver consists of four metrics: Consumer 78. Note that this index measures the impact of the Big Power, Returns to Talent, Brand Disloyalty, and Executive Shift: So as competitive pressures force down returns, as Turnover. markets become more volatile, or as brand loyalty erodes, the index will increase.125 Individually, these drivers tell us how the Big Shift has affected key groups over time. Collectively, as shown In this sense, to decide whether a decrease in a metric (such in Exhibit 79, they describe how rapid changes in the as profitability) should increase the index, we had to make foundations and flows are altering the dynamics between a guess as to which direction it would go — at least in the companies, customers, and the markets in which they short term — in response to the Big Shift. These decisions operate. were made in accordance with our logic (that competition will put growing pressure on returns) and Right away, we can tell that the Impact Index has not grown long-term trends (that returns have been steadily declining as consistently as the Foundation Index and the Flow Index. since 1965). However, as we predict above, there will This is to be expected: Unlike the latter two, the Impact come a time when companies learn to harness the new Index is particularly susceptible to short-term cyclicality, as 125 For further information on how the Impact Index is calculated, digital infrastructure and generate powerful, new modes it is based on a number of financial measures that fluctuate please refer to the Shift Index of economic growth. At that time, the way many of these over time. As such, we made an attempt to smooth the data Methodology section.

108 Impact Index Drivers 2

Exhibit 78: Impact Index drivers, (1993-2010) Exhibit 79: Impact Index drivers (1993-2010)

120

100

80 Tab Title Here Tab 2011 Impact Index

60 Index value Index

0 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Markets Firms People Source: Deloitte Analysis

Source: Deloitte analysis to represent long-term trajectories more clearly relative to traditional, scale-based corporate strategy — cut costs and short-term movements.126 acquire others to achieve industry leadership and to capture economies of scale — the pressures in the markets driver After doing this, we see that growth in this index is much impact firms nearly one to one. Since 1993, the firms driver, slower than in the Foundation Index or Flow Index: It has which measures the negative impact of the Big Shift on grown at a CAGR of 1.5% since 1993. The reason for this is individual companies, has grown over 20%, at a CAGR of that, at least right now, the underlying metrics in the Impact 1.1%. The similarity to increases in market pressures, despite Index do not move as fast as, say, increases in computing aggressive efforts to offset them, is striking. If companies power. But we do expect the index to keep growing — do not catch up in their ability to harness the new digital perhaps at an even faster rate — as companies begin to infrastructure, they will likely see their performance continue adapt their institutional architectures and business practices to deteriorate (perhaps even more quickly) as competition 78to more effectively harness the potential of the digital inevitably grows steeper. © 2011 Deloitte Touche Tohmatsu infrastructure and richer knowledge flows. Unfortunately, we are forced to make assumptions when it Slower growth does not mean that movements in this comes to the impact of the Big Shift on people because our index are of less importance. Shifts, albeit small, in the way of measuring this through a recent survey precludes us Impact Index are indicative of powerful trends, many of from assessing historical trends (see Exhibit 82 represents which were discussed in the previous section. For example, an estimate). But understanding that changes in digital where we are today (an index value of 101) is the result of technologies and practices tend to impact individuals before parallel growth in the impact of the Big Shift on all three institutions, we can be confident that people have been constituencies: markets, firms, and people. The impact impacted the most, and most consistently by the Big Shift. on markets, a reflection of growing Competitive Intensity, As technology continues to reshape the playing field and put Labor Productivity, and volatility in stock prices, has gone up power in the hands of consumers and talent, we expect this more than 33% since 1993, as shown in Exhibit 80. Since driver to increase. 1993, it has grown at roughly a 1.8% CAGR each year. As companies learn to harness the new digital infrastructure Overall, we expect the Impact Index to increase at a growing and knowledge flows to become more productive and more rate over the coming years, but with much more volatility effectively compete, we expect this to not only continue, but than the Foundation Index or the Flow Index. As individuals also increase significantly. continue to outpace institutions in the value they gain from technology, the broad competitive forces degrading The economic downturn may also have a lasting effect on performance will only increase and, with them, the index, these dynamics. Again, “normal” may, in fact, be a thing of until firms finally develop the institutional architectures and the past. business practices required to more effectively create and capture economic value. The impact at the firm level — shown in Exhibit 81 — is

highly telling. Despite an obsessive focus on tenets of 126 For further information on data smoothing, please refer to the Shift Index Methodology section. 2011 Shift Index Measuring the forces of long-term change 109 Impact Index Drivers 3

Exhibit 79: Market, (1993-2010)

2011 Impact Index Exhibit 80: Market (1993-2010)

Index value Index 30

20 Impact Index

10 Drivers 4

0 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Source: Deloitte analysis Exhibit 80: Firm, (1993-2010) Exhibit 81: Firm (1993-2010) Source: Deloitte analysis 80

Index value Index 30

10 Drivers 5

0 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Source: Deloitte analysis Exhibit 81: Flow Amplifiers, (1993-2010) Exhibit 82: People (1993-2010) Source: Deloitte analysis 80

40 The charts above represents the combined movements of Index value Index 30 the underlying metrics in the index, after data adjustments 80 © 2011 Deloitte Touche Tohmatsu and indexing to a base year of 20 2003. For more information on the index creation process, see 10 the methodology section of the report. 0 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Soure: Deloitte Analysis

110 Source: Deloitte analysis

81 © 2011 Deloitte Touche Tohmatsu Competitive Intensity 2011 Impact Index Competitive Intensity is increasing as the digital infrastructure and changing public policy erode the barriers to entry and movement

Introduction attachment to brands.128 The shift in market power from Many executives have the sense that the world is more the makers of goods and services to the people who buy The Competitive competitive today. Indeed, consultants and academics alike them increases the pressure on firms to innovate and sell in Intensity metric is a have argued this same hypothesis that pervasive forces of new and creative ways. measure of market the 21st century, such as globalization and technology, concentration and serves are creating unprecedented competitive pressures for Many of today’s companies continue to follow traditional as a rough proxy for established firms.127 Tracking Competitive Intensity is a way scale-based notions of corporate strategy, pursuing how aggressively firms of measuring the falling barriers to entry and movement mergers and acquisitions to achieve industry leadership, interact. It is based resulting from digital technology and public policy focusing tirelessly on cost reduction, and making every on the Herfindahl- changes. effort to squeeze value from the channel and suppliers. Hirschman Index (HHI), As quickly as they accomplish these things, however, which tracks changes in During the last several decades, public policy liberalization competitors enter with new efficiencies and ideas. Even industry concentration has opened up the global economy, allowing freer flow of leading firms struggle to stay ahead. by measuring the market capital across geographic and institutional lines. Businesses share held by the top 50 now find it easier to enter and exit markets, industries, and Observations and Implications firms. countries and workers enjoy fewer restrictions on where To illustrate how the HHI works, imagine an industry they can work. with high fixed costs of production. The high investment This metric is a rough required to do business (to build and operate factories, for proxy for changesCompetitive in Meanwhile, digital technology has removed previous example) are barriers to entry that enable a small group of competitive dynamicsIntensity 1 barriers to the flow of information, eroding the information players to win the lion’s share of sales. According to the over time. asymmetries that once favored sellers over buyers. HHI, market power is highly concentrated in this industry Today’s consumers have a growing wealth of knowledge and, as a consequence, it is deemed low in Competitive and choice when buying goods and services and less Intensity. Now consider the converse, in which barriers are Updated Exhibit 82: Economy-wide Herfindahl-Hirschman Index (HHI), (1965-2010) Exhibit 83: Economy-wide Herfindahl-Hirschman Index (HHI) (1965-2010)

0.16 Moderate Competitive Intensity

0.14 0.14

0.12 0.10

0.1 High Competitive Intensity

0.08

0.06 HHI Index HHI Index Score 0.05 0.04

0.03 0.02 127 William L. Huyett and Patrick Viguerie, “Extreme Com petition,” Very High Competitive Intensity The McKinsey Quarterly, 2005, no. 0 2 and Richard D’Aveni, Hyper- 1965 1969 1973 1977 1981 1985 1989 1993 1997 2001 2005 2009 Competition (New York: Free Press, 1994). HHI Linear (HHI) 128 For further information, refer to the Consumer Power and Brand Source: Compustat, Deloitte analysis Disloyalty sections. Source: Compustat, Deloitte analysis 2011 Shift Index Measuring the forces of long-term change 111

Competitive Intensity 2

Updated Exhibit 84: Economy-wide merger activity and HHI, (1972-2010) Exhibit 84: Economy-wide merger activity and HHI (1972-2010)

600 0.1 0.09 0.09 500 0.08

0.07 400 0.06 0.05 300 0.05 HHI

217 0.04 Number of Mergers 200 0.03

0.02 100 0.01

32 0 0 1972 1976 1980 1984 1988 1992 1996 2000 2004 2008

Merger Activity HHI

Source: CRSP US Stock Database ©200903 Center for Research in Security Prices (CRSP®), The University of Chicago Booth School of Business, Source:Deloitte CRSP analysis US Stock Database ©200903 Center for Research in Security Prices (CRSP®), The University of Chicago Booth School of Business, Deloitte analysis

Despite a brief climb in recent years, market Before 1995, industry concentration decreased consistently, indicating that Competitive Intensity overall was steadily concentration is still less than half of what increasing (see Exhibit 83).129 Despite a brief climb in recent years, market concentration is still less than half of what it was in 1965, suggesting that Competitive it was in 1965, suggesting that Competitive Intensity has Intensity has more than doubled during that more than doubled during that period. It is worth noting that HHI values between 0 and 0.10 denote low industry period. concentration and by extension high Competitive Intensity. The United States has fallen in that range throughout most 83 © 2011 Deloitte Touche Tohmatsu low and sales are spread evenly across a large number of of the period under analysis. firms. The HHI would indicate that there is little market concentration and this industry would be much more As noted above, our methodology suggests that competitive: more players means a greater chance — and Competitive Intensity has eased in recent years. We imperative—to compete for customer business. attribute this less to a decline in competition than to a wave of mergers and acquisitions (see Exhibit 84) that 130 Of course, this framework breaks down in a number have increased industry concentration and thus HHI. of situations and comparing industries with different Technically, this is a situation where our methodology structural characteristics using HHI is problematic. Overall, breaks down: In a given year, HHI might “get it wrong” however, longitudinal shifts in this metric provide a good because of heavy mergers and acquisitions. However, indicator for how Competitive Intensity has changed over over the long term, we view this merger and acquisition time. behavior as a response to increasing Competitive Intensity

129 Source: Compustat, Deloitte analysis. 130 Source: Deloitte analysis based on historical data from CRSP US Stock Database ©200903 Center for Research in Security Prices (CRSP®), The University of Chicago Booth School of Business.

112 Spotify: Street Fight for Distribution Channels or Music Everywhere? 2011 Impact Index

ver since Napster began offering peer-to-peer music file sharing in 1999, the music industry has been roiled by advances in the digital infrastructure that have turned traditional business models upside and, consequently, believe it supports the validity down and unleashed competition from unexpected places. of our metric. Executives seeking to defend their E company’s position often acquire competitors both to Enter the newest competitor to the already crowded digital music scene: In July reduce near-term pressure and to squeeze out more 2011, Spotify launched in the United States and has already made a significant costs through greater economies of scale. However, if impact on the music industry. Prior to their U.S. entry, Spotify had already achieved barriers to entry and barriers to movement continue success overseas; founded in Sweden, the service reached 1 million users less to erode, we expect that these defensive moves will than 6 months after launch in 2008. Spotify offers consumers the ability to stream only have short-term impacts until another wave of songs directly, create playlists, and share music with friends. And after just a competitors emerge to challenge incumbents. So few weeks in the United States, Spotify boasted 1.4 million U.S. customers, with even if HHI increases due to mergers and acquisitions 175,000 paying for service, an admirable 12.5% conversion rate by consumer over a few years, we believe the long-term trend is internet standards, where 2-4% is the prevailing conversion of free to premium highly indicative of a tectonic shift toward increasing products. Though growing rapidly, Spotify faces a host of direct and indirect competitive pressure. competitors. The firm competes directly with subscription-based streaming sites, such as Rhapsody, with a catalog of over 11 million songs and 800,000 paid The profound increase in Competitive Intensity since subscribers. There are also many more tangential competitors among internet the mid-1960s shows no sign of slowing. Not only are radio sites, such as Pandora and MOG, who are more focused on music discovery competitive forces increasing within the country, U.S. Source: CRSP US Stock Database ©200903 Center for Research in Security Prices (CRSP®), The University of Chicago Booth School of Business, than playlist creation. What differentiates Spotify from these competitors, and firms increasingly face competition from firms abroad. Deloitte analysis may make it difficult to fight back, is the degree of control that Spotify users have In today’s porous economy, where competitors may over their music and the social features that Spotify offers. Spotify is banking on a come from unexpected places, differentiating friend partnership with Facebook to encourage users to engage more with the site and from foe is increasingly difficult. As technological change the way people share music across social platforms. While all these music improvements disintegrate barriers to entry and sites provide slightly different services, they are battling for the same customers, promote the free flow of information, businesses hoping to convert internet users into paying music consumers. must rethink traditional strategic, organizational, and operational approaches. Scalable efficiency, the primary And what about the music companies themselves — are they collaborators or strategy firms undertook in the 20th century, will likely competitors? Although Spotify has signed distribution agreements with all of the have diminishing returns for firms going forward. ‘big four’ music groups, Spotify currently pays more for music royalties than it Instead, companies seeking to remain competitive 131 makes in subscriptions and advertising. Of course, the firm is also dependent on will need to consider increasing efficiency via scalable these agreements to avoid copyright infringement. learning, empowering employees to perform their jobs better and more efficiently. Finally, a large threat for Spotify and the music industry in general, still comes from a more nefarious competitor: pirating and illegal downloads.

A Spotify spokesperson acknowledges “Our biggest competitor is piracy rather than other streaming services. Our goal is to offer a user experience that is higher quality, simpler, and altogether better than piracy.”132

The rise of Spotify is a testament to the increasing Competitive Intensity felt by traditional incumbents and new entrants alike in the music industry. Just a few years ago, disruptors, such as Pandora and Rhapsody, forever changed the 131 Ben Sisario, “New Service Offers Music in Quantity, Not competitive landscape of the music industry. In today’s increasingly fast-changing by Song.” NY Times, continue as new models emerge to try to satisfy consumer’s needs. 132 David Lim, “Spotify Looks to Convert Teens from iTunes, Piracy.” Patch. 2011 Shift Index Measuring the forces of long-term change 113 2011 Impact Index Labor Productivity

Technological and business innovation, open public policy, and fierce competition, drive long-term increases in Labor Productivity

Introduction By focusing on “revenue productivity,” executives can The Labor Productivity Robert Solow famously said, “You can see the computer switch from wringing out ever-more elusive efficiency gains metric is a measure of age everywhere but in the productivity statistics.”133 Often to unleashing the potential of employees by increasing economic efficiency that referred to as the productivity paradox, this view holds that the rate at which they learn, which can, in turn, lead to shows how effectively big investments in IT have done little to increase long-term innovation and continuous performance improvement. economic inputs are labor productivity. There is tremendous opportunity to couple the digital converted into output. infrastructure with new management approaches to It is based on data from A central hypothesis of the Big Shift is that digital create and mobilize the knowledge that workers possess, the Bureau of Labor technology, as it increasingly penetrates business and unlocking the intangible assets that can drive company Statistics. social domains, holds the potential to substantially increase profits in the digital era. productivity growth. In this view, the fact that technology The metric is a proxy has yet to make a truly significant mark on productivity Advances in productivity, that is, the ability to produce for the value creation may say more about traditional institutional architectures more with the same or less input, are a significant source resulting from the Big and management practices than about what is possible in of potential national income.134 Shift and enriched the future as companies embrace the Big Shift. knowledge flows. Observations and Implications Traditional approaches to productivity improvement too As a whole, the U.S. economy has been able to achieve often focus on manipulating inputs—the denominator, modest productivity gains since 1965 (see Exhibit 85). or cost, side of the productivity ratio. Since companies The upward trend suggests that in the face of steadily can only reduce costs so far before reaching zero, this increasing competitive pressures, companies have been Labor is ultimately a diminishing returns game. The fixation able to achieve productivity growth. Productivity 1 on inputs moreover overlooks a bigger opportunity: the potential to offer more value while keeping the same total cost.

Exhibit 85: Labor Productivity, (1965–2010) Exhibit 85: Labor Productivity (1965-2010)

120 111.5

100 101.2

60 45.3

40 41.4 Tornqvist aggregation

20 133 Robert Solow, New York Review of Books, July 12, 1987. 134 Bureau of Labor Statistics, “Labor Productivity and Costs”. Unites 0 States Department of Labor. < 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 http://bls.gov/lpc/faqs.htm#P01> Source: Compustat, Deloitte analysis 114

Source: Compustat, Deloitte analysis

9 © 2011 Deloitte Touche Tohmatsu Tab Title Here Tab 2011 Impact Index While Labor Productivity in the United States has shown increased from 2.1% to 2.6%. This growth was in part a a consistent upward trend, Exhibit 86 suggests that the continuation of 1990s trends, including the proliferation of rates of growth over the past five decades have varied.135 IT advances. However, reductions in labor input also played In the 2000s, Labor Productivity increased at a 2.7% CAGR, an important role in the productivity increases of the past as compared with the 2.1% CAGR in the 1960s and the decade.136 As firms were hit with the economic downturn, lowest value of 1.6% CAGR in the 1980s. Productivity many sought efficiency gains and increased their reliance Labor growth accelerated in the late 1990s, led by rapid output on automation and outsourcing as a means to reduce Productivity 2 in IT-intensive industries and spurred by factors, such as costs. the rise of outsourcing (thus reducing the price of inputs.) In the 2000s, this growth trend continued, as CAGR

Exhibit 85: Labor Productivity CAGR, (1965 – 2010) Exhibit 86: Labor Productivity CAGR (1965-2010)

2.50%

2.00%

1.50%

1.00% Labor Labor Productivty CAGR

0.50% Labor Productivity 3

0.00% 1960s 1970s 1980s 1990s 2000s

Source: Compustat, Deloitte analysis Exhibit 86: U.S. Productivity Growth, (1965 – 2010) Exhibit 87: U.S. Productivity Growth (1965-2010) Source: Compustat, Deloitte analysis

5.0%

4.0% 3.9% 3.1% 2.3%

3.0%

1.9% 2.0%

1.0%

85 © 2011 Deloitte Touche Tohmatsu 0.0% 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 135 Note that the 60’s column of data includes data from 1965-1970 Percentage change in U.S. Labor Productivity 136 Holman, Corey, Bobbie Joyeux, Y - -1.0% and Christopher Kask. “Labor O - Productivity Trends Since 2000, Y by Sector and Industry”. February -2.0% 2008. Bureau of Labor Statistics. < http://www.bls.gov/opub/ Y-O-Y Percent Change Linear (Y-O-Y Percent Change) mlr/2008/02/art4full.pdf> Source: Compustat, Deloitte analysis Source: Federal Reserve Bank of New York 2011 Shift Index Measuring the forces of long-term change 115

Source: Federal Reserve Bank of New York

GE’s Enterprise Collaboration

n aviation team scattered across three countries and speaking two languages needs to work jointly to develop an application. A program developer in China wants to leverage the knowledge of an American counterpart to help him do his job faster. A newly minted manager in New York seeks a way to keep in touch with members of his old team. These are just three examples of issues resolved each day on General Electric’s (GE) corporate AWeb interface, SupportCentral. SupportCentral serves as the backbone of knowledge transfer throughout the multinational and multifaceted firm, creating collaboration between counterparts across the globe, and helping employees get to better answers faster through the power of scalable learning.

In the late 1990s, GE Senior Vice President and Chief Information Officer, Gary Reiner, identified collaboration and transparency as primary cultural goals for the 21st century. In 2000, a team of employees deployed SupportCentral, a Web community for GE employees, to share knowledge and connect with one another. Since then, SupportCentral has become “the heartbeat of the company,” according to Reiner. Indeed, the numbers are staggering: In 2008, there were 400,000 global users, including employees, visitors, and consultants working at GE sites in 6,000+ locations, all accessing SupportCentral via a Web interface available in 20 languages. SupportCentral receives over 25 million hits a day from employees all over the world (greater than employee usage of Google and Yahoo combined).137

Employees rely on SupportCentral as a tool for doing their jobs better and more efficiently. Over 100,000 experts (all full-time GE employees) have signed up to help respond to user questions and manage content, and SupportCentral has become the ubiquitous tool for sharing documents and information, keeping groups connected across departments and countries. This has many benefits for employees throughout the organization. For example, whereas before, process owners had to outsource the creation of applications to IT teams and wait for results, SupportCentral is an example of how a company made it simple for IT teams to serve as mentors — empowering process owners to develop and tweak solutions to fit their needs. According to one GE Manager, “Just in our small corner of Aviation, we are saving ~$11 Million in real productivity this year.”138

Foxconn, the Chinese manufacturer of Apple technology is being used to improve labor productivity by moving employees into higher value positions and devices such as the iPhone and iPad, recently reducing the number at lower levels. Foxconn, the Chinese manufacturer of Apple devices, such as the iPhone and announced a plan to deploy one million robots iPad, recently announced a plan to deploy 1 million robots to perform basic manufacturing work. to perform basic manufacturing work. Foxconn CEO announced that, in addition to allowing the company to produce a greater volume of higher quality products, the Going forward, U.S. firms may find greater, and more shift will move the company’s workers “higher up the sustainable, productivity growth in the rapidly advancing foodchain, beyond basic manufacturing work.”139 digital infrastructure. An effective way to realize this potential is for companies to embrace new institutional In thinking about productivity improvement in the Big architectures, governance structures, and operational Shift, it is imperative that companies evaluate how to best practices, and to track, for example, employee adoption capitalize upon the potential of employees. Productivity of new technologies, how well employees are sharing yields can and likely will be influenced by firms’ willingness knowledge across organizational boundaries, and the to adopt technologies that allow resources to do their extent to which their employees are part of an ecosystem jobs better and more efficiently, from using emerging 137 Olivia Marks, “GE’s Enterprise Collaboration Backbone.” ZDNet. that is creating new value for customers. Scalable efficiency technologies to minimize the number of employees July, 17 2008. rather, the real gains can stem from harnessing the employees to access information and connect with one 138 Chuck Hollis, “A Humbling Experience”, Chuck’s Blog. July potential of scalable learning made possible by the digital another more easily. Empowering employees to participate 08, 2008. < http://chucksblog. infrastructure. typepad.com/a_journey_in_social_ in knowledge flows should, in time, allow for long-term, media/2008/07/a-humbling-expe. increasing productivity gains. html> 139 Christina Bonnington, “iPhone Investments in technology can also enable firms to Maker Foxconn Employs 1M produce more with fewer resources. Even in industries and Robots to do Grunt Work.” Wired Magazine. http://www. countries where labor is abundant and cheap, new digital wired.com/gadgetlab/2011/08/ foxconn-robots/

116 Stock Price Volatility Tab Title Here Tab 2011 Impact Index Digital infrastructures and public policy initiatives amplify Competitive Intensity, market uncertainty, and Stock Price Volatility The Stock Price Introduction Volatility in the markets has been a topic among experts Volatility metric is a It stands to reason that equity markets are a primary place for years. Recently, Professor Robert Stambaugh of measure of trends in in which the forces of long-term change would become The Wharton School said that while stocks have been movement of stock visible. Paradoxically, perhaps, these long-term forces are traditionally viewed as less volatile over the long-term prices. playing out in the form of increased short-term volatility in due to “mean reversion.”144 Mean reversion suggests that stock prices. prices and returns eventually move back towards the mean This metric is a or average, and in many respects stock prices tend to be proxy for measuring Our analysis of this metric draws on data from the Center more uncertain and more volatile over long horizons.145 disruption and for Research in Security Prices (CRSP) at the University of Stambaugh went on to say that the uncertainty of the uncertainty. Chicago Booth School of Business.140 By looking at the long-term trend erodes even short-term “certainties.” one-year standard deviation of daily value-weighted141 The prospect of 50 years of uncertainty is much more total returns across the entire U.S. economy,142 we tried unsettling than the prospect of one to two years’ 140 Established in 1960, CRSP maintains the most complete, to establish a proxy for market-related uncertainty as uncertainty followed by a resumption of stability. In the accurate, and easily usable securi- 143 ties database available. CRSP has expressed through Stock Price Volatility. interview, Stambaugh noted that even “two centuries of tracked prices, dividends, and data leaves one with enough uncertainty that as you look rates of return of all stocks listed and traded on the New York Observations and Implications at the implied variance of stock returns over the longer Stock Exchange since 1926, and in subsequent years, they have Over the last 38 years, Stock Price Volatility has been horizons, the risk actually does rise significantly with the also started to track the National steadily increasing (see Exhibit 88). Since stock prices are time horizon.” Association of SecuritiesStock Dealers Price Automated Quotation System heavily driven by investor reaction to the news of the day (NASDAQ) and the New York Stock Exchange (NYSE) Arca, previouslyVolatility 1 and assumptions about what is to come, volatility in stock According to our findings, the long-term trend is toward known as ArcaEx, an abbreviation prices can be seen as a reflection of increasingly volatile higher short-term Stock Price Volatility. That is, in any given of Archipelago Exchange. 141 “In a value-weighted portfolio events and higher uncertainty about the future. week or month, stock prices are likely to fluctuate more or index, securities are weighted by their marketUpdated capitalization. Each period the holdings of each Exhibit 88: Economy-wide Stock Price Volatility, (1972-2010) security are adjusted so that Exhibit 88: Economy-wide Stock Price Volatility (1972-2010) the value invested in a security relative to the value invested in the portfolio is the same proportion 0.030 as the market capitalization of the security relative to the total portfolio market capitalization.” CRSP Glossary, s.v. “Value- 0.025 Weighted Portfolio,” http://www. crsp.com/support/glossary.html. 142 Calculated (or derived) based on data from CRSP US Stock Database 0.020 ©200903 Center for Research in Security Prices (CRSP®), The University of Chicago Booth School of Business. 0.015 143 Stock Price Volatility is a suitable proxy for uncertainty about where the markets are headed. See Standard Deviations Robert Stambaugh and Jeremy J. 0.012 0.010 Siegel, “Why Stock-Price Volatility Should Never Be a Surprise, Even in the Long Run,” interview by Knowledge@Wharton, April 29, 0.005 0.005 2009. 144 Ibid. “Volatility does tend to even out over time and stock returns tend to fluctuate around a trend 0.000 line.” 1972 1975 1978 1981 1984 1987 1990 1993 1996 1999 2002 2005 2008 145 Lubos Pastor and Robert F. Stambaugh, “Are Stocks Really Less Stock Price Volatility Linear (Stock Price Volatility) Volatile in the Long Run?,” http:// Source: CRSP U.S. Stock Database ©200903 Center for Research in Security Prices (CRSP®), ssrn.com/abstract=1136847 (last revised May 29, 2009). The University of Chicago Booth School of Business, Deloitte analysis Source: CRSP US Stock Database ©200903 Center for Research in Security Prices (CRSP®), The University of Chicago Booth School of Business, Deloitte analysis 2011 Shift Index Measuring the forces of long-term change 117

The Flash Crash of 2010

t was just another day on Wall Street on May 6th 2010. The U.S. stock markets opened down that morning and trended down most of the day on worries about the debt crisis in Greece. Then, suddenly, things began to change. At 2.42 pm, the Dow Jones dropped more than 300 points for the day, the equity market began to fall rapidly, dropping more than 600 points in 5I minutes for an almost 1000-point loss on the day by 2:47 pm. Twenty minutes later, by 3:07 pm, the market had regained most of the 600-point drop, however, for a few minutes the market lost $1 trillion worth of market capitalization! Says Seth Hoenig, Head trader at Glenhill Capital Management, “We were floored and it was surreal. We have been conditioned in these past ten years to rule out nothing. I remember being in disbelief as to the magnitude of the move in such a short period of time. We were trying to decipher whether or not we were missing information or news, and the move was not reflecting some world event, perhaps with Greece or the EU.”

Market Snapshot — DJIA 2:00 PM -155.76 points 2:40 PM -415.81 points 2:47 PM -998.50 points 2:57 PM -388.38 points 4:00 PM -347.80

The May 6, 2010, market crash, also known as The Crash of 2:45, the 2010 Flash Crash or just simply, the Flash Crash, was a U.S. stock market crash on May 6, 2010, in which the Dow Jones Industrial Average plunged about 900 points — or about 9% — only to recover those losses within minutes. It was the second largest point swing, 1,010.14 points, and the biggest one-day point decline, 998.5 points, on an intraday basis in Dow Jones Industrial Average history.

Investigations by the U.S. Securities and Exchange Commission (SEC) and the Commodity Futures Trading Commission (CFTC) into the cause of the crash help shed light on how the Big Shift has generated greater Stock Price Volatility. To begin with, uncertainty concerning the debt crisis in Greece had set up a market “so fragmented and fragile that a single large trade could send stocks into a sudden spiral.” Specifically, the SEC’s and CFTC’s report highlighted the role of one mutual fund, Waddell & Reed, in precipitating the crisis. At 2.32 pm, Waddell & Reed initiated a trading algorithm that sold 75,000 E-mini futures contracts (which mimic movements in the S&P 500 stock index). Even though trades of that size were normal for Waddell & Reed, this particular algorithm executed the trade within a span of 20 minutes. Comparatively, a trade of similar size in 2010 had taken 5 hours to complete. As Waddell & Reed’s sale hit the futures market, high-frequency trading firms began picking up their contracts. Because high-frequency trading firms exit trades very swiftly, by 2:41 pm they had begun selling the contracts they had bought from Waddell & Reed, which was still trying to sell the remainder of its contracts as prices declined. The rapid sell-off then began to spill over into the market for stocks. Liquidity began drying up as automatic trading systems used by market makers began to pause when prices moved beyond certain thresholds. Collectively, the sell-off briefly erased $1 trillion in value, but recovered most of the ground before trading closed for the day.146

The “Flash Crash” of 2010 is illustrative of changes the Big Shift has brought. Foundationally, falling computing costs and the complexity of modern trading algorithms made possible the rapid sell-offs that occurred on the day, and the fluidity of capital and knowledge flows was what set the context for stock market uncertainty. Most of all, it makes apparent that our institutions and practices must adapt to the Big Shift if we are to avoid similarly disconcerting market disruptions in the future.

146 “How A Trading Algorithm Went Awry”, Wall Street Journal, Oct 2nd 2010

118 widely than they would have in a given week or month

Surveying today’s business landscape, perhaps Title Here Tab 2011 Impact Index 20 or 30 years ago. We believe that this is attributable to several aspects of the Big Shift. First, increasing investors intuitively grasp that “normal” is a penetration of digital technology has reduced information asymmetries in markets and enabled the proliferation of thing of the past—that we have entered a complex financial trading mechanisms. Most importantly, world that does not stabilize as easily as it once this has exacerbated and amplified investor reactions to changes in the market, which has increased Stock Price might have. Volatility. Second, the fluidity of capital flows across international borders due to the liberalization of public As we hope this report makes clear, companies must soon policy has contributed to the amount of speculation come to terms with the Big Shift through new institutional and volatility in markets. Third, the unwillingness or architectures, governance structures, and operating inability of many executives to give a clear sense of the practices. We expect these new approaches will enable long-term direction of their companies has contributed to firms to better navigate and potentially thrive in a less uncertainty of long-term company performance and the stable environment. To the extent that firms are able to resulting valuation. Finally, as investors are increasingly adapt to the realities of the Big Shift, they might be able to uncertain about the economy and companies abilities to restore investor confidence in their ability to create value tap into long-term changes, executives have also been amidst our new economic realities. While stock prices will either unwilling or unable to provide a clear sense of their always be influenced by market sentiments and economic companies’ long-term direction. Collectively, investors’ forces, this might possibly ameliorate the volatility of stock short-term doubt about company performance manifests price movements in the future. itself in the form of greater short-term Stock Price Volatility.

Surveying today’s business landscape, perhaps investors intuitively grasp that “normal” is a thing of the past—that we have entered a world that does not stabilize as easily as it once might have. Investors may also sense a mismatch between the mindset and capabilities of today’s companies and the environment in which they compete.

2011 Shift Index Measuring the forces of long-term change 119 2011 Impact Index Asset Profitability

Cost savings and the value of modest productivity improvement tends to get value from productivity gains are being competed away and captured by customers The Asset Profitability metric (Return on Assets) and talent is a measure used to Introduction Second, we use ROA instead of revenue-oriented evaluate corporate To measure long-term corporate performance, we metrics, such as Return on Net Sales because ROA allows performance. calculated economy-wide Asset Profitability (ROA) for all us to measure returns in comparison to a firms’ asset publicly traded firms (numbering greater than 20,000) holdings, thus making it a more complete picture of firm This metric is a proxy for between 1965 and 2010. We use ROA as a measure of performance. the value captured by Asset Profitability firm performance for two reasons. First, as opposed to firms relative to their size. other asset-oriented metrics, such as Return on Equity Observations and Implications 1 (ROE), ROA is a comprehensive measure of firm profitability The previous editions of the Shift Index highlighted that and is not affected by distortions associated with a firm’s ROA for the U.S. economy has been in steady decline for capital structure. the past 45 years. We believe that this decline in ROA Updated Exhibit 89: Return on Assets, Selected Industries, (1972–2010) Exhibit 89: ROA, Selected Industries (1972-2010)

8% 7% 5.7% 6% 5.4% 5% 4% 3.7% 4.6% 3% 2.8% 3.0% 2% 1.7% 1% 0% 0.7% -1% -2% Aerospace & Defense Health Care Services Linear (Aerospace & Defense) Linear (Health Care Services)

15% Return on Assets (%)ReturnAssetson 10% 7.3%

5% 6.8% 5.2% 2.0% 0% 0.6% -5% -0.1% 1972 1977 1982 1987 1992 1997 2002 2007 -10%

-15% Media & Entertainment Technology Automotive Linear (Media & Entertainment) Linear (Technology) Linear (Automotive) Source: Compustat, Deloitte analysis Source: Compustat, Deloitte Analysis

has been driven by companies’ inability to adapt to the average of 0.15% per year over the 45-year period. By long-term trends behind the Big Shift. While this decline contrast, the strongest performing industry, aerospace and has been influenced by trends in the banking industry, defense, only saw its ROA rise at an average rate of 0.02% this same declining trend in ROA has also consistently per year over the same period. While the bottom industries occurred across the rest of the economy. This decline is all are experiencing sharp declines in performance, the top the more noteworthy because of the increasingly favorable industry is just barely yielding better results over time (see tax environment and improvement efforts by individual Exhibit 89) companies. The effective corporate income tax rate has declined over the past 45 years and firms have engaged As part of our continued investigation into declining ROA, in a suite of efforts, including restructuring, outsourcing, we focused our attention on the role of the banking and mergers and acquisitions to improve performance. industry. There are two reasons why we were concerned The decline in ROA is significant because it has continued with the banking industry. First, the banking sector has in spite of these factors which we might have expected to come to constitute a large portion of the overall economy’s improve ROA. asset base. And second, the banking sector has also had historically low ROA levels. Taken collectively, these facts This year, our analysis confirmed that the decline in ROA yielded interesting results in our analysis of the declining is occurring consistently across almost all sectors of the ROA levels. economy. With the exception of aerospace and defense and health care services, all other industries in the economy Truly reversing this will require a profound shift in thinking exhibited a downward trend in ROA. This suggests that the and a strong grasp of the forces — often overlooked fundamental forces of the Big Shift are driving down Asset — facing modern firms. In particular, executives will Profitability across the entire economy. have to focus on capability leverage and mobilizing the Asset Profitability resources of others to deliver more value (the numerator 2 Of these industries, the technology, media, and in the profitability ratio) rather than just focusing on cost entertainment and automotive sectors have experienced reduction as a driver of firm profitability. the steepest declines in ROA, with ROA declining at an Updated Exhibit 89: Asset Base ($, trillions), U.S. Economy and Banking Industry, (1965-2010) Exhibit 90: Asset Base ($, Trillions), U.S. Economy and Banking Industry (1965-2010)

100

30 Size of Industry ($, Trillions)

0 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 Banking & Financial Institutions Other Industries Source: Compustat, Deloitte analysis

Source: Compustate, Deloitte Analysis

2011 Shift Index Measuring the forces of long-term change 121

Updated Exhibit 90: Return on Assets for the U.S. Economy, (1965-2010) Exhibit 91: ROA for the U.S. Economy (1965-2010)

7.00% 6.5%

6.00% 5.6%

5.00% 4.9%

3.8% 4.00% 4.2%

3.00%

2.0% 2.00% Return on Assets (%) 1.7% 1.00% 0.6% 0.00% 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010

-1.00% Economy ROA Economy less Banking ROA Linear (Economy ROA) Linear (Economy less Banking ROA) Source: Compustat, Deloitte analysis

Source: Data from Compustat, Deloitte analysis ... ROA for the U.S. economy has been in only consider the (higher) ROA exhibited in the ‘economy less banking’ chart, it is imprudent to isolate banking steady decline for the past 45 years. We believe completely from the story of declining ROA because the banking industry has provided capital to the rest of the that this decline in ROA has been driven by economy at a low cost over the past 25 years. The cost of companies’ inability to adapt to the long-term capital has steadily declined and it has allowed companies to pursue growth at a relatively low cost. While we might trends behind the Big Shift. be able to isolate the depressive effect of banking on overall ROA, it is imperative that we still consider it as part As we can see from Exhibit 90, the banking industry’s share of the overall economy because of this power to stimulate 90 © 2011 Deloitte Touche Tohmatsu of the total asset base has grown swiftly, from 30% in growth throughout the entire economy. 1965 to 60% in 2010. Consequently, the banking industry has been an increasingly important determinant of the From 2008-2010, we have seen an uptick in ROA for all overall economy’s ROA. Secondly, the banking industry has but three industries (aerospace and defense, energy, and had historically low levels of ROA, trending from 0.75% in life sciences).;While some may see this rise as a source 1965 and declining to 0.55% in 2010. for encouragement, we believe it to be the result of short-term measures, such as workforce reduction, rather Collectively, these factors yielded two key insights into the than fundamental restructuring of business strategies to economy’s decline in ROA. As we can see from Exhibit 91, address the Big Shift. In short, we do not believe that these the inclusion of the banking industry significantly lowers efforts to improve performance are sustainable in the the overall economy’s ROA consistently over the past 45 long run. For greater detail concerning our analysis of the years. More importantly, when the banking industry is relationship between layoffs and ROA, please refer to the excluded from our calculations, the overall economy’s ROA section “2011 Shift Index: Key Ideas.” experienced a slightly steeper decline. As evidenced by the trend lines in Exhibit 91, when we consider the rest of the economy apart from the banking industry, the rate of decline in ROA is even more severe. While it is tempting to

122 Tab Title Here Tab 2011 Impact Index

Retail Kings Struggle to Maintain Power n the 1950s, department store Lord and Taylor (L&T) was a beacon for American designers and the envy of U.S. retailers. Not only was it America’s oldest department store, L&T was also a fashion leader and the crown jewel of the Associated Dry Goods Corporation, which was formed in 1916. However, by 2003, L&T’s aggressive national expansion plans had led to the closure of 38% I 147 of its store base, and the company had to receive several cash infusions from its parent company, private equity group, National Realty Development Corporation (NRDC), in order to make its debt payments.148 What was driving this tumultuous change in L&T’s fortunes?

L&T’s struggles were reflective of the broader change which the Big Shift has wrought on the U.S. retail industry. The company is certainly not alone in its struggles — the recent demise of California retail chain Mervyn’s, and K-Mart’s Chapter 11 bankruptcy in 2001 point to components of the Big Shift which are making it increasingly tough for companies to maintain ROA. First, competition has become increasingly intense because of technology adoption in the industry. For example, K-Mart’s demise was largely driven by its inability to compete with Wal-Mart’s low-cost structure, which was developed, in part, by the use of technology to effectively manage inventory.149 Similarly, the role of technology is reflected in L&T’s struggle to tackle online retailing, in comparison to competitors like Nordstrom’s who have combined their physical and online merchandise to successfully drive online sales.150 Second, firm performance in the retail industry has become more volatile because of the opportunities and threats posed by capital availability in the economy. While Mervyn’s decline in California was largely driven by predatory moves by private equity investors,151 capital availability has had both positive and negative effects on L&T. On one hand, the growth in Competitive Intensity in the sector has undoubtedly been driven by the availability of capital funding both big box retailers (Wal-Mart) and online retailers (Amazon), but on the other hand, L&T’s buyout by private equity group NRDC has provided it with the capital needed to revitalize its operations.

While scale drove competition in the retail industry during the earlier half of last century, performance will increasingly be determined by how well retailers can capture flows of information and capital. Information asymmetry is fading, consumers become increasingly aware of the options available to them, and the 147 “Who Will Take Lord & Taylor’s Vacant Stores?”Retail Traffic, online shopping experience of e-tailers like Amazon has only improved. If traditional http://retailtrafficmag.com/ar/ retailers like L&T are to remain relevant in the marketplace, they need to improve retail_wholl_lord_taylors/ 148 “Lord & Taylor Gets $60M to Stay how they use flows both internally and externally — capital will have to be employed Afloat” New York Post, http:// to optimize inventory management, as well as effective online retailing strategies and www.nypost.com/p/news/business/ item_SauPKNwcDehqXGuCGExPiI customer engagement. 149 “K-mart’s Check Out Woes” The Economist, http://www.economist. com/node/948832 150 “Nordstrom Links Online Inventory to Real World” New York Times, http://www.nytimes. com/2010/08/24/business/24shop. html 151 “How Private Equities Strangled Mervyns” Bloomberg Business Week, http://www.businessweek. com/magazine/content/08_49/ b4111040876189_page_3.htm 2011 Shift Index Measuring the forces of long-term change 123 2011 Impact Index ROA Performance Gap

Winning companies are barely holding on, while losers experience rapidly deteriorating performance

Introduction surprising, however, is how little winners have gained The ROA Performance Economy-wide, ROA is declining as competition intensifies during the past 45 years. Technology has enabled firms to Gap metric measures and consumers and talented workers gain market power. leverage talent in new and innovative ways and cut costs the percentage Yet we all know averages can be deceiving. Maybe good from operations on an unprecedented scale, however, difference in ROA companies are generating high returns, but the losers are even top quartile performers have failed to convert these between the top and losing big and dragging down ROA? What is happening at advances into ROA gains.152 The ROA for the top quartile of bottom quartiles and the company level? firms has actually declined gradually over the past 45 years reflects how value flows (see Exhibit 92), from 12.7% in 1965 to 9.9% in 2010. to (or from) “winners” The ROA Performance Gap is meant to shed light on what and “losers” in an might otherwise be obscured by averages. Over time, this These findings corroborate the research of our colleagues, increasingly competitive metric will reveal trends in how value is distributed among Michael Raynor and Mumtaz Ahmed, in Deloitte’s environment. firms and quantify the true consequences of doing poorly Persistence Project.153 While ROA for the top 1% of firms or well in the Big Shift. has improved, ROA in the top decile firms has only held This metric is a proxy for steady over the past 45 years.154 Only a very small group of ROA Perf Gap 1 firm performance. Observations and Implications companies has succeeded in improving ROA. The ROA Performance Gap shows a bifurcation of winners and losers; this finding is by no means new. What is Updated Exhibit 91: Economy-wide ROA by quartile, (1965-2010) Exhibit 92: Economy-wide ROA by quartile (1965-2010)

20%

15% 12.7%

9.9% 10%

0% Top Quartile Linear (Top Quartile)

Return on Assets (%)ReturnAssetson 20% 1.3% 152 Source: Compustat, Deloitte 0% analysis. -9.9% 153 Deloitte’s Persistence Project was carried out to identify the manage- -20% ment practices that have most contributed to sustained, superior -40% corporate performance. Findings from this research were published -60% in a series of articles in 2010. 154 Raynor, Michael and Mumtaz Ahmed. “Survival of the -80% Fattest,” Deloitte Review. http:// www.deloitte.com/view/ -100% en_US/us/Insights/Browse-by- 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 Content-Type/deloitte-review/ bfeebb8fda426210VgnVC- M100000ba42f00aRCRD.htm Bottom Quartile Linear (Bottom Quartile) Source: Compustat, Deloitte analysis 124 Source: Data from Compustat, Deloitte analysis

While ROA in the top quartile firms has declined gradually, This accelerating deterioration among weak performers Title Here Tab 2011 Impact Index in the bottom quartile, weak performers are deteriorating and lack of ROA improvement in all, but the very best at an increasingly rapid pace. Over the same 45-year time performers aligns with our analysis of Firm Topple Rate.156 period, average ROA for companies in the bottom quartile While the financial rewards for successful companies dropped from 1.3% to -9.9%.155 The volatility in ROA have remained the same, it is increasingly difficult for has also increased for the bottom quartile of companies, companies to remain successful and capture these returns. ROA Perf Gap 2 with the greatest downward swing coming in during the This competitive reality plays out at the bottom of the recession of 2001. Clearly, the majority of companies are economic hierarchy, where the churn rate for the bottom averaging lower returns, and the gap between top and decile of firms is falling (see Exhibit 93). In other words, not bottom performers is widening. only are companies with the weakest ROA performance Updated Exhibit 92: Churn Rate for bottom decile firms, (1965-2006) Exhibit 93: Churn Rate for bottom decile firms (1965-2006)

85%

75%

65% 62%

55% Given Year

48%

% of FirmsNew to a Decile in a 45% 44% 44% ROA Perf Gap 3

35% 1967 1972 1977 1982 1987 1992 1997 2002 0-10th Decile Linear (0-10th Decile) Updated Source: Compustat, Deloitte analysis Exhibit 93: Asset vs. Net Income Growth Index, (1966-2010) Source:Exhibit Data from 94: Compustat, Asset vs.Deloitte Net analysis Income Growth Index (1966-2010)

140.0 129.30

120.0

100.0

80.0 85.4

60.0 46.34

40.0

0.0 1966 1970 1974 1978 1982 1986 1990 1994 1998 2002 2006 2010 Assetvs. Net Income Growth Index (1965=1.0) -20.0

155 Source: Compustat, Deloitte -40.0 analysis. Economy Assets Economy Net Income 156 See discussion of Firm Topple Rate Linear (Economy Assets) Linear (Economy Net Income)

Source: Compustat, Deloitte analysis 2011 Shift Index Measuring the forces of long-term change 125 Source: Data from Compustat, Deloitte analysis

Updated Exhibit 94: Top & Bottom Quartile Asset vs. Net Income Index, (1965-2010) Exhibit 95: Top & Bottom Quartile Asset vs. Net Income Index (1965-2010)

140.0 116.95 120.0

100.0

80.0 91.63

60.0

40.0

20.0

0.0 1966 1970 1974 1978 1982 1986 1990 1994 1998 2002 2006 2010

Top Quartile Assets Top Quartile Net Income

20.0 4.18 0.0 1966 1970 1974 1978 1982 1986 1990 1994 1998 2002 2006 2010 -20.0

Asset vs. Net Income Growth Index (1965=1.0) -32.76 -40.0

-60.0

-80.0

-100.0

-120.0

-140.0 Bottom Quartile Assets Bottom Quartile Net Income Source: Compustat, Deloitte analysis

Source: Data from Compustat, Deloitte analysis delivering ever-worse results, they are now more likely to practices.157 Not only is it difficult for companies to remain at the bottom than they were 45 years ago—once generate sustained ROA performance, but companies that in the bottom decile, companies do not move back out. are actually driving superior performance are rare. 94 © 2011 Deloitte Touche Tohmatsu The Persistence Project research in the monograph A Finally, the changing relationship between assets and Random Search for Excellence provides insight into the net income provides additional insight into the ROA management practices driving these trends. Looking at performance gap. Indexing both assets and net income the relative performance of firms from 1966 to 2006, against 1965 levels (see Exhibit 94), we see that, economy- companies were most likely to end each year in the wide, assets and income increased at the same rate same decile in which they started. By first quantifying the until 1980. From that point, the gap between the two likelihood of companies to achieve specific relative rankings began expanding, as companies added assets without a in terms of performance and then specifying cutoffs commensurate increase in profitability. beyond which outcomes are sufficiently unlikely to have been caused by luck alone, Raynor and Ahmed are able to Restricting that analysis to the top quartile of companies isolate for the impact that firm management practices have (see Exhibit 95), we see that net income growth tracked on performance. The study concluded that only 167 out of asset growth more closely, until 1992, when the gap 22,000 companies can reliably be said to have performed began widening as a result of the gradual decline in the in the top decile because of superior management ROA of the top firms. The picture could not be more

157 Raynor, Michael and Mumtaz Ahmed. “A Random Search for Excellence.” Deloitte Review.

126 Tab Title Here Tab 2011 Impact Index

different for the bottom quartile firms: While assets grew only marginally over the 45 years, income fell, decreasing Wal-Mart Embraces at an exponential rate until 2001. It remains at -32 times Scalable Learning the 1965 level. hile our ROA Performance Gap metric has shown that The ROA Performance Gap—and its underlying drivers— many companies are not using scalable learning in a have far-reaching implications for executives. A recent meaningful way, there is evidence of firms breaking the mold and creating significant value as a result. One article in the Harvard Business Review aptly describes the exampleW of this comes with Wal-Mart’s innovative supply chain partnership threat: “Just as a digital photo or a web-search algorithm with the Chinese firm, Li & Fung. can be endlessly replicated quickly and accurately by copying the underlying bits, a company’s unique business Wal-Mart’s approach to building its reputation and a loyal customer base processes can now be propagated with much higher has been to focus on providing value and selection to its customers. A fidelity across the organization by embedding them in core driver of Wal-Mart’s approach as it expands across the nation and enterprise IT. As a result, an innovator with a better way around the globe has been the efficiency of its supply chain. As a leader in of doing things can scale up with unprecedented speed this particular area, Wal-Mart has demonstrated a willingness to innovate to dominate an industry. In response, a rival can roll and stay ahead of the curve: In January 2010, the firm announced it was out further process innovations throughout its product entrusting Li & Fung, a Hong Kong-based company to provide sourcing lines and geographic markets to recapture market share. services for an estimated 2 billion dollars of products. By making this strategic investment, Wal-Mart has accessed the vast ecosystem of Li & Winners can win big and fast, but not necessarily for very 160 Fung’s supplier network to drive efficiency and performance improvement long.” in their sourcing. To survive in this new and constantly changing The Center for the Edge has studied and written on the ecosystems of Li environment, leaders must move beyond marginal cuts & Fung for several years. In the publication “Performance Ecosystems,” that offer diminishing returns and instead make smart the Center for the Edge team discusses the value of fostering existing long-range investments that will enable talent at every and joining new ecosystems. Applying this concept to supply chain, firms level to contribute knowledge and improve performance. can benefit tremendously by moving from a tightly controlled procuring The key success factor in the world of the Big Shift will be environment with few strategic partners to a dynamic system of many the organization’s ability to learn faster, to drive cumulative diverse suppliers, as Wal-Mart has done with Li & Fung.158 improvements in performance by working with others. The partnership was viewed favorably by market analysts who noted While most companies struggle to maintain profitability that the arrangement has the potential to help Wal-Mart lower cost, in the Big Shift, the best among them will still find ways improve inventory management, and product choice, predicting that to inspire confidence through sustained performance at a the volume of products sourced via Li & Fung will like grow substantially high level. “as the advantages become more obvious to WMT.”159 Historically, many firms considered supply chain efficiency to be predicated on marginal cost reduction. This partnership, however, reflects Wal-Mart’s willingness to embrace external established knowledge networks and enable contributions from talent both within and outside of the organization.

While the majority of firms are yet to tap into the potential of ecosystems, the partnership between Wal-Mart and Li & Fung is a telling example 158 John Hagel et all. “Performance of how firms can leverage knowledge flows enabled by performance Ecosystems — A decision ecosystems as a means to improve performance. framework to take performance to the next level.” Deloitte Publication, June, 2011. 159 Strasser, David and Sarang Vora, “Lower Costs/Lower Inventory = Higher Returns.” Janney Capital Markets, January 29, 2010. 160 Andrew McAfee and Erik Brynjolfsson, “Investing in IT That Makes a Competitive Difference," Harvard Business Review, July- August 2008: 98-107. 2011 Shift Index Measuring the forces of long-term change 127 2011 Impact Index Firm Topple Rate

Big companies are losing their leadership position at an increasing rate

Introduction learning and quick response strategies in order to compete. The Topple Rate metric This Shift Index describes a climate in which the value Those that are unable to adjust to these rapid shifts are tracks the rate at which captured by firms is deteriorating as reflected by declining increasingly susceptible to topple. big companies (with asset profitability and a widening gap between winning more than $100M in firms and losing firms. Neither of these metrics, however, The rate at which firms suffer a decline in ROA, relative to net sales) change ranks, quantifies the ability of individual firms to stay in the other firms, has trended upward since 1965 (see Exhibit defined in terms of their top tier of performance, even if overall performance is 96).161 Between 1965 and 2010, the topple rate for all ROA performance. declining. We know winners are worse off in terms of companies in the economy with more than $100M in net returns—but are they at least winning longer? Or is it sales increased almost 40%, as competition exposed low This metric is a proxy for increasingly difficult to develop a sustained advantage in performers and ate away at their returns. In recent years, the ability to sustain a the world of the Big Shift? The Topple Rate addresses these the topple rate has been more volatile. Firm topples spiked competitive advantage questions. as a result of the financial crisis in 2008 but returned to in the world of the Big the long-term trend in 2010. This volatility underscores the Shift. Of course, in a large, dynamic market such as the U.S. influence of macroeconomic events and economy-wide economy, one would expect companies to change ranks performance in the short-term, despite an overall trend often. The metric is normalized to account for the rank toward faster topples. changes that could be expected to occur randomly (zero indicates stability and relative ease for a firm to The rapid rate at which companies suffer declines in Firm Topple Rate sustain an advantage). The resulting topple rate metric ROA ranking reflects the rise in competitive intensity. This provides a strong and accurate indicator of changeability observation has also been validated in “Survival of the 1 and upheaval in the economy. As the pace of change Fattest,” an article by Deloitte colleagues Michael Raynor, accelerates, firms should consider how to leverage scalable Mumtaz Ahmed, and James Guszcza. Churn in the top Updated Exhibit 95: Economy-wide Firm Topple Rate, (1965-2010) Exhibit 96: Economy-wide Firm Topple Rate (1965-2010)

0.8

0.7

0.6 0.55

0.5 0.47 0.38 0.4

Firm Topple Rate 0.3 0.34

0.2

0.1

0.0 1965 1969 1973 1977 1981 1985 1989 1993 1997 2001 2005 2009

161 Thomas C. Powell and Ingo Topple Rate Linear (Topple Rate) Reinhardt, “Rank Friction: An Note: Ordinal Approach to Persistent 0: Ranks Perfectly Stable = Perfectly Sustainable Competitive Advantage Profitability,” Compustat, Deloitte Legend1: Ranks Change Randomly = Complete Absence of Sustained Competitive Advantage analysis. 0: Ranks Perfectly Stable = Perfectly Sustainable Competitive Advantage 128 1:Source: Ranks ChangeThomas Randomly C. Powell = andComplete Ingo AbsenceReinhardt, of Sustained“Rank Friction: Competitive An Ordinal Advantage Approach to Persistent Profitability,” Compustat, Deloitte analysis

Source: Thomas C. Powell and Ingo Reinhardt, “Rank Friction: An Ordinal Approach to Persistent Profitability,” Compustat, Deloitte analysis

Exhibit 96: Churn Rate in 90th-100th Decile, (1967-2006) Title Here Tab 2011 Impact Index Exhibit 97: Churn Rate in 90th-100th Decile (1967-2006)

75%

65%

55% 53%

45% 45% % of FirmsNew to a Decile in a Given Year 42% 41%

35% 1967 1970 1973 1976 1979 1982 1985 1988 1991 1994 1997 2000 2003 2006

Churn Rate 90-100th Decile Source: Compustat, Deloitte analysis Source: Compustat, Deloitte Analysis decile of ROA performers has increased over time (see “Between 1965 and 2010, the topple rate for Exhibit 97); that is, increasingly more of the companies in the top decile are new to that decile in a given year.162 This all companies in the economy with more than trend indicates that competition is increasing in the top strata of performers, making a firm’s time at the top all $100M in net sales increased almost 40%, as the more tenuous. At the same time, churn for the lowest competition exposed low performers and ate decile (0-10th percentile) has been declining, implying that fewer firms are performing poorly enough to sink away at their returns.” to the bottom, and those that do are experiencing long, drawn-out declines. In the automotive industry, imports have risen as a result 96 © 2011 Deloitte Touche Tohmatsu of consumer demand for hybrid and fuel-efficient cars in These findings tie closely with our findings in the recent times.163 Over the past five years, the topple rate Competitive Intensity metric. As discussed, the Herfindahl- within the industry has increased by 75%. While many Hirschmann Index (HHI) of market concentration has factors contribute to the topple rate, increased competition dropped by more than half since 1965, suggesting large and a lagging response to changing customer preferences increases in competitive intensity. In addition, as the have certainly helped unseat the domestic automotive world becomes more connected, foreign competitors firms. will continue to challenge domestic firms, creating more competition for established firms. With more The digital infrastructure also poses an opportunity- or competition than ever before, firms have shorter windows threat--for rapid change among firms. Foundational forces of opportunity to respond to change in the marketplace. such as increased internet usage and wireless activity have

162 Raynor, Michael, Mumtaz Ahmed and James Guszcza, “Survival of the Fattest”. Deloitte Review Issue 6, 2010. Pages 18-27. 163 Thormahlen, Casey. “Automobile Wholesaling in the U.S.” IBISWorld. April 2011. 2011 Shift Index Measuring the forces of long-term change 129 Tab2011 Impact Index Here Title

The Rise and Fall of Borders

n 2005, Borders was the second-largest book retailer in the world, with 1,329 locations, including outposts in Asia and the UK. In 2011, Borders declared bankruptcy and was liquidated.

Started as Borders Group in 1971 by Tom and Louis Borders during graduate school at the University of Michigan and acquiredI by K-Mart in 1992 to form the Borders-Waldon Group, Borders story is one of great success and rapid demise. It is tempting to explain away Borders’ bankruptcy as death by internet age, something that was inevitable. However, the company’s 2000 annual report offers a better clue: “Our online investment will be channeled to support our in-store platform… We have targeted loss reduction as a major goal in this area.”164 Borders counted on its historically loyal customer base and bricks-and-mortar success and made a strategic decision not to pursue opportunities in the emerging digital infrastructure aggressively as an independent business opportunity.

Between 2001 and 2008, Borders failed to develop its own online storefront, effectively allowing competitors to eat in to their customer base as e-commerce exploded. As the ecosystem was rapidly changing, competitor Barnes and Noble invested in e-readers and digital content, while Borders expanded retail locations, signing costly 15-20 year leases and missing the lucrative e-reader market. By May 2010 when Borders introduced its own e-reader, the Kobo, it was too late: Border’s bankruptcy filing listed $1.29 billion in debt on $1.27 billion in underlying assets.

fundamentally changed the way customers interact with are unable to tap into foundational forces are increasingly companies allowing companies to identify and respond susceptible to market topple. to customer needs more quickly and effectively and with innovative solutions. Consider Apple’s introduction of the Companies face more difficulties than ever before. iPod in 2001. In the mid 1980s, Apple suffered a topple Competition is increasing both domestically and abroad, that left it on the brink of failure through much of the while brand loyalty among consumers is decreasing. 1990s. The visionary firm, however, was able to change The rapid changes in the digital infrastructure present course to exploit the rapidly changing digital infrastructure opportunities, but firms have a very short time frame to and shape a new paradigm for delivery and consumption capitalize on them; those that do not are likely to fall to the of media. The iPod and iTunes music store were possible wayside. The quickening turnover of industry leadership because of the proliferation of internet usage and a underscores the need for firms to consider how to become fundamental shift in how consumers interacted with more flexible and to increase the rate at which they learn devices. While the digital infrastructure can enable firms to and innovate. improve their position in the marketplace, those firms that

164 Annie Lowrey, “Readers Without Borders”, Slate July 2011 < http:// www.slate.com/id/2299642/> 130 Shareholder Value Gap Tab Title Here Tab 2011 Impact Index Shareholder returns for market “winners” increase at a modest rate; while “losers” destroy more value than ever before

Introduction value is our strategy.’ That's not a strategy you can touch… The trends discussed so far have a profound impact increasing the value of your company in both the short The Shareholder on financial markets. Stock prices, which are based on and long term is an outcome of the implementation of Value Gap metric investors’ expectations of future returns, take a longer successful strategies.”165 In the backlash against short- is a measure of the view than the current income statement, but often do a termism, an increasing number of companies, from Google difference between poor job of representing firm performance. At the same to GE itself, no longer report quarterly earnings estimates. the top-quartile and time, because boards focus on stock prices, they are Practical considerations have also contributed to this shift: bottom-quartile uniquely positioned to quantify the value of acting on Big Lack of visibility into future earnings makes short-term of returns to Shift trends or the risks of ignoring them. Thus, however projections virtually impossible, while many companies still shareholders, which erratic, the behavior of the stock market and how it treats have faith in long-term profit growth.166 incorporates share “winners” and “losers” is an indicator of the perceived risks price appreciation and and opportunities related to the Big Shift trends. Markets can be fickle in their evaluation of firms, predicting dividends. false positives or negatives based on forecasts for an Shareholder value as a measure of firm performance unknown future. However, as a function of investors’ This metric is a proxy became popular in the 1980s, spurred by then-CEO Jack expectations of future performance,167 shareholder returns for the increasing Welch of GE. In a 1981 speech entitled, “Growing fast in can serve as a suggestive proxy of public opinion over bifurcation of winning a slow-growth economy,” Welch touted aggressive short- the long run for both high and low performing firms. By companies and losing term gains and beating quarterly targets as the principal looking at trends in the total returns of each group over companies. strategies for GE and all other successful firms. Critics of time, we can gauge how investors reward companies that this “short-termism” strategy argue that companies have beat expectations and punish those that do not. More grown too beholden to shareholders and the marketplace; importantly, we can measure how well these expectations this argument has largely prevailed, particularly in the wake truly reflect the realities of corporate performance. of the 2008 financial crisis. Indeed, even Welch concedes that, “you would never tell your employees, ’Shareholder

165 “Jack Welch Elaborates: Shareholder Value”, Businessweek, March 2009. < http://www. businessweek.com/bwdaily/ dnflash/content/mar2009/ db20090316_630496.htm> 166 “Shareholder Value: Time for a Longer View?”, Businessweek, March 2009 < http://www.businessweek.com/investor/content/ mar2009/pi20090317_247202_ page_3.htm> 167 Raynor, Michael, Mumtaz Ahmed, and Andrew Henderson. “A Random Search for Excellence”. Deloitte Publication.

2011 Shift Index Measuring the forces of long-term change 131 2011 Impact Index Shareholder Value Gap 1

Exhibit 97: Weighted average Total Returns to Shareholders by quartile, (1965-2010) Updated Exhibit 98: Weighted Average Total Returns to Shareholders by quartile (1965-2010) 250%

200%

150%

100% 67%

50% 69%

0% 1965 1969 1973 1977 1981 1985 1989 1993 1997 2001 2005 2009 Top Quartile Linear (Top Quartile)

0% -22.1% -20%

-40% -19.1%

WeightedAverage Total Returns to Shareholders (%) -42.6% -60%

-80%

-100% 1965 1969 1973 1977 1981 1985 1989 1993 1997 2001 2005 2009

Bottom Quartile Linear (Bottom Quartile) Source: Compustat, Deloitte analysis

Source: Compustat, Deloitte analysis

Observations and Implications Today, the cost to shareholders of holding the lowest Despite volatility year-to-year, over the long term, the performing firms is double what it was 40 years ago. This upper quartile of firms—the “winners”—have only very suggests that the financial markets perceive the bottom tier slightly managed to increase the rate at which they create of companies to be destroying value more than before and value for their shareholders (see Exhibit 98).168 This is that it will be difficult for underperformers to overcome consistent with our finding that the economic performance this perception. (measured by ROA) of these companies has been relatively 97flat. This also supports the notion that short-termism These trends highlight the inherent difficulty of increasing © 2011 Deloitte Touche Tohmatsu may be just that and trends experienced in three-month shareholder value over time, even for top-performing increments are not guaranteed to play out over time. companies. Although firms in the bottom quartile are Another phenomenon at play for consistently high trending down, there is no commensurate uptick in top-tier performers is that the market has come to expect such firms. There have been, of course, superstar firms that performance from them, and fails to reward it—meeting have experienced sustained growth, but this trend has not expectations is no longer enough. As such, a firm may played out on a macro level. In aggregate, there appears to continue to perform well without seeing an equivalent rise be declining share holder value, a phenomenon consistent in shareholder value. with our ROA analysis.

At the same time, the bottom quartile—the “losers” — are losing ground. Since 1965, the bottom quartile firms’ returns to shareholder have tracked their ROA performance by destroying increasing amounts of shareholder value.

168 Source: Compustat, Deloitte analysis.

132 Tab Title Here Tab 2011 Impact Index

In a market captivated by short-term movements, the long-term polarization of returns has powerful implications New Standards for Success for executives. Not only are current business strategies less and less effective, but investors are recognizing this al-Mart is incontrovertibly one of the most successful in their diminished expectations regarding companies’ firms in America, topping the Fortune 500 list eight times in the past decade and posting revenue of almost long-term performance. Taken with the downward trend 430 billion dollars in 2010.169 The firm has achieved an in ROA, this is not surprising; it suggests that, rather unprecedentedW scale and is the largest private employer in the world, with than simply trying to tell a more compelling “story” to over 2 million employees nationwide. At the turn of the millennium, the the investment community, the answer is more likely to stock was valued at over $50 per share and it has hovered around that involve fundamental shifts in strategies and operational point ever since. performance.

Has Wal-Mart stopped growing or stumbled operationally? Hardly. A tangential—but relevant—implication of these trends is Wal-Mart is the rare company that has consistently delivered excellent that it will likely only become more and more difficult to performance throughout its existence. meet investor expectations as competition puts pressure on shareholder returns. Executives must be increasingly From 1975-2000, Wal-Mart’s stock price mirrored its impressive trajectory, starting from mere pennies and growing at a 38% CAGR. In 1997, wary of this dynamic; as we discuss later, turnover in their Wal-Mart’s earnings surpassed 100 billion dollars, and the firm continued ranks is increasing. expanding globally, entering the European marketplace with the acquisition of the 21-unit Wertkauf hypermarket chain in Germany. As the company surpassed shareholder expectations yet again, the stock grew accordingly, as investors projected great things for the company’s future. This sustained growth and market power has placed Wal-Mart in a league of operational performance that few, if any, U.S. firms have reached in recent history. So why, in the past decade, has Wal-Mart’s stock price not risen with its impressive growth? The answer, it seems, has to do with expectations. By 2000, the expectations of investors had finally caught up with the performance of the firm. In a time when investors have become accustomed to rapid growth and change and receive a constant stream of information adjusting their expectations, it is difficult to deliver results that will be rewarded by the market. Holding steady can seem uninteresting and just meeting expectations is no longer enough.

169 “Fortune 500”. Fortune. May 23, 2011. < http://money. cnn.com/magazines/fortune/ fortune500/2011/full_list/> 2011 Shift Index Measuring the forces of long-term change 133 2011 Impact Index Consumer Power

Greater access to information and choices boost Consumer Power

Introduction certain retailers and can exercise greater discretion in their The Consumer Power Relations between vendors and consumers are changing purchasing decisions. metric measures the profoundly as product choices expand and consumers value captured by have increased access to information about these choices. Not only do consumers have more options — and consumers based on Vendors once had the upper hand, but in the world of the more convenient access to them — but increased the degree to which Big Shift, consumers are gaining power back. communication among consumers gives rise to more consumers perceive power. “Crowd clout” is defined as “an online grouping of they have choices, Consumer power stems from different sources, including citizens/consumers for a specific cause, be it political, civic convenient access to increased choices, lower switching costs and easier access or commercial.” The aim of crowd clout can be anything and information about to product information. The transparency of information from challenging politicians to putting pressure on those choices, access to empowers customers to make more informed decisions suppliers to offer discounts.171 The impact of crowd clout customized offerings, the and compare alternatives more easily. The internet and, can be seen in the abundance of forums and communities ability to avoid marketing more recently mobile applications, give consumers access for consumers, particularly those looking to save money. efforts, and minimal to price comparisons, customer reviews, and more. In what On these sites, customers post coupons and coupon switching costs. Wal-Mart stores’ Chief Executive, Mike Duke, calls “a new codes from in-store and online retailers and even discuss era of price transparency,” stores are losing the advantage when certain items go on sale and strategies for obtaining This measure proxies over customers as shoppers are more inclined to perform greater savings. the relationship and due diligence, either beforehand or in the store itself.170 relative power between The final element of consumer power is the ability to avoid consumers and vendors. For customers in this newly integrated world, switching marketing messages. Technology has armed consumers Consumer Power costs are low, often requiring only the click of a mouse. with more control over what they see and what they can With remote transactions made possible by the internet easily avoid. For example, the increasing popularity of 1 and mobile browsing, consumers can buy products and digital video recorders and online streaming of content services from nearly anywhere, at any time. This means allows viewers to control their exposure to advertisements that consumers are no longer limited by proximity to and other marketing material. Updated Exhibit 98: Consumer Power, (2011) Exhibit 99: Consumer Power (2011)

Strongly Disagree Strongly Agree 1 2 3 4 5 6 7 Top 2 There are a lot more choices now in this category 1 than there used to be 3% 3% 7% 26% 20% 20% 21% 41% 2 I have convenient access to choices in this category 16% 12% 12% 20% 16% 12% 12% 24% There is a lot of information about brands in this 3 category 3% 3% 5% 21% 19% 22% 27% 49% 4 It is easy for me to avoid marketing efforts 7% 5% 10% 26% 16% 17% 18% 35% 170 Bustillo, Miguel and Ann I have access to customized offerings in this Zimmerman. “Phone-Wielding 5 Shoppers Strike Fear Into Retailers”. category 9% 7% 9% 27% 17% 16% 15% 31% Wall Street Journal December 15, There is not much cost associated with switching 2010. < http://online.wsj.com/ 6 article/SB10001424052748704694 away from this brand 4% 3% 5% 20% 21% 23% 24% 47% 004576019691769574496.html> 171 “Crowd Clout,” Trendwatching, http://trendwatching.com/trends/ Source: Synovate, Deloitte analysis crowdclout.htm (created April 2007). Source: Synovate, Deloitte analysis 134

Updated Consumer Power Exhibit 99: Consumer Power by category, (2011 ) Exhibit 100: Consumer Power by category (2011)

Consumer Category 2011 2010 2009 Search Engine 71.6 68.7 70.9 Computer 71.7 68.6 68.0 Home Entertainment 70.1 68.1 69.1 Tab Title Here Tab 2011 Impact Index Restaurant 71.4 68.0 69.7 Insurance (Home/Auto) 70.4 67.3 68.4 Athletic Shoe 69.4 67.2 66.8 Hotel 72.4 67.1 68.8 Broadcast TV News 69.4 66.8 70.2 Banking 69.4 66.6 70.1 Snack Chip 68.4 66.6 70.7 Gaming System 67.1 65.6 62.5 Wireless Carrier 69.4 65.6 65.6 Household Cleaner 66.8 65.3 65.9 Pain Reliever 69.3 65.1 69.0 Investment 67.3 64.8 65.8 Department Store 65.9 64.7 66.3 Magazine 70.9 64.5 68.8 Soft Drink 66.2 64.4 69.5 Automobile Manufacturer 68.4 64.4 67.3 Airline 65.0 63.2 65.4 Grocery Store 66.1 62.8 65.5 Mass Retailer 65.4 62.0 65.9 Gas Station 61.7 61.3 61.6 Shipping 62.1 59.1 61.3 Cable/Satellite TV 60.9 59.1 63.1 Newspaper 56.3 54.0 54.0

Source: Synovate, Deloitte analysis

Source: Synovate, Deloitte analysis Observations and Implications location-specific offers from sites, such as Groupon and The overall Consumer Power score has been relatively high, Living Social, have become exceptionally popular this year, growing from 65 in 2008, when the survey began, to 67.5 reflecting a rapid shift toward more customized offerings. 99 © 2011 Deloitte Touche Tohmatsu in 2011. The true value of this measure, however, is in The digital infrastructure will continue to drive consumer analyzing the trends for individual categories. power, increasing not only the number of choices, but also access to and information about these choices. Across all consumer categories, almost 50% of respondents strongly agreed that they had more choices than before As interesting as the overall numbers are, the absolute and also had more information about those choices (see and relative responses to each consumer category provide Exhibits 99 and 100). Access to choices and customized deeper insight into changes in competitive pressures and offerings were the lowest contributors to overall Consumer consumer preferences. The data shows high consumer Power. However, as social media and other online outlets power (a score greater than 60) in most categories with reflect more and more of our interests and preferences, we the exception of Newspapers, a category in which options expect customized offerings to become more sophisticated are limited. While there are many alternative digital options and applicable. Firms, such as American Express, for for news, those who still prefer paper are usually limited to example, are starting to offer customized discounts a few local options and just as few national options. 172 Kopecki, Dawn “AmEx Facebook to customers who allow them access to relationships, Page Lets Users Get Customized 172 Discounts, Offers”. Bloomberg. “Liked” pages, and interests on Facebook. Similarly, July 19,2011. < http://www. bloomberg.com/news/2011-07-19/ amex-facebook-page-lets-users- get-customized-discounts-offers. html> 2011 Shift Index Measuring the forces of long-term change 135 Tab2011 Impact Index Here Title Black Friday

rightly-clad shoppers race down the aisles of a supermarket, grabbing cereal and laundry detergent in a mad dash to fill their carts. This image from the popular game show, Supermarket Sweep, entertained a few generations of America’s shopping-obsessed TV audience. In real life, the same craze, complete with careening carts and ferocious competition, grips shoppers every year on “Black Friday,” the day after Thanksgiving which Bhas become the busiest shopping day of the year. In 2010, 212 million people spent over $45 billion at stores and Web sites over the Black Friday weekend.173 However, unlike the contestants on Supermarket Sweep who cannot see the prices on the products they grab, last year’s Black Friday customers were not shopping blind. Customers were armed with complete product lists, prices, and even floor plans to compete for the best deals. In 2010, applications from Web sites, such as fatwallet.com, allowed customers to access a full range of leaked coupons, while the Mall Maps Mobile application helped guide customers through the throngs of shoppers. The impact has been staggering: on Black Friday, 2009, mobile site traffic accounted for just 0.1% of visits to retail Web sites. This increased 50-fold in 2010 to 5.6%.174 Smartphone users are not the only ones using devices to gain price transparency. Amazon’s TextBuyIt, an SMS messaging service, has mobilized pricing information to everyone with a cellphone, enabling the average consumer to make quick product and pricing comparisons in the palm of their hand.

To cater to the crowd-averse shopper, many retailers have begun offering the same deals online that they have in store. The response in recent years has been a large shift toward online purchase; nearly one-third of the weekend’s customers decided to navigate the sales in the comfort of their pajamas at home. These customers have even more information at their fingertips and can compare not only prices, but also delivery time, customer reviews, and return policies without leaving their living rooms.

In most categories, perceived Consumer Power. increased had a negative impact which is only now dissipating. this year over previous years. Hotels, wireless carriers and Between 2009 and 2010, survey respondents indicated computers had the biggest increases in Consumer Power. that their perception of Consumer Power in most The 5% increase in Consumer Power in the hotel industry categories did not change or actually decreased. Compared was driven by greater choice as well as more information with 2010, consumers in 2011 cited lower switching costs about options. The travel industry, and in particular the as a key driver of increased Consumer Power. We believe hotel industry, has been fundamentally altered by the a long-term trend will emerge showing greater Consumer growing digital infrastructure. Consumers can easily search Power, as this survey incorporates the coming years. for hotels online or via smartphone applications and can easily access detailed information and find more options While most industries experienced an increase in Consumer than ever before. Power. soft drinks, cable/satellite TV, and snack chips have shown the largest decline since 2009. For cable/satellite With regard to wireless carriers, consumers feel that TV, consumers cited a dearth of accessible options as the options, convenient access, and information have all primary detractor. Many consumers are limited to one improved. As different tiers of service become available or two local providers of cable TV, making it difficult to (e.g, prepaid wireless service)175, customers have a greater exert power in this particular industry. This may not reflect variety of options. This increase in options has also come the full story. Consumers today increasingly receive their with more information to help customers make decisions news and entertainment via other mediums, primarily that best fit their needs. the internet.176 While consumers have found ways to circumvent the constraints in this category, the Consumer The year-over-year changes are interesting as well, Power score itself does not reflect access to these other although we are more interested in the long-term options.

173 http://www.nrf.com/modules. trajectory. External forces can cause year-to-year php?name=News&op=viewlive&sp_ fluctuations in many categories; the financial crisis clearly id=1043 174 Bustillo, Miguel and Ann Zimmerman. “Phone-Wielding Shoppers Strike Fear Into Retailers”. Wall Street Journal December 15, 2010. < http://online. wsj.com/ article/SB10001424052748704 694004576019691769574496.html> 175 For more information, see the Wireless Subscriptions metric. 176 “The State of the News Media Annual Report 2011.” Pew Research Center. March 14, 2011.

136 Tab Title Here Tab 2011 Impact Index Lack of convenient access to choices or customized With more complete and transparent offers contributed to a 3% drop in the Consumer Power score for soft drinks and a similar drop for snack chips. information, customers have greater control In these low-cost, brand-loyal categories,177 consumers feel relatively constrained to their favorite brand. While over not only how they shop (in store or online) consumers have many options, it is inconvenient (or but also what they pay. unsavory) to switch to a less-preferred brand. Similarly, the commoditized nature of these goods means that De-emphasizing traditional marketing efforts may help consumers have limited ability to customize to their specific companies capture the attention of consumers, but that tastes. may not be enough. In the marketing world, consumer demands are creating a shift in the way companies engage The trend toward greater consumer power has significant with them, one in which companies will no longer succeed implications for executives. In particular, consumer power by trying to isolate consumers and limit their choices. provides a foundation, and an outlet, for Brand Disloyalty, They will need to look instead for ways to help consumers especially if vendors are slow to respond to evolving make the most of their newfound power; for instance, customer needs and behaviors. The proliferation of the helping them connect to the information they need and digital infrastructure has allowed customers to push back to other vendors that might help them. This suggests on vendors in different ways. With more complete and that companies must rethink the role of solely providing transparent information, customers have greater control content. By giving customers complete and honest over not only how they shop (in store or online), but also information, as well transparent access to alternative what they pay. With this power, consumers can switch solutions that may better serve their needs, companies can between brands more readily and explore all purchase build trust with their customers that will provide companies options. Indeed, as switching costs decline, it becomes with long-term returns and increased loyalty. apparent that, in many categories, consumers feel that sticking with a particular brand is no longer particularly enticing.

177 For more information on Consumer Power and Brand Disloyalty, see the Brand Disloyalty metric. 2011 Shift Index Measuring the forces of long-term change 137 2011 Impact Index Brand Disloyalty

Brand Disloyalty Brand Disloyalty is increasing among consumers, 1 particularly the younger generation Updated Exhibit 100: Brand disloyalty by age group, (2011) Exhibit 101: Brand Disloyalty by age group (2011) The Brand Disloyalty 70.0 metric is another 68.5 measure of value captured by consumers 65.0 as a result of increased consumer power and a generational shift 60.0 in reliance on brands stemming from the Big 55.0 Shift.

This metric is a proxy 50.0 based on survey Brand Disloyalty Index Value responses to a set 48.0 of questions testing 45.0 various aspects of brand disloyalty and brand 40.0 “agnosticism.” 15-20 21-25 26-30 31-35 36-40 41-45 46-50 51-55 56-60 61-65 66-70 71-75 76-80 81-85 85- Age Group Source: Synovate, Deloitte analysis Source: Synovate, Deloitte analysis

Introduction cachet and changing notion of brand in the Big Shift will Brand loyalty is on the decline. Consumers today are challenge companies that have crafted their strategies and inundated with more brands than ever before. The average operations around building and reinforcing brand. supermarket in 2010 carried 38,719 stock-keeping units (SKUs), a drastic increase over prior decades.178 Consumers Observations and Implications also now have access to information from more trusted Brand Disloyalty is inversely related to age: Younger sources to evaluate brands and their purchase choices no consumers are less loyal to brands than older consumers longer rely solely on advertising claims. (see Exhibit 101). Younger consumers, born in the internet era, generally rely less on brand names as an indicator While established authorities, such as J.D. Power and of product reliability, turning instead to the internet 100 © 2011 Deloitte Touche Tohmatsu Associates and Consumer Reports still influence consumers, for product and service information, user reviews and a plethora of consumer-driven Web sites are gaining feedback, as well as substitutes. Older consumers have power. This increased availability of information has also historically relied on “tried and true” brand names and changed the landscape of trust. The 2011 Edelman’s consumer product assessment agencies in the absence of 178 “Supermarket Facts” Food Marketing Institute Trust Barometer Report found that in the United States, other forms of reliable, published information. < http://www.fmi.org/ consumer trust has declined; in 2011, 46% of those facts_figs/?fuseaction=superfact> 179 Respondents were posed the surveyed trusted business versus 59% in 2008.179 As a The overall Brand Disloyalty score for 2011 is 60.8, question “How much do you trust business to do what is right?” result, consumers increasingly seek alternate sources of indicating a relatively high Brand Disloyalty across all 2011 Edelman Trust Barometer, product information, rather than buying into branding and categories, however, this metric is most valuable for Edelman, January 2011< http:// www.edelman.com/trust/2011/ marketing pushed from the company. The loss of brand analyzing the trend in individual categories. uploads/Edelman%20Trust%20 Barometer%20Global%20Deck. pdf>

138 Brand Disloyalty 2

Brand Disloyalty Updated Exhibit 101: Brand Disloyalty by category, (2011) Exhibit 102: Brand Disloyalty by category (2011)

Consumer Category 2011 2010 2009 Airline 75.9 75.3 69.9 Tab Title Here Tab 2011 Impact Index Hotel 72.6 68.3 70.1 Department Store 68.7 67.4 65.9 Home Entertainment 70.2 67.2 69.0 Grocery Store 68.4 65.3 63.6 Mass Retailer 69.4 65.0 68.0 Gas Station 63.9 64.0 59.5 Shipping 66.1 63.6 60.0 Athletic Shoe 61.9 62.3 57.2 Computer 67.8 62.0 61.7 Cable/Satellite TV 63.9 61.4 61.4 Restaurant 63.4 61.0 58.5 Automobile Manufacturer 65.3 59.5 62.7 Gaming System 58.3 59.5 55.3 Wireless Carrier 62.2 59.0 56.5 Household Cleaner 59.7 55.2 54.5 Search Engine 52.8 54.2 53.4 Insurance (Home/Auto) 60.4 54.1 57.8 Pain Reliever 56.0 53.9 51.4 Snack Chip 56.8 52.8 51.5 Broadcast TV News 50.6 52.1 49.4 Brand Disloyalty Banking 52.2 50.9 54.6 Magazine 53.6 49.7 45.2 3 Investment 60.6 49.0 53.3 Soft Drink 45.0 44.1 40.9 Newspaper 45.2 41.0 42.3 Updated Source: Synovate, Deloitte analysis ExhibitSource: Synovate, 102: Consumer Deloitte analysis Power and Brand Disloyalty, (2011) Exhibit 103: Consumer Power and Brand Disloyalty (2011)

Search Engine 71.6 52.8 Magazine 70.9 53.6

Mass Retailer 65.4 69.4 Airline 65.0 75.9

Newspaper 65.4 69.4

High Low

Source: Bureau of Labor Statistics, Richard Florida's "The Rise of the Creative Class“, Deloitte analysis Source: Synovate, Deloitte analysis 2011 Shift Index Measuring the forces of long-term change 139

Brought to you by ______?

family gathers in their dining room for dinner. The camera closes in as the pig-tailed daughter brings a steaming spoonful of chicken noodle soup to her mouth and recites the company tagline. This $3M dollar ad hopes to get viewers to make a brand connection that transitions from the Super Bowl couch to the supermarket cart. However, once today’s price-conscious consumers get to the store, many of them are as likely to purchase the Aunbranded product that looks and feels almost the same. Generic store brands are not new: They gained traction in American shopping carts in the inflationary 1970s and benefitted from a focus on improved quality in the 1990s. But the sales growth of these substitutes in recent years is unprecedented. In 2010, branded food sales were up 1%, while private label sales were up almost twice that amount at 1.7%.180 Today, one in four items purchased on an average store trip is a generic.181 As brand companies push more SKUs to the shelf, private labels act as fast-followers, piggy-backing off the marketing dollars spent by big brands and banking on increasingly disloyal consumers to choose with their pocketbooks rather than nostalgia. In a tight economy, shoppers complied, shedding branded products in favor of generics. The shift toward private label seems to be permanent: 88% of shoppers globally said they intend to keep buying private labels even after the economy improves.182 Today’s shoppers are more willing to embrace unbranded soup as a viable, and appealing, substitute.

Among the categories included in the survey, disloyalty Although consumers are disloyal in both categories, the was highest in hotels, airlines, and home entertainment. perceived Consumer Power differs between the two. Scores were lower (indicating greater brand loyalty) in the Consumer Power is high for hotels, driven primarily soft drink, newspaper, and broadcast TV news categories. by the accessibility of information and many different Consumers seemed to be less loyal to brands in higher interchangeable options. When shopping for flights, cost occasional purchase categories than with low-cost however, consumers have relatively fewer choices and purchases. Consumers were most likely to agree with customized offerings despite being able to compare flight the statement (I would) “compare prices of this brand to options easily. other brands” for hotels, airlines, and home entertainment and least likely to agree for soft drinks, newspapers, In the home entertainment category, consumers have and broadcast TV news. While this price sensitivity is both high power and high disloyalty. An increase in not absolute (computers, for example, have a relatively quality across the board has made home entertainment low Brand Disloyalty score despite a high price tag), the products harder to differentiate. With a narrowing gap economic climate has contributed to increasing consumer between high- and low-end brands and a wealth of wariness for large expenditures, hence greater Brand information available to potential customers, consumers Disloyalty in high-cost categories. have less incentive to choose a brand based on a previously trustworthy name.186 Accessibility of pricing and Comparing Brand Disloyalty and Consumer Power183 scores information is the greatest contributor to consumer power for some categories offers additional insights (see Exhibit in this category. 180 The Global Staying Power of Private 103). In general, one might expect a positive correlation Labels,” Nielsen and Co. August, 2010. 181 “Store Brand Growth: The While in some categories, gains in consumer power have differentiation. In 2011, the soft drink industry had the Trend Continues.” Private Label Manufacturers Assn. March, 2011 been matched by decreasing loyalty to brands, it does not lowest Brand Disloyalty score. A telling example of brand < http://plma.com/storeBrands/sbt10. hold true in all categories. loyalty in soft drink’s is the backlash experienced by the html> 182 Ibid. iconic brand, Coca-Cola, in 1985 when they attempted to 183 For further information, see the Consumer Power metric. The travel industry, in particular, has been impacted by introduce “New Coke,” a reformulation and rebranding 184 Harteveldt, Henry and Elizabeth greater Brand Disloyalty, with both the hotel and airline of their classic product. After the poor reception by the Stark. “Travelers are Cashing in on Loyalty Programs” Forrester Research categories scoring high Brand Disloyalty in 2011. Despite a American public, Coca-Cola reintroduced their original November 16, 2009“ 184 185 Noel, Josh. “Hotel Brand Loyalty reported 52% of travelers using travel loyalty programs, formula under the apt descriptor, “Coca-Cola Classic.” Dives” Chicago Tribune, November disloyalty for both airlines and hotels has increased Coca-Cola’s experience illustrates how, in brand-loyal 16, 2010. down from 59% a year ago.185 and do not wish to deviate from their preferred brand 186 Surowiecki, James, “The Decline of Brands,” Wired 12, no. 11 (2004) experience.

140 Tab Title Here Tab 2011 Impact Index Newspapers and broadcast TV news also have relatively Younger consumers, born in the internet low disloyalty scores, however, for the changing media industry, these low scores only tell part of the story. era, generally rely less on brand names as Consumers have typically been constrained to limited, location-based options for newspapers and broadcast an indicator of product reliability, turning TV news and have tended to display “stickiness” to instead to the internet for product and service their choices, resulting in relatively low disloyalty. More and more, however, consumers are overcoming these information, user reviews and feedback, as well constraints by using the digital infrastructure to access news sources. According to a Pew Project study, over 40% as substitutes. of Americans consume the majority of their news online; among 18- to 29-year olds, 65% cited the internet as their a generation ago. With more transparent information primary source of news.187 Because the Brand Disloyalty regarding the contents, quality, and price of products, metric focuses on competition and brand dilution within consumers are able to make more informed decisions. a category, it says nothing about the broader movement Their perceptions about alternatives are also changing. For away from print to digital media—low disloyalty offers established brands, it signals an increasingly competitive little help for a category that is shrinking. environment. For new brands, it offers an opportunity to capture market share faster with fewer marketing dollars. Some categories have low disloyalty despite high consumer power. In particular, customers for magazines and search For marketers, one implication may be that the notion of engines report having many options in these categories yet the brand needs to change. The core brand promise may maintain strong brand preferences.188 Whether consumer need to focus less on the features of a product or service loyalty will withstand the proliferation of choices, especially and more on establishing trust that the provider can as more personalized choices become available, remains configure products and services to meet individual needs. to be seen. In the case of magazines, there may be other Companies should consider integrating consumers’ voices forces at work that go uncaptured by the metric. While more fully into the product life cycle — from determining consumers who enjoy magazines in print may remain loyal which products and services are most valued to building to a brand, the rise of digital options poses significant grassroots, trusted validation of products and services — competition for print magazines as a whole. using the power of the digital infrastructure to build scalable trust-based relationships. The trend toward Brand Disloyalty has significant implications for companies. Not only are consumers more price-sensitive, brands do not carry the clout they did just

187 “The State of the News Media 2011” Pew Research Center’s Project for Excellence in Journalism (2011) 188 Customers, on average, strongly agreed with the statement “I have a strong preference for the brand I use” in both the Search Engine and Magazine categories. 2011 Shift Index Measuring the forces of long-term change 141 2011 Impact Index Returns to Talent

Talented workers garner higher compensation and market power as their value and career options expand

Introduction also increasingly must react to the fast-moving and The Returns to Talent As tangible assets play a smaller role in generating unpredictable circumstances that characterize the Big Shift. metric measures the revenues and profits for U.S. companies, the so-called In this era of unprecedented innovation and disruption, gap in fully loaded “creative” workers are increasingly important.189 These new, interfirm, organizational forms are emerging.193 compensation (including workers garner higher returns than other workforce classes These distributed “creation networks,” together with the health insurance, other and wield growing power relative to the firms that employ geographic concentrations of talent we call “spikes,”194 benefits and bonuses) them. are where creative class workers connect to amplify and between “creative” accelerate their learning and performance. professions and other As defined by Richard Florida, the creative class is made up professions. It is based on of workers whose job is to create meaningful new forms, Observations and Implications examining annual mean and whose work is knowledge intensive or whose work is For the last seven years, the compensation gap between compensation across a broadly relevant and transferable.190 Florida categorized the the creative class and the rest of the workforce has range of occupational Bureau of Labor Statistic’s occupational classifications191 widened across the U.S. labor market (see Exhibit 104). The groupings. into five classes: super-creative core, creative, working, gap has increased at a 4% annual growth rate during this service, and agriculture. For our analysis, we aggregated time. This metric is a proxy for the five classes into the creative class and the other the value captured by workforce class.192 The Returns to Talent metric reflects the Creative class occupations, on average, are now valued talent. annual mean total compensation within these classes. 120% higher (receiving approximately $53,125 more in Returns to Talent total compensation) than other workforce occupations. 1 As power shifts from companies to the creative class Within the creative class, high growth in total returns workers, compensation and stability alone are not for the “creative” occupational grouping — including sufficient to attract and retain creative talent. Companies management and professional as well as business 189 Intangible assets in 2010 Updated represented 20% of assets in the US economy, compared with 1% Exhibit 103: Creative Class compensation gap, (2003-2010) of the economy in 1965 1965 Exhibit 104: Creative Class compensation gap (2003-2010) (Compustat and Deloitte Analysis). 190 Florida, Rise of the Creative Class. $70,000 191 “The 2000 Standard Occupational Classification (SOC) system is used by Federal statistical agencies $59,366 to classify workers into occupa- $60,000 tional categories for the purpose of collecting, calculating, or disseminating data.” “Standard $50,000 Occupational Classification,” ($) $46,546 Bureau of Labor Statistics, http:// www.bls.gov/SOC (accessed June 9, 2009). $40,000 192 The Creative Class is composed of the super-creative core occupations in science and engineering, $30,000 education, arts, entertainment and sports, and creative occupations which which include management,

health care, sales, law and business Total Compensation Gap $20,000 and financial operations.The Other Workforce Class is composed of working occupations such as $10,000 construction, maintenance and transportation; service occupations like food service, personal and administrative support; and agricul- $0 ture industry occupations including 2003 2004 2005 2006 2007 2008 2009 2010 farming, fishing and forestry. 193 Hagel and Brown, "Creation Nets.” Total Compensation Gap Linear (Total Compensation Gap) 194 For more information, see the Source: Bureau of Labor Statistics, Richard Florida's "The Rise of the Creative Class“, Deloitte analysis Migration to Creative Cities metric. Source: Bureau of Labor Statistics, Richard Florida's "The Rise of the Creative Class“, Deloitte analysis 142

103 © 2011 Deloitte Touche Tohmatsu Returns to Talent Returns to Talent 2 Tab Title Here Tab 2011 Impact Index Exhibit 104: Total compensation breakdown, (2003-2010) Exhibit 105: Total Compensation Breakdown (2003-2010)

$140,000

$120,000

$100,000 ($)

$80,000

$60,000 Total Compensation $40,000

$20,000

$0 2003 2004 2005 2006 2007 2008 2009 2010 Agriculture Service Working Super-Creative Core Creative Other Workforce Average Creative Class Average Source: Bureau of Labor Statistics, Richard Florida's "The Rise of the Creative Class“, Deloitte analysis Source: Bureau of Labor Statistics, Richard Florida's "The Rise of the Creative Class“, Deloitte analysis

and financial — has contributed significantly to the As talented employees come at an increasingly higher cost, compensation gap (see Exhibit 105). Within the rest of executives should consider rethinking their firms’ primary the workforce, the “working” occupational grouping activities to get better value from those employees. Today’s received the highest compensation (note, agriculture in the firm is often an ill-fitting bundle of three different types of Occupational Employment Statistics data does not include businesses: infrastructure management, product innovation farms). and commercialization, and customer relationships. As long as they remain bundled together, the differing The growth in Returns to Talent is related to other economics, skill sets, and cultures required to succeed in indicators, such as GDP. The positive correlation with GDP each make it difficult to provide creative class workers with growth signals that creative market participants benefit the opportunities they need to best develop their talent. 104from, and may contribute to, economic growth.195 In Prospective employees today are interested not only in the © 2011 Deloitte Touche Tohmatsu fact, the creative class (including the super-creative core) growth of the firm, but also opportunities for individual only accounts for 44% of the the total U.S. workforce’s career advancement and personal growth. headcount, but earns 65% of the workforce’s total compensation, or $3 trillion dollars. This compares with the As companies become more focused, they are better able $1.7 trillion earned by the remaining 56% of all workers to participate in (and eventually orchestrate) distributed, who come from the working, service, and agriculture interfirm organizational forms—such as open source classes.196 initiatives—that are mobilizing tens (and even hundreds) of thousands of participants in flexible, diversely specialized, The results are clear: The creative class is capturing a larger and customizable configurations. These massive networks share of the economic pie. function less through conventional command-and-

195 For more information, see the Migration to Creative Cities metric. 196 Bureau of Labor Statistics, Richard Florida’s, Rise of the Creative Class and Deloitte analysis. 2011 Shift Index Measuring the forces of long-term change 143 Tab2011 Impact Index Here Title

Attracting the best talent calls for more than a pay raise

.P. Rangaswami (JP) is not your average tech employee; although he now works at salesforce.com, a leading Software-as-a-Service (Saas) company, he describes himself as an “accidental technologist” and defines his career as existing “in that strange space where finance meets technology for a number of very large firms.”197 His decision to accept the Chief Scientist position at salesforce.com, a role created for him by CEO Marc Benioff, was largely driven Jby the unprecedented opportunities for career trajectory and personal growth within the rapidly growing company. The promise of growth is so appealing that JP can put aside significant challenges, like working for a San Francisco-based company while based in the UK.

In the year prior to JP assuming the role of Chief Scientist, salesforce.com revenues grew 21%, providing an alluring opportunity for JP to be a part of this rapid acceleration.198

To keep on the leading edge of innovation, businesses must attract the type of renaissance men and women that J.P. represents and enable them to connect, grow, and blur boundaries of traditional business. In Benioff’s words, "He has the rare talent of being able to see what the future should be, knowing what it takes to get there, and the enthusiasm to make it happen.”

control, make-to-stock, and “push”-minded approaches Firms should also consider how to harness the forces that than through the laws of attraction and influence that have enabled Silicon Valley and other “spikes” to attract characterize “pull” systems. They enable workers and firms talent from around the world. Roughly half of the start-ups to mobilize resources on an as-needed basis, encouraging in Silicon Valley were founded by foreign-born talent.200 (rather than stifling) the tinkering and experimentation Public policy should reflect the importance of immigrant that facilitate learning and talent development. Because talent if the United States as a whole is to emulate the they can react quickly to fast-moving, unpredictable Silicon Valley model. Even more promising, a focus on circumstances, these “creation networks” are well suited talent development can transcend national interests. No for the Big Shift.199 matter how talented U.S. citizens are, they will develop their talents more rapidly if they have opportunities to interact with other talented people from around the world. In this era of unprecedented innovation and If we are serious about developing the talent of our own people, we must find rich and creative ways to access and disruption, new, interfirm, organizational forms connect with talent wherever it resides. are emerging. These distributed “creation networks,” together with the geographic concentrations of talent we call “spikes” are where creative class workers connect to amplify and accelerate their learning and performance.

197 Confused of Calcutta: A Blog About Information.JP Rangaswami’s Personal Blog.http://confusedofcalcutta.com/. Accessed 15 Aug 2011. 198 Salesforce.com 2011 Annual Report. http://www.sfdcstatic.com/assets/pdf/ investors/FY12AnnualReport.pdf 199 Hagel and Brown, "Creation Nets.” 200 Wadwha, Vivek.“Foreign-Born Entrepreneurs: An Underestimated American Resource.”Kauffman Thoughtbook 2009. www.kauffman. org.2008.

144 Executive Turnover Tab Title Here Tab 2011 Impact Index Executive Turnover is increasing as performance pressures rise

Introduction subset of performance-related turnover increased 318%. Given the increasing competitive pressures and declining Globally, only half of outgoing CEOs left office voluntarily The Executive ROA that have characterized the U.S. economy since 1965, during this time.201 Turnover metric it probably is not surprising that executives lose their jobs, measures executive or leave their jobs, more frequently in response to the Big Turnover, it turns out, fluctuates with the economy. During attrition rates, Shift. periods of prosperity, such as from 2005 to 2007, Executive voluntary or Turnover increased steadily, perhaps representing the wide involuntary, based In many ways, executives epitomize the difficulties facing range of other opportunities available to executives who on the number all levels in the workforce as labor markets globalize. A leave voluntarily. During a downturn, this supply of new of executive faster-moving, less predictable world has raised the degree job opportunities dries up, limiting the allure of leaving, management changes of difficulty for senior management jobs, even while and lowering the turnover rate. Furthermore, during a (VP- to board of remunerating them more highly. Executive Turnover may deep recession a board may be reluctant to change the director-level) at reflect the performance pressures and uncertainty, as well company’s top leaders because of the uncertainty and risk public companies. as the perceived opportunities, all workers’ experience. involved in finding new talent — and because of the risk that it might signal pessimism or distress to investors and This metric is a proxy Observations and Implications other stakeholders. for the unpredictable, Although over the long term, executives are leaving their dynamic pressures jobs at increasing rates as shown in Exhibit 106, the rate The 2009 data supports this analysis as Executive on the market Executive at which executives resign from, retire, or involuntarily Turnover continued to slide, reaching a five-year low. Both participants with the leave their positions has fluctuated with corporate and companies and executives exhibited a propensity to “stay most responsibility.Turnover 1 – market performance since 2002 (when the database began the course” and avoid additional instability in an uncertain needs update tracking attrition). A separate study found that, from 1995 environment. to 2006, annual CEO turnover increased 59%, and the D Exhibit 105: Executive Turnover Index, (1993-2010) Exhibit 106: Executive Turnover Index (1993-2010)

160

140

120

100 88.7

Index value Index 52.1 60 40.9 40

20 201 On-Boarding-A New Take on an Old Practice. A Cook Associates 0 Report. 2011 Shift Index Measuring the forces of long-term change 145 Source: Leading technology research vendor

Wanted: Executive Talent

wo years ago, if you were making six figures a year, the probability of finding a new job and moving forward in your career was slim. The news from the Association of Executive Search Consultants (AESC) was grim: Poor economic conditions and shelved plans for executive replacement suggested that the best course of action for Tan employed executive was no action, regardless of her current job. Now, with improvements in the economy, headhunters are calling again. Following a precipitous 32.5% decline in senior executive recruiting in 2009, the industry grew by an average of 28.5% in 2010 and is on track to do well in 2011, according to the AESC. The U.S. market is experiencing a “sustained resurgence,” according to AESC President, Peter Felix.202 The 2011 Outlook, released in January 2011 by AESC, showed a peak in industry confidence since its low point at the end of 2008.

While the pick-up in executive search marks increased opportunities for top executives, hiring companies can afford to be specific about their requirements. According to Colleen Aylward, president of executive search firm, Devon James Associates, "Employers are hiring niche authorities, plug-and-play specialists-those who have fixed the same problem many times in different ways."203 Furthermore, hired executives are under tremendous pressure to prove themselves from day one. Rising Competitive Intensity, highly engaged boards of directors and demanding investors have put executives under close scrutiny: “The brutal reality is that executives have less time than ever to prove their worth,” says Businessweek.204

The renewed demand for executive search services in 2011 could signal an increase in voluntary executive churn. However, as performance pressures mount on firms, CEOs must produce better results, faster, to keep board members and investors satisfied.

From 1995 to 2006, annual CEO turnover These trends are not limited to the executive team. Change or instability at the executive level often spurs employee increased 59% and the subset of performance- attrition across the organization. While involuntary attrition peaks during difficult economic periods, voluntary attrition related turnover increased 318%. is highest during periods of strong growth when more opportunities become available and companies compete for talent. For instance, the recent boom in social media and internet companies in Silicon Valley has increased the If the economy were to continue to improve, as it did in competition for specific talent. the first two quarters of 2011, this trend would reverse. CEO, CFO, and overall Executive Turnover have started to There are a number of factors that drive Executive increase again. With the economy improving, we expect Turnover. In times of prosperity, executives are more Executive Turnover to rise as boards act on deferred likely to be lured away from their current employment leadership changes, executives seek new opportunities, by another opportunity. However, as more and more and companies adjust their organizational skill sets to meet pressure mounts on firms, involuntary turnover has risen the changing needs of the new economy. as well. And at times, the media attention regarding a CEO’s departure makes it difficult to discern whether the 202 “Executive Search Industry Analysis conducted by Liberum Research on Executive decision was voluntary or not. Ultimately, we believe that Anticipates Growth.” Executive Newswire. January 19, 2011. Turnover between 2005 and 2011 shows a strong churn in the executive ranks will increase, driven both by level. Newly hired executives often poach talent from firms to shift course and increase performance. 203 “Out-of-Work Executives: Are The Economy And Ageism Really To their previous organizations or change the existing Blame?” Business Exchange. May leadership structure in order to build out their executive 25, 2011. significantly reshuffle the existing leadership and bring new 204 “CEOs: Hello, You Must Be Going.” BusinessWeek. February 12, 2007. talent into an organization. < http://www.businessweek. com/magazine/content/07_07/ b4021050.htm> 205 Liberum Research, http://www. twst.com/liberum.html

146 2011 Impact Index

2011 Shift Index Measuring the forces of long-term change 147 Methodology TabShift Index Here Title

148 Shift Index Methodology Shift Index Methodology

Shift Index Overview current “gold standard” indices were consulted throughout The Deloitte Center for the Edge developed the Shift the development process. Index to measure long-term changes to the business landscape. The Shift Index measures the magnitude and In compiling the Index, the Center identified and evaluated rate of change of today’s turbulent world by focusing on more metrics than could possibly be included. In some long-term trends, such as advances in digital infrastructure cases, the Center obtained metrics directly from vendors. and the increasing significance of knowledge flows. In other cases, the Center leveraged existing studies and reproduced methodologies to construct metrics. Still others The 2011 release of the Shift Index not only focuses on the Center constructed on its own. the U.S. economy, but also includes data gathering and analysis at the industry level. The Center for the Edge Many of the metrics included in the Shift Index are proxies published a report in the fourth quarter 2009 exploring used to assess the concepts key to the Big Shift logic. in greater detail how the Big Shift is affecting various U.S. For example, our Inter-Firm Knowledge Flow survey is an industries. attempt to use a proxy to estimate total knowledge flows across firms. For the list of Shift Index metrics, please refer Subsequent releases of the Shift Index, in 2011 and to Exhibit 108. beyond, will broaden the index to a global scope and provide a diagnostic tool to assess performance of To assemble the final list of 25 Shift Index metrics, we individual companies relative to a set of firm-level metrics. carefully analyzed more than 70 potential metrics, using a Exhibit 107 details these development phases. process detailed in Exhibit 109.

Our research applied a combination of established and This process evaluated fit between potential metrics originalEKM analytical  approaches to pull together four and the conceptual logic of the Big Shift. To measure decades of data, both preexisting and new. More than geographic spikiness, for example, we started by evaluating a dozen vendors and data sources were engaged, four U.S. urbanization and then measured the percentage of surveys were developed and deployed, and five proprietary total population in metropolitanNo updates areas, the percentage methodologies were created to compile 25 metrics into of population in the top 10 largest cities, and the overall three indices representing 15 industries. Architects of population density. Realizing that urbanization might

ExhibitExhibit 107:88: Shift Shift Index Index waves waves

Wave 3 Wave 2 Wave 1

Global Shift U.S. firm Index U.S. economy diagnostic tool Index

Present Future

Source: Deloitte

2011 Shift Index Measuring the forces of long-term change 149

EKM 

No updates

Exhibit 108: The Shift Index metrics Exhibit 89: The Shift Index metrics

Foundation Index Flow Index Impact Index

Technology performance Virtual flows Markets • Computing • Inter-firm knowledge flows • Competitive intensity • Digital storage • Wireless activity • Labor productivity • Bandwidth • Internet activity • Stock price volatility Infrastructure penetration Physical flows Firms • Internet users • Migration of people to • Asset profitability • Wireless subscriptions creative cities • ROA performance gap • Travel volume • Firm topple rate Public policy • Movement of capital • Shareholder value gap • Economic freedom Flow amplifiers People • Worker passion • Consumer power EKM  • Social media activity • Brand disloyalty • Returns to talent • Executive turnover No updates

Source:Source: DeloitteDeloitte

Exhibit 109: Shift Index metric selection process Exhibit 90: Shift Index metric selection process

Big Shift logic

~70 25 Proxies Metrics considered selected

Data quality and availability

150

© 2009 Deloitte Touche Tohmatsu Shift Index Methodology not be an ideal measure to assess pull forces that certain Data quality and availability was another factor evaluated geographic centers, such as Silicon Valley and Washington, when selecting metrics. Proxies with outdated data or D.C. possess over other cities, we elected to apply ones that are no longer maintained were discarded. For Richard Florida’s study of creative cities. The creative cities example, total factor productivity was a potential proxy identified by Florida are the epicenters of diversity, talent, for productivity improvements, but available data sources and tolerance. Thus, they represented places where people lacked industry-level information and had three-year data migrate to benefit from cognitive diversity and sharing of lags. These limitations led us to include Labor Productivity tacit knowledge. As the Big Shift takes further hold, we rather than total factor productivity in the Impact Index. anticipate increased migration to the most creative cities, For a representative list of metrics considered for the Shift as compared to the least creative ones. Selecting the Index, please refer to Exhibit 110. Migration of People to Creative Cities metric as a proxy . for geographic spikiness seemed more appropriate and consistent with the logic of the Big Shift than using any general measure of U.S. urbanization.

Exhibit 110: Shift Index Proxies Considered but Not Selected

Component Proxies Considered Index Driver Foundation Index Technology • Market spending on hardware, software, and IT services (U.S.$ per person) Performance • Broadband connections (xDSL, ISDN PRI, FWB, cable, and FTTx) per person Infrastructure • Telecommunication equipment exports and imports (U.S.$) Penetration • Percentage of automatic phone lines compared to the percentage of digital phone lines • Number of fixed telephone line subscribers per 100 inhabitants • Number of mobile cellular telephone subscribers per 100 inhabitants • Total fixed and cellular telephone subscribers per 100 inhabitants • Number of people within mobile cellular network coverage as a percentage of total population • Total number of PCs • Percentage of homes with a PC • Internet users per 100 inhabitants • Total Internet subscribers (fixed broadband) per 100 inhabitants Public Policy • Number of regulations per industry • Number of new regulations per year Flow Index Virtual Flows • Number of joint ventures • Number of co-branded products • Patent citations • Percentage of time spent interacting with external business partners • Patent distribution • Open innovation participation • Bibliometric analysis —academic paper citations • People movement/immigration • International Internet bandwidth (Mbps) • International Internet bandwidth per inhabitant (bit/s)

2011 Shift Index Measuring the forces of long-term change 151 Methodology Shift Index

Component Proxies Considered Index Driver Physical Flows • Percentage of total population in metropolitan areas • Percentage of population in top 10 largest cities • Population density Flow Amplifiers • Total number of people participating in online communities • Total number of open sourced products • Total number of social networking sites • Total unique users engaged in social networking sites Impact Index Markets • Total factor productivity • Average time to complete a set of employee tasks • Firm distribution (startup vs. incumbent) • Number of new firms created • Number of days stock price has changed more than three Standard Deviations from average of yearly returns Firms • Profit elasticity • Profit margin (earnings before interest, taxes, depreciation and amortization/revenue) • Economic margin • ROIC • Shareholder value creation People • Rank shuffling by Interbrand Survey score • Minimum wage as percentage of value added per worker • Hiring patterns for top management team • Average compensation of senior executives • Median age (in years) of patents cited

Source: Deloitte

152 Shift Index Methodology

Shift Index Metrics Overview The following set of tables provides detailed descriptions of each metric used to compile the Shift Index, including metric definition, high-level calculations, and primary data sources.

Foundation Index

Metric Methodology Technology Performance Computing Definition: Computing measures the vendor cost associated with putting 1 million transistors on a semiconductor. The metric provides visibility into cost/performance associated with the computational power at the core of the Big Shift.

Calculations: The metric was derived from Moore’s Law, which furnishes insight into the basic computing performance curve. Initial insights were confirmed by direct observations of the number of transistors vendors are able to put on the most powerful commercially available semiconductors, an analysis of wholesale pricing for individual chips and as a breakdown component of servers, and an assessment of vendor margins to determine cost as a component of wholesale price.

Data Source: The data were obtained from a number of publicly available sources of information about semiconductor performance as defined by millions of transistors per semiconductor, including vendors, wholesale distributors of semiconductors, and leading technology research vendors.

Digital Storage Definition: Digital Storage measures the vendor cost associated with producing 1 GB of digital storage. The metric provides visibility into the cost/performance curve associated with digital storage allowing for the computational power at the core of the Big Shift.

Calculations: The metric is described by Kryder’s Law, which is derived from Moore’s Law. Kryder’s Law provides insight into the basic cost/performance curve that governs digital storage. Initial insights were confirmed by direct observations of the wholesale pricing for 1 GB of memory and an assessment of vendor margins to determine cost as a component of wholesale price.

Data Sources: The data were obtained from a number of publicly available sources of cost information, including vendors, wholesale distributors of digital storage, and leading technology research vendors.

2011 Shift Index Measuring the forces of long-term change 153 Methodology Shift Index

Metric Methodology Bandwidth Definition: The 2009 Shift Index measure for bandwidth captured the vendor cost associated with producing GbE-Fiber as deployed in data centers. In 2010, we chose to transition the bandwidth metric from GbE (1,000 Mbps) to 10 GbE (10 GB) based on increasing market penetration of 10 GbE and the resulting cost reduction as manufacturing volumes increase. Regardless of the measure used, this metric provides visibility into the cost/performance curve associated with network bandwidth, one of the key components of the new digital infrastructure.

Calculations: Because technology performance in the Shift Index is designed to measure the impact of innovation and bandwidth, which is the result of a complex array of technologies that extend from the enterprise data center to the last mile into residential homes, this metric focuses on GbE—Fiber in the data center as the best commercially available example of bandwidth innovation. Initial insights were confirmed by direct observations of the wholesale pricing for GbE-Fiber and an assessment of vendor margins to determine cost as a component of wholesale price.

Data Sources: The data were obtained from a number of publicly available sources of cost information, including vendors, wholesale distributors of network equipment in the data center, and leading technology research vendors.

Infrastructure Penetration Internet Users Definition: The Internet Users metric measures the number of “active” Internet users in the United States as a percentage of total U.S. population. “Active” users are defined as those who access Internet at least daily. The Internet Users metric is a proxy for the core technology adoptions.

Calculations: Active Internet user data were obtained directly from a report published by comScore. comScore conducts monthly enumeration phone surveys to collect data on the Internet usage and user demographics. Each month, comScore utilizes data from the most recent wave of the surveys and from the 11 preceding waves to estimate the proportion of households in the United States with at least one member using the Internet and the average number of Internet users in these households. comScore then takes the product of these two estimates and compares it with the census-based estimate of the total number of households in the United States to assess total Internet penetration.

Data Sources: The data were obtained from comScore’s Media metrics report.

154 Shift Index Methodology

Metric Methodology Wireless Subscriptions Definition: The Wireless Subscriptions metric estimates the total number of active Wireless Subscriptions as a percentage of the U.S. population. The Wireless Subscriptions metric is a proxy for core technology adoption.

Calculations: CTIA’s semiannual wireless industry survey (traditionally known as the CTIA “data survey”) gathers industry-wide information from Commercial Mobile Radio Service (CMRS) providers operating commercial systems in the United States. Only companies with operational systems and licenses to operate facilities-based systems are surveyed. The survey prompts respondents to answer the following question: “Indicate the number of subscriber units operating on your switch, which produce revenue. Include suspended subscribers that have not been disconnected. This number should not include subscribers that produce no revenue, such as demonstration phones and some employee phones.” The CTIA survey requests the information on the number of revenue-generating wireless service subscribers and summarizes the result in the CTIA Wireless Subscriber Usage report. Since the metric measures Wireless Subscriptions and not wireless subscribers, it is possible for the total number to exceed the overall U.S. population, as one person can have multiple Wireless Subscriptions.

Data Sources: The data were obtained from the CTIA Wireless Subscriber Usage report.

Public Policy Economic Freedom Definition: The Economic Freedom metric measures how free a country is across 10 component freedoms: business, trade, fiscal, government size, monetary, investment, financial, property, labor, and, finally, freedom from corruption. The Economic Freedom metric is a proxy for openness of public policy and the degree of economic liberalization, which are both fundamental to either enabling or restricting Big Shift forces.

Calculations: Each freedom component was assigned a score from 0 to 100, where 100 represents maximum freedom. The 10 scores were then averaged to gauge overall economic freedom.

Data Source: The data were obtained from the 2010 Index of Economic Freedom by The Heritage Foundation and Dow Jones & Company, Inc., http://www.heritage.org/Index.

2011 Shift Index Measuring the forces of long-term change 155 Methodology Shift Index

Flow Index

Metric Methodology Virtual Flows Inter-Firm Knowledge Definition: Flows The Inter-Firm Knowledge Flows metric is a proxy for knowledge flows across firms. Success in a world disrupted by the Big Shift will require individuals and firms to participate in knowledge flows that extend beyond the four walls of the firm.

Calculations: We explored the types and volume of interfirm knowledge flows in the United States through a national survey of 3,108 respondents. The survey was administered online in April 2010. The results are based on a representative (95% confidence level) sample of approximately 200 (±5.8%) respondents in 15 industries, including 50 respondents (±11.7%) tagged as senior management, 75 (±9.5%) as middle management, and 75 (±9.5%) as frontline workers. In the survey, we tested the participation and volume of participation in eight types of knowledge flows: 1) In which of the following activities do you participate: • Use social media to connect with other professionals (e.g., blogs, Twitter, and LinkedIn) • Subscribe to Google alerts • Attend conferences • Attend Web-casts • Share professional information and advice over the telephone • Arrange lunch meetings with other professionals to exchange ideas and advice • Participate in community organizations • Participate in professional organizations

2) How often do you participate in each of the above professional activities? • Daily • Several times a week • Weekly • A few times a month • Monthly • Once every few months • Once a year • Less often than once a year

The knowledge flow activities were normalized by the maximum possible participation for each activity (e.g., daily for social media and weekly for Web casts).

Thus, an Inter-Firm Knowledge Flow value was calculated for each individual based on his or her participation in knowledge flows. The average of these flows is the index value for the Inter-Firm Knowledge Flow value metric.

Data Sources: Data were obtained from the proprietary Deloitte survey and analysis.

156 Shift Index Methodology

Metric Methodology Wireless Activity Definition: The Wireless Activity metric measures the total number of wireless minutes and total number of SMS messages in the United States per year. The metric is a proxy for connectivity and knowledge flows.

Calculations: CTIA’s semiannual wireless industry survey develops industry-wide information drawn from CMRS providers operating commercial systems in the United States. Only companies with operational systems and licenses to operate facilities-based systems are surveyed. Wireless minutes are estimated from the CTIA survey, which measures the total minutes used by subscribers. The CTIA survey asks wireless carriers to report the total number of billable calls, billable minutes (both local and roaming), and total SMS volume on the respondent’s network. Note that for the 2009 index, we used a December-December calendar year to measure wireless minutes and the six months ending in December for SMS volume. Due to data availability issues, this was changed for the 2010 report: now, wireless minutes are measured from June-June and SMS volume from January-June as opposed from June- December. While this shift did impact the index in 2010, as it effectively gave these metrics less time to "grow" before being measured again, it is not indicative of a slowdown in wireless activity. Also, since this was a one-time change, it will not impact the index in 2011.

Data Sources: The data were obtained from the CTIA Wireless Subscriber Usage report.

Internet Activity Definition: The Internet Activity metric measures Internet traffic for the 20 highest capacity U.S. domestic Internet routes in gigabits/second. The metric is a proxy for connectivity and knowledge flows.

Calculations: Internet volume data were obtained through TeleGeography, which determines Internet capacity and traffic data through confidential surveys, informal discussions, and follow-up interviews with network engineering and planning staff of major Internet backbone providers.

Data Sources: The data were obtained from TeleGeography’s Global Internet Geography report.

2011 Shift Index Measuring the forces of long-term change 157 Methodology Shift Index

Metric Methodology Physical Flows Migration of People to Definition: Creative Cities The Migration of People to Creative Cities metric measures the increase in population in cities ranked as most creative as compared to the increase in population in cities ranked as least creative. The metric serves as a proxy for physical flow of people towards centers of creativity and innovation in order to access knowledge flows more effectively and intimately.

Calculations: As one of the proxies for physical knowledge flows expressed through face-to-face interactions and serendipitous connections, we were measuring the growth in population, as provided by the U.S. Census Bureau, within creative cities, as defined by Richard Florida.

The most and least creative cities are defined by Richard Florida in his bookThe Rise of the Creative Class. Each city with more than one million people in population is ranked by its creative index score. Florida determined the creative index score by adding three equally weighted components: technology, talent, and tolerance. U.S. Census Bureau data were used to determine the population of the cities defined by Florida as most and least creative. We defined the metric as a gap between the two groups’ population.

Data Sources: Florida’s book, The Rise of the Creative Class, and the U.S. Census Bureau http://www. census.gov/popest/cities/cities.html.

158 Shift Index Methodology

Metric Methodology Travel Volume Definition: The Travel Volume metric is defined as the volume of passenger travel. The metric serves as a proxy for physical flows of people and indicates levels of face-to-face interactions, which are more likely to drive the most valuable knowledge flows—those that result in new knowledge creation rather than simple knowledge transfer.

Calculations: The Transportation Services Index (TSI) published by the Bureau of Transportation Statistics, the statistical agency of the U.S. Department of Transportation (DOT) is used to assess the volume of passenger travel. The passenger TSI measures the movement and month-to- month changes in the output of services provided by the for-hire passenger transportation industries. The seasonally adjusted index consists of data from passenger air transportation, local mass transit, and intercity passenger rail. Note that to keep pace with ongoing methodology adjustments by the BTS, we update the full historical data set each year the Shift Index is calculated.

Data Sources: U.S. Department of Transportation, Research and Innovation Technology Administration, Bureau of Transportation Statistics Transportation Services Index; http://www.bts.gov/xml/ tsi/src/index.xml.

Movement of Capital Definition: The Movement of Capital metric measures the value of U.S. FDI inflows and outflows. The metric serves as a proxy for capital flows between the edge and the core. Edges are peripheral areas of geographies, demographic generations, and technologies where growth and innovation tend to concentrate. The core is where the money is today.

Calculations: Current dollar FDI inflows into the United States and outflows from the United States were summed. Absolute values were used to capture the total amount of flows regardless of the direction. The result was normalized by the size of the economy by dividing FDI flows by the U.S. GDP. This normalization will allow for comparability as we extend our index internationally. FDI stocks were excluded from the calculations as they do not directly represent the flows of capital.

Data Source: The data were obtained from the United Nations Conference on Trade and Development (UNCTAD) FDI database (http://stats.unctad.org/FDI/TableViewer/tableView. aspx?ReportId=1254. Previous years' estimates for FDI flows were replaced with actuals when available. Also, note that due to ongoing changes in the way FDI flows are measured by the UNCTAD, we update the full historical data set each year.

2011 Shift Index Measuring the forces of long-term change 159 Methodology Shift Index

Metric Methodology Flow Amplifiers Worker Passion Definition: The Worker Passion metric measures how passionate U.S. workers are about their jobs. Passionate workers are fully engaged in their work and their interactions and strive for excellence in everything they do. Therefore, worker passion acts as an amplifier to the knowledge flows, thereby accelerating the growth of the Flow Index.

Calculations: Our exploration of worker passion was designed around a national survey with 3,108 respondents. The survey was administered online in April 2010. The results are based on a representative (95% confidence level) sample of approximately 200 (±5.8%) respondents in 15 industries, including 50 respondents (±11.7%) tagged as senior management, 75 (±9.5%) as middle management, and 75 (±9.5%) as frontline workers.

In the survey, we tested different attitudes and behavior around worker passion— excitement about work, fulfillment from work, and willingness to work extra hours—using the following six statements/questions:

Please tell us how much you agree or disagree with each statement below relating to your specific job (7-point scale from strongly agree to strongly disagree): 1) I talk to my friends about what I like about my job. 2) I am generally excited to go to work each day. 3) I usually find myself working extra hours, even though I don't have to. 4) My job gives me the potential to do my best. 5) To what extent do you love your job? (7-point scale from a lot to not at all) 6) Which of the following statements best describes your current situation? • I’m currently in my dream job at my dream company. • I’m currently in my dream job, but I’d rather be at a different company. • I’m not currently in my dream job, but I’m happy with my company. • I’m not currently in my dream job, and I’m not happy at my company.

A response was classified as a “top two” response if it was a 7 or 6 on the 7-point scales or a 1 or 2 on the last question.

The respondents were then classified as “disengaged,” “passive,” “engaged, "and “passionate” based on the number of “top two” responses: • Passionate: 5-6 of the statements • Engaged: 3-4 of the statements • Passive: 1-2 of the statements • Disengaged: None of the statements

The index value for Worker Passion is the percentage of “passionate” respondents to the number of total respondents.

Data Sources: Data were obtained from the proprietary Deloitte survey and analysis.

160 Shift Index Methodology

Metric Methodology Social Media Activity Definition: Social Media Activity is a measure of how many minutes Internet users spend on social media Web sites relative to the total minutes they spend on the Internet. The metric is a proxy for two- and multiple-way communication, which amplifies knowledge flows by offering the ability to collaborate.

Calculations: comScore provides industry-leading Internet audience measurement that reports details of online media usage; visitor demographics; and online buying power for home, work, and university audiences across local U.S. markets and across the globe. Using proprietary data collection technology and cutting-edge methodology, comScore is able to capture great volumes of extremely granular data about online consumer behavior. comScore deploys passive, non-invasive measurement in its collection technologies, projecting the data to the universe of persons online. For the purposes of collecting data for our analysis, comScore defines social media as a virtual community within Internet Web sites and applications to help connect people interested in a subject.

Data Sources: The data were obtained from comScore’s Media Metrics report.

2011 Shift Index Measuring the forces of long-term change 161 Methodology Shift Index

Impact Index

Metric Methodology Markets Competitive Definition: Intensity The Competitive Intensity metric is a measure of market concentration and serves as a rough proxy for how aggressively firms interact.

Calculations: The metric is based on the HHI, a methodology used in competitive and antitrust law to assess the impact of large mergers and acquisitions on the concentration of market power. Underlying the metric is the notion that markets where power is more widely dispersed are more competitive. This logic is consistent with the Big Shift, which predicts that industries will initially fragment as the traditional benefits of scale decline with barriers to entry. As strategic restructuring occurs, and companies begin to focus more tightly on a core business type, certain firms will likely once again begin to exploit powerful economies of scale and scope, but in a much more focused manner.

Data Source: The metric was calculated by Deloitte, using data provided by Standard & Poor’s Compustat on over 20,000 publicly traded U.S. firms (and foreign companies trading in American Depository Receipts). It is available annually and by industry sector through 1965.

Labor Definition: Productivity The Labor Productivity metric is a measure of economic efficiency that shows how effectively economic inputs are converted into output. The metric is a proxy for the value creation resulting from the Big Shift and enriched knowledge flows.

Calculations: Productivity data were downloaded directly from the Bureau of Labor Statistics database.

The Bureau of Labor Statistics does not compute productivity data by the exact sectors analyzed in the Shift Index. Therefore, Labor Productivity by industry was derived using data published by the Bureau. Bureau data were aggregated by five, four, and sometimes three-digit North American Industry Classification System (NAICS) codes using Bureau methodology to map to the Shift Index sectors.

Sector Labor Productivity figures were calculated as a ratio of the output of goods and services to the labor hours devoted to the production of that output. A sector output index was calculated using the Tornqvist formula (the weighted aggregate of the growth rates of the various industries between two periods, with weights based on the industry shares in the sector value of production). The input was calculated as a direct aggregation of all industry employee hours in the sector. Note that due to ongoing methodology and data revisions by the Bureau of Labor Statistics, we update and replace the entire Labor Productivity data set each year.

Note for the 2011 Shift Index release, labor productivity and related cost measures for 2010 for mining, utility, manufacturing, and selected service industries were not available and will not be released by the Bureau of Labor Statistics until 2012.

Data Sources: The metric was based on the Bureau of Labor Statistics data. Major sector data are available annually beginning in 1947, and detailed industry data on a NAICS basis are available annually beginning in 1987.

162 Metric Methodology Stock Price Definition: Volatility The Stock Price Volatility metric is a measure of trends in movement of stock prices. The metric is a proxy for measuring disruption and uncertainty. Shift Index Methodology Calculations: Standard deviation is a statistical measurement of the volatility of a series. Our data provider, Center for Research in Security Prices (CRSP) at the University of Chicago Booth School of Business, provides annual standard deviations of daily returns for any given portfolio of stocks. Rather than using an equal-weighted approach, we used value-weighting.

According to CRSP: “In a value-weighted portfolio or index, securities are weighted by their market capitalization. Each period the holdings of each security are adjusted so that the value invested in a security relative to the value invested in the portfolio is the same proportion as the market capitalization of the security relative to the total portfolio market capitalization” (http://www.crsp. com/support/glossary.html).

Data Sources: Established in 1960, CRSP maintains the most complete, accurate, and user-friendly securities database available. CRSP has tracked prices, dividends, and rates of return of all stocks listed and traded on the New York Stock Exchange since 1926, and in subsequent years, it has also started to track the NASDAQ and the NYSE Arca. http://www.crsp.com/documentation/product/stkind/ calculations/standard_deviation.html

Firms Asset Definition: Profitability Asset Profitability (ROA) is a widely used measure of corporate performance and a strong proxy for the value captured by firms relative to their size.

Calculations: In the Shift Index, Asset Profitability is an aggregate measure of the net income after extraordinary items generated by the economy (defined as all publicly traded firms in our database) divided by the net assets, which includes all current assets, net property, plants, and equipment, and other non-current assets. Net income in this case was calculated after taxes, interest payments, and depreciation charges.

Data Sources: The metric was calculated by Deloitte, using data provided by Standard & Poor’s Compustat on over 20,000 publicly traded U.S. firms (and foreign companies trading in American Depository Receipts). It is available annually and by industry sector through 1965.

2011 Shift Index Measuring the forces of long-term change 163 Methodology Shift Index

Metric Methodology ROA Definition: Performance The ROA Performance Gap tracks the bifurcation of returns flowing to the top and bottom quartiles Gap of performers and is a proxy for firm performance.

Calculation: This metric consists of the percentage difference in ROA between these groups and is a measure of how value flows to or from “winners” and “losers” in an increasingly competitive environment.

Data Sources: The metric is based on an extensive database provided by Standard & Poor’s Compustat. It was calculated by Deloitte. The metric is available annually and by industry sector through 1965.

Firm Topple Definition: Rate The Firm Topple Rate measures the rate at which companies switch ranks, as defined by their ROA performance. It is a proxy for dynamism and upheaval and represents how difficult or easy it is to develop a sustained competitive advantage in the world of the Big Shift.

Calculations: To calculate this metric, we used a proprietary methodology developed within Oxford’s Said Business School and the University of Cologne that measures the rate at which firms jump ranks normalized by the expected rank changes under randomness. A topple rate close to zero denotes that ranks are perfectly stable and that it is relatively easy to sustain a competitive advantage, whereas a value near one means that ranks change randomly, and that doing so is uncommon and incredibly difficult.

We applied this methodology to firms with more than $100 million in annual net sales and averaged the results from our 15 industry sectors to reach an economy-wide figure.

Data Sources: This metric is based on data from Standard & Poor’s Compustat. It was calculated annually and by industry sector through 1965.

164 Shift Index Methodology

Metric Methodology Shareholder Definition: Value Gap The Shareholder Value Gap metric is defined in terms of stock returns and it aims to quantify how hard it is for companies to generate sustained returns to shareholders. It is another assessment of the bifurcation of “winners” and “losers.”

Calculations: The calculation uses the weighted-average TRS percentage for both the top and bottom quartiles of firms in our database, in terms of their individual TRS percentages, to define the gap. Total returns are annualized rates of return reflecting price appreciation plus reinvestment of monthly dividends and the compounding effect of dividends paid on reinvested dividends.

Data Sources: The metric is based on Standard & Poor’s Compustat data and is available annually and by industry sector through 1965.

People Consumer Definition: Power The Consumer Power metric measures the value captured by consumers. In a world disrupted by the Big Shift, consumers continue to wrestle more power from companies.

Calculations: A survey was administered online in April 2010 to a sample of 2,000 U.S. adults (at least 18 years old) who use a consumer category in question and can name a favorite brands in that category. The sample demographics were nationally balanced to the U.S. census. A total of 4,292 responses were gathered as consumers were allowed to respond to surveys on multiple consumer categories. A total of 26 consumer categories were tested with approximately 180 (±6.2%, 95% confidence level) responses per category.

We studied a shift in Consumer Power by gathering 4,292 responses across 26 consumer categories to a set of six statements measuring different aspects, attributes, and behaviors involving consumer power: • There are a lot more choices now in the (consumer category) than there used to be. • I have convenient access to choices in the (consumer category). • There is a lot of information about brands in the (consumer category). • It is easy for me to avoid marketing efforts. • I have access to customized offerings in the (consumer category). • There isn't much cost associated with switching away from this brand.

The index value for the Consumer Power metric is the average Consumer Power score of all respondents.

Data Sources: Data were obtained from the proprietary Deloitte survey and analysis.

2011 Shift Index Measuring the forces of long-term change 165 Methodology Shift Index

Metric Methodology Brand Disloyalty Definition: The Brand Disloyalty metric is another measure of value captured by consumers. As a result of increased Consumer Power and a generational shift in reliance on brands, the Brand Disloyalty measure is an indicator of consumer gain stemming from the Big Shift.

We studied a shift in Brand Disloyalty by gathering 4,292 responses across 26 consumer categories to a set of six statements measuring different aspects, attributes, and behaviors involving brand disloyalty: • I would consider switching to a different brand. • I compare prices for this brand with other brands. • I seek out information about other brands. • I ask friends about the brands they use. • I switch to the brand with the lowest price. • I pay attention to advertising from other brands.

Each participant was asked to respond to these statements on a 7-point scale, ranging from 7=completely agree to 1=completely disagree. An average score was calculated for each respondent and then converted to a 0—100 scale. The index value for the Brand Disloyalty metric is the average Brand Disloyalty score of all respondents.

Data Sources: Data were obtained from the proprietary Deloitte survey and analysis.

166 Shift Index Methodology

Metric Methodology Returns to Definition: Talent The Returns to Talent metric examines fully loaded compensation between the most and least creative professions. The metric is a proxy for the value captured by talent.

Calculations: The most and least creative occupations were leveraged from Florida’s study. A fully loaded salary (cash, bonuses, and benefits) was calculated for each group and the differences were measured.

Data Sources: The most and least creative occupations were obtained from Florida’s book The Rise of the Creative Class. Fully loaded salary information was gathered from the Bureau of Labor Statistics data leveraging the Occupational Employment Statistics (OES) Department and Employer Cost for Employee Compensation information (ECEC). The analysis was performed by Deloitte.

ECEC: http://www.bls.gov/ect/home.htm OES: http://www.bls.gov/OES/ Creative Class Group: http://www.creativeclass.com/

Executive Definition: Turnover The Executive Turnover metric measures executive attrition rates. It is a proxy for tracking the highly unpredictable, dynamic pressures on the market participants with the most responsibility—executives.

Calculations: The data were obtained from the Liberum Research (Wall Street Transcript) Management Change database and measures the number of executive management changes (from a board of director through vice president level) in public companies. For the purposes of this analysis, we summed the number of executives who resigned from, retired, or were fired from their jobs and then normalized that one number, each year from 2005 to 2009, against the number of total management occupational jobs reported by the Bureau of Labor Statistics (Occupation Employment Statistics) for each of those years. Liberum Research’s Management Change Database is an online SQL database. Each business day, experts examine numerous business wire services, government regulatory filings (e.g., SEC Form 8K filings), business periodicals, newspapers, RSS feeds, corporate and business- related blogs, and specified search alerts for executive management changes. Once an appropriate change is found, Liberum’s staff inputs the related management change information into the management change database. Below are the overall management changes tracked by Liberum: • I-Internal move, no way to differentiate if the move is lateral, a promotion, or a demotion • J-Joining, hired from the outside • L-Leaving, SEC Form 8K or press release contains information that states individual has left the firm; no indication of a resignation, retirement, or firing • P-Promotion, moved up the corporate ladder • R-Resigned/retired • T-Terminated

Data Sources: Liberum Research (a division of Wall Street Transcript); http://www.twst.com/liberum.html OES: http://www.bls.gov/OES/

2011 Shift Index Measuring the forces of long-term change 167 Methodology Shift Index

Index Creation Methodology over time; the latter is what we want the Impact Index to After a rigorous data collection process, we made several represent. On the other hand, Labor Productivity moves adjustments to the data to create the final Shift Index. To very little, so any large fluctuations are critically important ensure that each metric has an appropriate impact on the to include. Essentially, the degree to which we want to overall index and to focus on secular, long-term trends, we smooth secular non-exponential metrics depends on how performed five steps: volatile they typically are.

Classifying metrics To make this assessment, we calculate something called A key challenge in assembling the index is being able to a “deviation score” for each metric of this type, which combine metrics of different magnitudes, trends, and represents how much (on average) it deviates from its volatility in a sensible way. The first step in this process long-term trend line. This score sets the “threshold” for involves carefully evaluating each metric with respect to how much volatility we allow through to the final index. historical trends, future projections, and qualitative research and classifying it as either “secular non-exponential,” We do this by revising the raw values to represent a meaning any non-exponential metric with a defined or combination of (a) the value predicted in a given year by assumed long-term trend, or “exponential,” which pertains linear regression and (b) the difference between the raw to metrics, such as Computing and Wireless Activity. With value and the predicted one (e.g., volatility). The former these classifications, we then apply one of two smoothing/ is always given a weight of one, but the latter is dynamic: transformation methodologies to make the metrics This is where the deviation score comes in. The higher the statistically comparable. deviation score, the less weight is given to this difference. Before indexing, the contribution of Movement of Capital Smoothing metric trends and volatility (which is highly volatile and, by extension, has a high- Metrics that are classified as exponential present a deviation score) to the index in a given year is 100% of the particular challenge, in that their rapid growth can predicted value and a small percentage of the deviation overwhelm slower moving metrics in the index. At the around that mean. By the same token, Labor Productivity, same time, accurately representing trends in the underlying which fluctuates much less, contributes a very large data is critical, especially those related to technology and percentage of that deviation in addition to 100% of its knowledge flows, whose exponentiality is at the core of predicted value. the Big Shift. Our solution to these concerns is exactly the middle ground: We dampen exponential metrics, Because our next step is to index these values to a base but not so much as to make them linear. To do this, we year (2003) — which will be discussed in the next section use a Box-Cox Transformation (a commonly accepted — this artificial inflation or deflation has no impact on technique for normalizing exponential functions), which the index and instead serves only to minimize or preserve uses a transformation coefficient to effectively reduce volatility in the underlying data. their growth rate. All exponential metrics are transformed using the same coefficient in order to preserve the relative Normalizing rates of change differences between them. After smoothing exponential and non-exponential metrics to make them comparable and to represent long-term For secular non-exponential metrics, we engage in a trends, we normalize each metric by indexing it to 2003. different kind of dampening: Smoothing out volatility to This process refocuses the Shift Index from magnitudes to focus the index on long-term trends. This is of particular rates of change, which is in the end what we are trying to concern in the Impact Index, which contains a number of measure. metrics that are highly volatile in the short term, but over the long run show defined trends. Stock Price Volatility, By choosing 2003 as a base year, we can easily evaluate for example, swings wildly, but is also trending upward rates of change in the past five years. In addition, historical

168 Shift Index Methodology data are available for nearly all 25 metrics by 2003, limiting about what forces are driving foundational shifts. As such, the need for estimation to backtest the index. However, we want to give equal weights to each concept, regardless those metrics that did not have historical data starting in of how many metrics it contains. To do this, each metric 2003 (e.g., our four proprietary survey metrics, Internet is assigned a weight based on the number of metrics in its Activity, and Social Media Activity) are indexed to 2008. respective driver (Technology Performance contains three This last difference in indexing treatment accounts for the metrics, so one-third) times one-third again, representing less-than-100 value of the Flow Index in 2003. the fact that Technology Performance accounts for an equal share of the Foundation Index. Weighting metrics to reflect the logic The final step before calculating the Foundation Index, In addition to preserving the logic, what this system allows Flow Index, and Impact Index is properly weighting each us to do is add and subtract metrics in future years without metricEKM to ensure each driver (key concept) contributes needing to materially restructure the index. Additionally, equally to the index. This process is detailed in Exhibit 111, when the Shift Index is released on a global scale, it but to clarify, the Foundation Index contains three drivers: provides room to choose geographically relevant metrics Technology Performance, Infrastructure Penetration, and and proxies while maintainingNo updates comparability with the U.S. Public Policy. Each of these contains different numbers of index. metrics, but overall they represent three core concepts

Exhibit 111: Shift Index weighting methodology Exhibit 92: Shift Index weighting methodology

Foundation Index

Technology performance • Computing => 1/9 times value 1/3 times value • Digital storage => 1/9 times value • Bandwidth => 1/9 times value + Foundation Index Infrastructure penetration value • Internet users => 1/6 times value 1/3 times value • Wireless subscriptions => 1/6 times value + Public policy 1/3 times value • Economic freedom => 1/3 times value

Source: Deloitte

2011 Shift Index Measuring the forces of long-term change 169

Other tools: Correlation model Correlations greater than 0.60 (signifying an increasing To explore conceptually plausible relationships in and linear relationship) or less than -0.60 (signifying a among various Shift Index metrics, as well as with decreasing linear relationship) are considered to be macroeconomic indicators, we also conduct a simple significant and worthy of applying conceptual logic and/or quantitative exercise to identify the strength of these further exploration. relationships and the subsequent correlations or degrees of linear dependence. The formula and function we use For example, the results of this basic analysis show a to calculate the correlation coefficient for a sample uses significant positive correlation between the Heritage the covariance of the samples and the standard deviations Foundation’s business freedom and GDP (0.69) and of each sample. To obtain the most accurate results, we between the Heritage Foundation’s business freedom and only note quantitative correlation relationships between Competitive Intensity (0.88). Because business freedom data sets with a time series of at least three years and an is defined as the “ability to start, operate, and close identifiably linear trend. businesses that represents the overall burden of regulations and regularity efficiency,” it seems plausible that as To be clear, this approach and our assertions do not imply business freedom increases, there is greater opportunity causality. Two data sets might be related and have a strong to create economic value, for the regulatory environment correlation, but could be independently related to another encourages growth while at the same time creating a more variable or not conceptually related at all. We invite others competitive environment due to lower barriers to entry and to join with us and engage in further exploration and participation. rigorous analyses where interesting insights might be developed further.

170 Appendix Appendix

172 Aerospace & Defense

176 Automotive

180 Banking & Securities

184 Consumer Products

188 Energy

192 Health Care

196 Insurance

200 Life Sciences

204 Media & Entertainment

208 Process & Industrial Products

212 Retail

216 Technology

220 Telecommunications

2011 Shift Index Measuring the forces of long-term change 171 Aerospace & Defense — Appendix Aerospace & Defense A64

Exhibit 1: Competitive Intensity, Aerospace & Defense, (1965-2010) Exhibit 1: Competitive Intensity, Aerospace & Defense (1965-2010)

0.16

0.14 0.14 0.13 0.12 0.11 0.10

0.08

Herfindahl Index 0.06 0.05 0.04

0.03 0.02 0.03

0.00 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 Aerospace & Defense Economy Linear (Aerospace & Defense) Linear (Economy)

Source: CompustatCompustat,, Deloitte Deloitte Analysis analysis

HHI Value Industry Concentration Competitive Intensity

< .01 Highly Un-concentrated Very High 0 - 0.10 Un-concentrated High A65 0.10 - 0.18 Moderate Concentration Moderate

0.18 - 1 High Concentration Low

Exhibit 2: Labor Productivity, Aerospace & Defense, (1987-2010) D Exhibit 2: Labor Productivity, Aerospace & Defense (1987-2010)

Productivity Index 40 20 0 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Aerospace & Defence Economy Linear (Aerospace & Defence) Linear (Economy)

Source:Source: Bureau Bureau of ofLabor Labor Statistics, Statistics, Deloitte Deloitte Analysis analysis

172

Exhibit 3: Asset Profitability, Aerospace & Defense, (1965-2010) Appendix — Defense & Aerospace Exhibit 3: Asset Profitability, Aerospace & Defense (1965-2010)

6% 5.6%

4.2% 4.6% 4% 3.7% 3%

2% Return on Assets (%) 1% 1.0% 0% 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 A67 Aerospace & Defense Economy Linear (Aerospace & Defense) Linear (Economy) Source: Compustat, Deloitte analysis

Source: Compustat, Deloitte Analysis D

Exhibit 4: Asset Profitability Top Quartile and Bottom Quartile, Aerospace & Defense, (1965-2010) Exhibit 4: Asset Profitability Top Quartile and Bottom Quartile, Aerospace & Defense (1965-2010)

20%

15%

10% 8.9% 8.8%

Top Quartile Linear (Top Quartile)

10% Return on Assets (%)ReturnAssetson -1.0% -10% -5.6%

-30%

-50% 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010

Bottom Quartile Linear (Bottom Quartile)

Source: Compustat, Deloitte analysis

2011 Shift Index Measuring the forces of long-term change 173

A68

Exhibit 5: Firm Topple, Aerospace & Defense, (1966-2010) Exhibit 5: Firm Topple, Aerospace & Defense (1966-2010)

1.20

1.00

0.80

0.56 0.60 0.54

Topple Rate 0.51 0.40

0.39 0.20

0.00 1966 1970 1974 1978 1982 1986 1990 1994 1998 2002 2006 2010 A69 Aerospace & Defense Economy Linear (Aerospace & Defense) Linear (Economy) Source: Compustat, Deloitte analysis

Source: Compustat, Deloitte Analysis D

Exhibit 6: Returns to Talent, Aerospace & Defense, (2003-2010) Exhibit 6: Returns to Talent, Aerospace & Defense (2003-2010)

$70,000 $59,366 $60,000

$46,546 $50,000 $53,510

$40,000 $41,132 $30,000

$10,000

$0 2003 2004 2005 2006 2007 2008 2009 2010

Aerospace & Defense Economy Linear (Aerospace & Defense) Linear (Economy)

Source: U.S. Census Bureau, Richard Florida's "The Rise of the Creative Class", Deloitte Analysis

Source: US Census Bureau, Richard Florida's "The Rise of the Creative Class", Deloitte Analysis

174

Updated

Exhibit 7: Percentage participation in Inter-Firm knowledge flows, Aerospace & Defense, (2011) Appendix — Defense & Aerospace Exhibit 7: Percentage participation in Inter-Firm knowledge flows, Aerospace & Defense (2011)

50% 46% 55% Firm - 39% 40% 37% 36% 33% 33% 38% 38% 31% 36% 30% 31% 28% 19% 25% 20% 20%

10% Percentage participationin Inter knowledge flows,knowledge participationby type 0% Email Alerts Community Lunch Meetings Web-Casts Professional Telephone Social Media Conferences Organizations Organizations

Aerospace & Defense Economy

Source:Source: Synovate Synovate,, Deloitte Deloitte Analysis Analysis A71

Updated

Exhibit 8: Worker Passion, Aerospace & Defense, (2010) Exhibit 8: Worker Passion, Aerospace & Defense (2010)

40%

31% 31%

30% 25% 24% 24% 23% 21% 21% 20%

Percentage of employees, by Passion category 0% Disengaged Passive Engaged Passionate

2010 2011 Economy Source: Synovate, Deloitte Analysis

Source: Synovate, Deloitte Analysis

2011 Shift Index Measuring the forces of long-term change 175

Exhibit 9: Competitive Intensity, Automotive, (1965-2010) Exhibit 9: Competitive Intensity, Automotive (1965-2010)

0.18

0.16 0.16

0.14

0.12 0.14 0.10 0.11 0.08

Herfindahl Index 0.07 0.06

0.04 0.03 0.02

0.00 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010

Automotive Economy Linear (Automotive) Linear (Economy)

Source:Source: Compustat Compustat,, Deloitte Deloitte Analysis analysis

HHI Value Industry Concentration Competitive Intensity < .01 Highly Un-concentrated Very High A2 0 - 0.10 Un-concentrated High

0.10 - 0.18 Moderate Concentration Moderate

0.18 - 1 High Concentration Low

Exhibit 10: Labor Productivity, Automotive, (1987-2010) D Exhibit 10: Labor Productivity, Automotive (1987-2010)

120

100 81.9

60 72.8 Productivity Index 40

0 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Automotive Economy Linear (Automotive) Linear (Economy) Source: Bureau of Labor Statistics, Deloitte analysis Source: Bureau of Labor Statistics, Deloitte Analysis

176

Exhibit 11: Asset Profitability, Automotive, (1965-2010)) Appendix — Automotive Exhibit 11: Asset Profitability, Automotive (1965-2010)

12% 10.1% 10%

6% 6.7%

4% 4.2% 3.1% 2% 1.0%

Return on Assets (%) 0% 0.3% 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 -2%

-4% Automotive Economy A4 Linear (Automotive) Linear (Economy)

Source:Source: Compustat Compustat,, Deloitte Deloitte Analysis analysis D

Exhibit 12: Asset Profitability Top Quartile and Bottom Quartile, Automotive, (1965-2010) Exhibit 12: Asset Profitability Top Quartile and Bottom Quartile, Automotive (1965-2010)

2009: 33.9% 20%

16.2% 15%

10% 11.7% 9.9%

Top Quartile Linear (Top Quartile)

5% 2.8% Return on Assets (%)ReturnAssetson 0% 2.7%

-5% -5.3%

-10%

-15%

-20% 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010

Bottom Quartile Linear (Bottom Quartile)

Source: Compustat, Deloitte analysis

2011 Shift Index Measuring the forces of long-term change 177

Source: Compustat, Deloitte analysis

Exhibit 13: Firm Topple, Automotive, (1966-2010) Exhibit 13: Firm Topple, Automotive (1966-2010)

0.80

0.70

0.60 0.56 0.55 0.43 0.50

0.40

Topple Rate 0.30 0.37

0.20

0.10

0.00 1966 1970 1974 1978 1982 1986 1990 1994 1998 2002 2006 2010 A6 Automotive Economy Linear (Automotive) Linear (Economy)

Source:Source: Compustat Compustat,, Deloitte Deloitte Analysis analysis D

Exhibit 14: Returns to Talent, Automotive, (2003-2010) Exhibit 14: Returns to Talent, Automotive (2003-2010)

$70,000 $59,366 $60,000

$50,000 $46,546 $52,760 $40,000 $44,119

$30,000

$10,000

$0 2003 2004 2005 2006 2007 2008 2009 2010

Automotive Economy Linear (Automotive) Linear (Economy)

Source:Source: US U.S. Census Census Bureau, Bureau, Richard Richard Florida's Florida's "The RiseThe Riseof the of Creative the Creative Class", Class Deloitte, Deloitte Analysis analysis

178

Exhibit 15: Percentage participation in Inter-Firm knowledge flows, Automotive, (2011) Appendix — Automotive Exhibit 15: Percentage participation in Inter-Firm knowledge flows, Automotive (2011)

50% 46%

40% 39% 37% 36% 33%

Firm knowledge 33% - 31% 34% 30% 33% 34% 30% 26% 26% 19% 20% 23%

flows, by participation type 15% 10%

Percentage participationin Inter 0% Email Alerts Community Lunch Meetings Web-Casts Professional Telephone Social Media Conferences Organizations Organizations A8

Automotive Economy Source: Synovate, Deloitte analysis Source: Synovate, Deloitte Analysis D

Exhibit 16: Worker Passion, Automotive, (2010) Exhibit 16: Worker Passion, Automotive (2010)

40%

31% 31% 30% 25% 24% 24% 23% 21% 21% 20%

Percentage of employees, by Passion category 0% Disengaged Passive Engaged Passionate

2010 2011 Economy

Source:Source: Synovate Synovate,, Deloitte Deloitte Analysis analysis

2011 Shift Index Measuring the forces of long-term change 179

Exhibit 17: Competitive Intensity, Banking & Securities, (1965-2010) Exhibit 17: Competitive Intensity, Banking & Securities (1965-2010)

0.16

0.14 0.14

0.12

0.10 0.11

0.08

Herfindahl Index 0.06

0.04 0.03 0.02 0.02 0.02

0.00 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010

Banking & Securities Economy Linear (Banking & Securities) Linear (Economy) Source: Compustat, Deloitte analysis Source: Compustat, Deloitte Analysis

HHI Value Industry Concentration Competitive Intensity

< .01 Highly Un-concentrated Very High A10

0 - 0.10 Un-concentrated High

0.10 - 0.18 Moderate Concentration Moderate

0.18 - 1 High Concentration Low

Exhibit 18: Labor Productivity, Banking & Securities, (1987-2010) D Exhibit 18: Labor Productivity, Banking & Securities (1987-2010)

160 144.9

100 81.9

80 68.4 60 Productivity Index 40

0 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Banking & Securities Economy Linear (Banking & Securities) Linear (Economy)

Source:Source: Bureau Bureau of ofLabor Labor Statistics, Statistics, Deloitte Deloitte Analysis analysis

180

Exhibit 19: Asset Profitability of Sub-Sectors, Banking & Securities, (1965-2010) Appendix Banking & Securities Exhibit 19: Asset Profitability of Sub-Sectors, Banking & Securities (1965-2010)

4% 4.2%

2% 1.9%

1% 1.0% 0.6% 0.6% Return on Assets (%) 0% 0.001% 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010

-1% Banking Securities Economy Linear (Banking) Linear (Securities) Linear (Economy) A12 Source:Source: Compustat Compustat,, Deloitte Deloitte Analysis analysis

Exhibit 20: Asset Profitability Top Quartile and Bottom Quartile, Banking & Securities, (1965-2010) Exhibit 20: Asset Profitability Top Quartile and Bottom Quartile, Banking & Securities (1965-2010)

1.5% 2% 1.1%

1% 1.0%

Top Quartile Linear (Top Quartile)

1% 0.4% Return on Assets (%)ReturnAssetson 1% 0%

-1%

-1% 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010

Bottom Quartile Linear (Bottom Quartile) Source: Compustat, Deloitte analysis

2011 Shift Index Measuring the forces of long-term change 181

A13 —

Exhibit 21: Firm Topple of Sub-Sectors, Banking & Securities, (1972-2010) Exhibit 21: Firm Topple of Sub-Sectors, Banking & Securities (1972-2010)

1.0%

0.8%

0.6% 0.55 0.51 0.46

Topple Rate 0.41 0.45 0.4% 0.39

0.2%

0.0% 1972 1975 1978 1981 1984 1987 1990 1993 1996 1999 2002 2005 2008 A14 Banking Securities Economy Linear (Banking) Linear (Securities) Linear (Economy)

Source: Compustat, Deloitte Analysis Source: Compustat, Deloitte analysis D

Exhibit 22: Returns to Talent, Banking & Securities, (2003-2010) Exhibit 22: Returns to Talent, Banking & Securities (2003-2010)

70,000

$65,485 65,000

60,000

50,000 $47,970 Compensation Gap ($)

45,000 $46,546

40,000 2003 2004 2005 2006 2007 2008 2009 2010

Banking & Securities Economy Linear (Banking & Securities) Linear (Economy)

Source: USU.S. Census Census Bureau, Bureau, Richard Richard Florida's Florida's "The The Rise Rise of the of Creativethe Creative Class", Class Deloitte, Deloitte Analysis analysis

182

Exhibit 23: Percentage participation in Inter-Firm knowledge flows, Banking & Securities, (2011) Appendix Banking & Securities Exhibit 23: Percentage participation in Inter-Firm knowledge flows, Banking & Securities (2011)

50% 46% 49% 39% 40% 37% 36% 41% 33% 33% 40% 31%

Firm knowledge 37% - 34% 30% 29% 29% 19% 20% 22%

flows by participation type 10%

Percentage participationin Inter 0% Email Alerts Community Lunch Meetings Web-Casts Professional Telephone Social Media Conferences Organizations Organizations A16

Banking & Securities Economy

Source: SynovateSynovate,, Deloitte Deloitte Analysis analysis D

Exhibit 24: Worker Passion, Banking & Securities, (2010)

Exhibit 24: Worker Passion, Banking & Securities (2010, 2011)

40%

31% 31% 30% 25% 24% 24% 23% 21% 21% 20%

Percentage of employees, by Passion category 0% Disengaged Passive Engaged Passionate

2010 2011 Economy Source: Synovate, Deloitte analysis Source: Synovate, Deloitte Analysis

2011 Shift Index Measuring the forces of long-term change 183

Exhibit 25: Competitive Intensity, Consumer Products, (1965-2010) Exhibit 25: Competitive Intensity, Consumer Products (1965-2010)

0.16

0.14 0.14

0.12

0.10 0.11

0.08

Herfindahl Index 0.06

0.04 0.03

0.02 0.01 0.02 0.00 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010

Consumer Proudcts Economy Linear (Consumer Proudcts) Linear (Economy)

Source: CompustatCompustat,, Deloitte Deloitte Analysis analysis

HHI Value Industry Concentration Competitive Intensity

< .01 Highly Un-concentrated Very High 0 - 0.10 Un-concentrated High A18 0.10 - 0.18 Moderate Concentration Moderate

0.18 - 1 High Concentration Low

Exhibit 26: Labor Productivity, Consumer Products, (1987-2010) D Exhibit 26: Labor Productivity, Consumer Products (1987-2010)

180

120

100 81.9

60 68.1 Productivity Index

0 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Consumer Products Economy Linear (Consumer Products) Linear (Economy)

Source:Source: Bureau Bureau of ofLabor Labor Statistics, Statistics, Deloitte Deloitte Analysis analysis

184

Exhibit 27: Asset Profitability, Consumer Products, (1965-2010)) Appendix — Consumer Products Exhibit 27: Asset Profitability, Consumer Products (1965-2010)

9% 8.0% 8% 7.2% 7% 6.5% 6% 6.1% 5%

4% 4.2% 3%

Return on Assets (%) 2% 1.0% 1%

0% 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010

Consumer Products Economy Linear (Consumer Products) Linear (Economy) A20

Source: Compustat, Deloitte analysis Source: Compustat, Deloitte Analysis D

Exhibit 28: Asset Profitability Top Quartile and Bottom Quartile, Consumer Products, (1965-2010) Exhibit 28: Asset Profitability Top Quartile and Bottom Quartile, Consumer Products (1965-2010)

15.00% 14.0%

13.75% 13.0% 12.4% 12.50%

10.00% Top Quartile Linear (Top Quartile)

10% 6.0% 5% 2.6% Return on Assets (%)ReturnAssetson

0% -0.13% -5%

-10% -9.0% -15%

-20%

-25% 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010

Bottom Quartile Linear (Bottom Quartile)

Source:Source: Compustat Compustat,, Deloitte Deloitte analysis analysis

2011 Shift Index Measuring the forces of long-term change 185

A21

Exhibit 29: Firm Topple, Consumer Products, (1966-2010) Exhibit 29: Firm Topple, Consumer Products (1966-2010)

0.80

0.70

0.60 0.55 0.49 0.50 0.39 0.40 Topple Rate 0.30 0.37

0.20

0.10

0.00 1966 1970 1974 1978 1982 1986 1990 1994 1998 2002 2006 2010 Consumer Products Economy Linear (Consumer Products) Linear (Economy) A22 Source:Source: Compustat Compustat,, Deloitte Deloitte Analysis analysis

Exhibit 30: Returns to Talent, Consumer Products, (2003-2010) Exhibit 30: Returns to Talent, Consumer Products (2003-2010)

$70,000

$59,366 $60,000

$50,000 $46,546 $53,575

$40,000 $45,803

$0 2003 2004 2005 2006 2007 2008 2009 2010

Consumer Products Economy Linear (Consumer Products) Linear (Economy)

Source: U.S. Census Bureau, Richard Florida's The Rise of the Creative Class, Deloitte analysis Source: US Census Bureau, Richard Florida's "The Rise of the Creative Class", Deloitte Analysis

186

Exhibit 31: Percentage participation in Inter-Firm knowledge flows, Consumer Products, (2011) Appendix — Consumer Products Exhibit 31: Percentage participation in Inter-Firm knowledge flows, Consumer Products (2011)

50% 46%

39% 40% 37% 36% 43% 33% 33% 31% 37% Firm knowledge - 35% 30% 31% 31% 30% 19% 20% 23%

18%

flows by participation type 10%

Percentage participationin Inter 0% Email Alerts Community Lunch Meetings Web-Casts Professional Telephone Social Media Conferences Organizations Organizations

Consumer Products Economy A24

Source:Source: Synovate Synovate,, Deloitte Deloitte Analysis analysis

Exhibit 32: Worker Passion, Consumer Products, (2010) Exhibit 32: Worker Passion, Consumer Products (2010), 2011

40%

31% 31% 30%

10% Percentage of employees, by Passion category 0% Disengaged Passive Engaged Passionate

2010 2011 Economy

Source:Source: Synovate Synovate,, Deloitte Deloitte Analysis analysis

2011 Shift Index Measuring the forces of long-term change 187

Exhibit 33: Competitive Intensity, Energy, (1965-2010) Exhibit 33: Competitive Intensity, Energy (1965-2010)

0.16

0.14 0.14

0.12

0.10 0.11 0.08

Herfindahl Index 0.06

0.04 0.03 0.03

0.02 0.03

0.00 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010

Energy Economy Linear (Energy) Linear (Economy)

Source: Compustat, Deloitte analysis Source: Compustat, Deloitte Analysis

HHI Value Industry Concentration Competitive Intensity

< .01 Highly Un-concentrated Very High 0 - 0.10 Un-concentrated High A65 0.10 - 0.18 Moderate Concentration Moderate

0.18 - 1 High Concentration Low

Exhibit 34: Labor Productivity, Energy, (1987-2010) D Exhibit 34: Labor Productivity, Consumer Products (1987-2010)

160

100 81.9

80 81.0 60

Productivity Index 40

0 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Energy Economy Linear (Energy) Linear (Economy)

Source:Source: Bureau Bureau of ofLabor Labor Statistics, Statistics, Deloitte Deloitte Analysis analysis

188

Exhibit 35: Asset Profitability, Energy, (1965-2010) Appendix — Energy Exhibit 35: Asset Profitability, Energy (1965-2010)

5% 4.7%

4.3% 4% 4.2% 3%

2% Return on Assets (%) 1% 1.0%

0% 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 A67

Energy Economy Linear (Energy) Linear (Economy)

Source: Compustat, Deloitte Analysis Source: Compustat, Deloitte analysis D

Exhibit 36: Asset Profitability Top Quartile and Bottom Quartile, Energy, (1965-2010)

15.00% Exhibit 36: Asset Profitability Top Quartile and Bottom Quartile, Energy (1965-2010)

12.50%

10.00% 8.6%

7.50%

20% Return on Assets (%)ReturnAssetson 0% 0.1%

-5.6% -20%

-40% 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010

Bottom Quartile Linear (Bottom Quartile)

Source:Source: Compustat Compustat,, Deloitte Deloitte analysis analysis

2011 Shift Index Measuring the forces of long-term change 189

A68

Exhibit 37: Firm Topple, Energy, (1966-2010) Exhibit 37: Firm Topple, Energy (1966-2010)

0.80

0.70

0.60 0.57 0.54 0.50

0.39 0.40

Topple Rate 0.30 0.35

0.20

0.10

0.00 1966 1970 1974 1978 1982 1986 1990 1994 1998 2002 2006 2010

Energy Economy Linear (Energy) Linear (Economy) A69 Source: Compustat, Deloitte analysis Source: Compustat, Deloitte Analysis D

Exhibit 38: Returns to Talent, Energy, (2003-2010) Exhibit 38: Returns to Talent, Energy (2003-2010)

$70,000 $64,534

$60,000 $52,430 $59,366 $50,000

$40,000 $46,546

$10,000

$0 2003 2004 2005 2006 2007 2008 2009 2010

Energy Economy Linear (Energy) Linear (Economy)

Source: US Census Bureau, Richard Florida's "The Rise of the Creative Class", Deloitte Analysis Source: US Census Bureau, Richard Florida's "The Rise of the Creative Class", Deloitte Analysis

190

Updated

Exhibit 39: Percentage participation in Inter-Firm knowledge flows, Energy, (2011) Appendix — Energy Exhibit 39: Percentage participation in Inter-Firm knowledge flows, Energy (2011) • Please use the exhibit to 50% 46% 57% replace the previous 48% 39% 46% exhibit named “Inter-firm 40% 37% 36% 33% 33% Knowledge Flow Index 31% 38% Firm knowledge - Values” 30% 32% 31% 29% • Adjust the bar color to 19% make it consistent with 20% 22% the exhibits in the other sections flows by participation type 10% • Please adjust the lines for economy based on 0% Percentage participationin Inter Email Alerts Community Lunch Meetings Web-Casts Professional Telephone Social Media Conferences Organizations Organizations the data A71 Energy Economy Source: Compustat, Deloitte analysis Source: Synovate, Deloitte Analysis Updated

Exhibit 40: Worker Passion, Energy, (2010) Exhibit 40: Worker Passion, Energy (2010, 2011)

40%

31% 31% 30% 25% 24% 24% 23% 21% 21% 20%

Percentage of employees, by Passion category 0% Disengaged Passive Engaged Passionate

2010 2011 Economy

Source:Source: Synovate Compustat,, Deloitte Deloitte Analysis analysis

2011 Shift Index Measuring the forces of long-term change 191

Start 1972

Exhibit 41: Competitive Intensity, Healthcare Services, (1972-2010) Exhibit 41: Competitive Intensity, Health Care Services (1972-2010)

0.35

0.30 0.32

0.25

0.20

0.15 Herfindahl Index 0.09 0.10 0.08

0.05 0.05 0.04

0.00 0 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010

Healthcare Services Economy Linear (Healthcare Services ) Linear (Economy)

Source: CompustatCompustat,, Deloitte Deloitte Analysis analysis

HHI Value Industry Concentration Competitive Intensity

< .01 Highly Un-concentrated Very High

0 - 0.10 Un-concentrated High 0.10 - 0.18 Moderate Concentration Moderate A26 0.18 - 1 High Concentration Low

Exhibit 42: Labor Productivity, Healthcare Services, (1994-2010) Exhibit 42: Labor Productivity, Health Care Services (1994-2010)

120 96.4 100

80 94.9

60 Productivity Index 40

0 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Healthcare Services Economy Linear (Healthcare Services ) Linear (Economy)

Source:Source: Bureau Bureau of ofLabor Labor Statistics, Statistics, Deloitte Deloitte Analysis analysis

192

D Appendix — Health Care ExhibitExhibit 43: 43:Asset Asset Profitability Profitability of of Sub Sub-Sectors,-Sectors, Healthcare Health Services,Care Services (1972-2010) (1972-2010)

3.7% 4% 3.2%

3.5% 2.3% 2% 0% 1.0% 0% 1972 1977 1982 1987 1992 1997 2002 2007

-2% Return on Assets (%) -4%

-6%

-8% Plans Providers Economy A28 Linear (Providers) Linear (Economy)

Source:Source: Compustat, Compustat Deloitte, Deloitte analysis Analysis D

Exhibit 44: Asset Profitability Top Quartile and Bottom Quartile, Healthcare Services, (1965-2010) Exhibit 44: Asset Profitability Top Quartile and Bottom Quartile, Health Care Services (1965-2010)

15%

10% 9.5%

9.3%

Top Quartile Linear (Top Quartile)

-5% Return on Assets (%)ReturnAssetson -15% -6.3%

-25% -19.2%

-35%

-45%

-55%

-65% 1972 1977 1982 1987 1992 1997 2002 2007

Bottom Quartile Linear (Bottom Quartile)

Source: Compustat, Deloitte analysis

2011 Shift Index Measuring the forces of long-term change 193

Source: Compustat, Deloitte analysis

A29

Exhibit 45: Firm Topple of Sub-Sectors, Healthcare Services, (1983-2010) Exhibit 45: Firm Topple of Sub-Sectors, Health Care Services (1983-2010)

3.50

3.00

2.50

2.00

1.50 1.0 Topple Rate

1.00 0.6 0.7

0.50 0.6 0.4 0.6 0.00 1983 1986 1989 1992 1995 1998 2001 2004 2007 2010

Health Plans Providers Economy Linear (Health Plans) Linear (Providers) Linear (Economy) A30

Source:Source: Compustat Compustat,, Deloitte DeloitteAnalysis analysis D

Exhibit 46: Returns to Talent, Healthcare Services, (2003-2010) Exhibit 46: Returns to Talent, Health Care Services (2003-2010)

$70,000 $59,366 $60,000

$50,000 $46,546

$10,000

$0 2003 2004 2005 2006 2007 2008 2009 2010

Healthcare Services Economy

Source:Source: US CensusU.S. Census Bureau, Bureau, Richard Richard Florida's Florida's "The Rise The of Risethe Creative of the Creative Class", Deloitte Class, AnalysisDeloitte analysis

194

Exhibit 47: Percentage participation in Inter-Firm knowledge flows, Healthcare Services, (2011) Appendix — Health Care Exhibit 47: Percentage participation in Inter-Firm knowledge flows, Health Care Services (2011)

50% 46% 61% Firm

- 39% 45% 46% 40% 37% 41% 36% 38% 33% 33% 31% 30% 34% 32%

19% 20%

10% 12% Percentage participationin Inter knowledge flowsknowledge participation by type 0% Email Alerts Community Lunch Meetings Web-Casts Professional Telephone Social Media Conferences Organizations Organizations Healthcare Services Economy A32 Source:Source: Synovate Synovate,, Deloitte Deloitte Analysis analysis

Exhibit 48: Worker Passion, Healthcare Services, (2010) Exhibit 48: Worker Passion, Health Care Services (2010, 2011)

40%

31% 31% 30% 25% 24% 24% 23% 21% 21% 20%

Percentage of employees, by Passion category 0% Disengaged Passive Engaged Passionate

2010 2011 Economy Source: Synovate, Deloitte analysis Source: Synovate, Deloitte Analysis

2011 Shift Index Measuring the forces of long-term change 195

Exhibit 49: Competitive Intensity, Insurance, (1965-2010) Exhibit 49: Competitive Intensity, Insurance (1965-2010)

0.50 0.45 0.44 0.40 0.35 0.30 0.25 0.20 0.16 0.15 Herfindahl Index 0.10 0.11 0.03 0.05 0.00 -0.01 -0.05 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010

Insurance Economy Linear (Insurance) Linear (Economy)

Source: CompustatCompustat,, Deloitte Deloitte Analysis analysis

HHI Value Industry Concentration Competitive Intensity < .01 Highly Un-concentrated Very High A34 0 - 0.10 Un-concentrated High

0.10 - 0.18 Moderate Concentration Moderate 0.18 - 1 High Concentration Low D

Exhibit 50: Asset Profitability of Sub-Sectors, Insurance, (1972-2010) Exhibit 50: Asset Profitability of Sub-Sectors, Insurance (1972-2010)

8.0%

3.7% 4.0% 3.1% 2.5%

2.0% 1.0%

0.4% Herfindahl Index 0.3%

0.0% 1972 1976 1980 1984 1988 1992 1996 2000 2004 2008

-2.0% Life Insurance P&C Insurance Brokers Economy Linear (Life Insurance) Linear (P&C Insurance) Linear (Brokers) Linear (Economy) -4.0%

Source:Source: Compustat Compustat,, Deloitte Deloitte Analysis analysis 196

Check data labels

Exhibit 51: Asset Profitability Top Quartile and Bottom Quartile, Insurance, (1965-2010) Appendix — Insurance Exhibit 51: Asset Profitability Top Quartile and Bottom Quartile, Insurance (1965-2010)

25%

20%

15%

10% 6.6% 5% 6.2%

0% Life Insurance P&C Insurance Broker Linear (Life Insurance) Linear (P&C Insurance) Linear (Broker)

10%

0% Return on Assets (%)ReturnAssetson 0.2% -10% -11.0% -20%

-30%

-40%

-50% 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 A36 Life Insurance P&C Insurance Broker Linear (Life Insurance) Linear (P&C Insurance) Linear (Broker)

Source: Compustat, Deloitte analysis D – no data available Source: Compustat, Deloitte analysis for Brokers Exhibit 52: Firm Topple of Sub-Sectors, Insurance, (1973-2010) Exhibit 52: Firm Topple of Sub-Sectors, Insurance (1973-2010)

0.8

0.7

0.6 0.55 0.5 0.54 0.5 0.41 0.52 0.4

0.3 Topple Rate 0.2 0.32

0.1

0.0 1973 1976 1979 1982 1985 1988 1991 1994 1997 2000 2003 2006 2009

Life Insurance P&C Insurance Economy Linear (Life Insurance) Linear (P&C Insurance) Linear (Economy)

Source:Source: Compustat Compustat,, Deloitte Deloitte Analysis analysis

2011 Shift Index Measuring the forces of long-term change 197

A37

Exhibit 53: Returns to Talent, Insurance, (2003-2010) Exhibit 53: Returns to Talent, Insurance (2003-2010)

$70,000 $59,366 $60,000 $55,808 $50,000 $46,546

$40,000 $33,989

$30,000 Compensation Gap ($) $20,000

$10,000

$0 2003 2004 2005 2006 2007 2008 2009 2010

Insurance Economy A38 Linear (Insurance) Linear (Economy) Source: U.S. Census Bureau, Richard Florida's The Rise of the Creative Class, Deloitte analysis Source: US Census Bureau, Richard Florida's "The Rise of the Creative Class", Deloitte Analysis Updated

Exhibit 54: Percentage participation in Inter-Firm knowledge flows, Insurance, (2011) Exhibit 54: Percentage participation in Inter-Firm knowledge flows, Insurance (2011)

50% 46%

39% 46% Firm - 40% 37% 41% 36% 40% 33% 33% 31% 37% 35% 30% 33%

10% Percentage participationin Inter knowledge flowsknowledge participation by type

0% Email Alerts Community Lunch Meetings Web-Casts Professional Telephone Social Media Conferences Organizations Organizations

Insurance Economy Source: Synovate, Deloitte analysis Source: Synovate, Deloitte Analysis

198

Updated

Exhibit 55: Worker Passion, Insurance, (2010) Appendix — Insurance Exhibit 55: Worker Passion, Insurance (2010, 2011)

40%

31% 31% 30% 25% 24% 24% 23% 21% 21% 20%

10%

Percentage of employees, by Passion category 0% Disengaged Passive Engaged Passionate

2010 2011 Economy

Source:Source: Synovate Synovate,, Deloitte Deloitte Analysis analysis

2011 Shift Index Measuring the forces of long-term change 199 Life Sciences — Appendix Life Sciences A64

Exhibit 56: Competitive Intensity, Life Sciences, (1965-2010) Exhibit 56: Competitive Intensity, Life Sciences (1965-2010)

0.16

0.14 0.14 0.12 0.11 0.10

0.08

Herfindahl Index 0.06

0.04 0.03 0.02 0.03 0.03

0.00 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010

Life Sciences Economy Linear (Life Sciences) Linear (Economy)

Source: CompustatCompustat,, Deloitte Deloitte Analysis analysis

HHI Value Industry Concentration Competitive Intensity

< .01 Highly Un-concentrated Very High 0 - 0.10 Un-concentrated High A65 0.10 - 0.18 Moderate Concentration Moderate

0.18 - 1 High Concentration Low

Exhibit 57: Labor Productivity, Life Sciences, (1987-2010) D Exhibit 57: Labor Productivity, Life Sciences (1987-2010)

160

100 89.4 101.8 80 81.9 60 Productivity Index 40

0 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Life Sicences Economy Linear (Life Sicences) Linear (Economy)

Source:Source: Bureau Bureau of ofLabor Labor Statistics, Statistics, Deloitte Deloitte Analysis analysis

200

D Appendix — Life Sciences Exhibit 58: Asset Profitability, Life Sciences, (1965-2010) Exhibit 58: Asset Profitability, Life Sciences (1965-2010)

12%

10% 9.6% 8%

6% 6.7%

4% 4.2% Return on on Return Assets (%) 2% 1.0% 0% 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 Life Sciences Economy Linear (Life Sciences) Linear (Economy) A67 Source:Source: Compustat Compustat,, Deloitte Deloitte Analysis analysis

Exhibit 59: Asset Profitability Top Quartile and Bottom Quartile, Life Sciences, (1965-2010) Exhibit 59: Asset Profitability Top Quartile and Bottom Quartile, Life Sciences (1965-2010)

20%

15% 15.5%

10% 11.0%

Top Quartile Linear (Top Quartile)

20%

Return on Assets (%) on Return 0% 2.7% 1.6% -20%

-40%

-60%

-80%

-100% -86.6% -120% 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010

Bottom Quartile Linear (Bottom Quartile) Source: Compustat, Deloitte analysis Source: Compustat, Deloitte analysis

2011 Shift Index Measuring the forces of long-term change 201

A68

Exhibit 60: Firm Topple, Life Sciences, (1966-2010) Exhibit 60: Firm Topple, Life Sciences (1966-2010)

0.80

0.70

0.60 0.60 0.54 0.50 0.39 0.40 Topple Rate 0.30 0.30 0.20

0.10

0.00 1966 1970 1974 1978 1982 1986 1990 1994 1998 2002 2006 2010

Life Sciences Economy Linear (Life Sciences) Linear (Economy) A69

Source:Source: Compustat Compustat,, Deloitte Deloitte Analysis analysis

Exhibit 61: Returns to Talent, Life Sciences, (2003-2010) Exhibit 61: Returns to Talent, Life Sciences (2003-2010)

$80,000 $73,588

$70,000

$56,015 $60,000 $59,366 $50,000

$40,000 $46,546

$10,000

$0 2003 2004 2005 2006 2007 2008 2009 2010

Life Sciences Economy Linear (Life Sciences) Linear (Economy)

Source:Source: US Census Bureau Bureau, of Labor Richard Statistics, Florida's Deloitte "The Riseanalysis of the Creative Class", Deloitte Analysis

202

Updated

Exhibit 62: Percentage participation in Inter-Firm knowledge flows, Life Sciences, (2011) Appendix — Life Sciences Exhibit 62: Percentage participation in Inter-Firm knowledge flows, Life Sciences (2011) • Please use the exhibit to 50% 58% 46% replace the previous Firm

- 39% exhibit named “Inter-firm 40% 37% 41% 36% 33% 33% 38% Knowledge Flow Index 31% 36% 37% 38% 30% Values” 30% • Adjust the bar color to 19% 20% 21% make it consistent with the

10% exhibits in the other sections Percentage participation in participation Percentage Inter knowledge flows by participation type 0% • Please adjust the lines for Email Alerts Community Lunch Meetings Web-Casts Professional Telephone Social Media Conferences Organizations Organizations economy based on the

Life Sciences Economy data Source: Synovate, Deloitte analysis Source: Synovate, Deloitte Analysis A71

Updated

Exhibit 63: Worker Passion, Life Sciences, (2010) Exhibit 63: Worker Passion, Life Sciences (2010, 2011)

40%

31% 31% 30% 25% 24% 24% 23% 21% 21% 20%

10% Percentage of of by Percentage employees, category Passion 0% Disengaged Passive Engaged Passionate

2010 2011 Economy Source:Source: Synovate Synovate,, Deloitte Deloitte Analysis analysis

2011 Shift Index Measuring the forces of long-term change 203

Exhibit 64: Competitive Intensity, Media & Entertainment, (1965-2010) Exhibit 64: Competitive Intensity, Media & Entertainment (1965-2010)

0.16

0.14 0.14 0.12

0.10 0.11 0.08

Herfindahl Index 0.06 0.05 0.04 0.03 0.02 0.02 0.00 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010

Media & Entertainment Economy Linear (Media & Entertainment) Linear (Economy)

Source:Source: CompustatCompustat,, Deloitte Deloitte Analysis analysis

HHI Value Industry Concentration Competitive Intensity

< .01 Highly Un-concentrated Very High

0 - 0.10 Un-concentrated High

0.10 - 0.18 Moderate Concentration Moderate 0.18 - 1 High Concentration Low A41

ExhibitExhibit 65: 65: Labor Labor Productivity, Productivity, Media Media& Entertainment, & Entertainment (1987-2010) (1987-2010) D

120 94.9 115.3 100

80 81.9 60 Productivity Index 40

0 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Media & Entertainment Economy Linear (Media & Entertainment) Linear (Economy)

Source:Source: Bureau Bureau of ofLabor Labor Statistics, Statistics, Deloitte Deloitte Analysis analysis

204

D Appendix — Media & Entertainment Exhibit 66: Asset Profitability, Media & Entertainment, (1965-2010) Exhibit 66: Asset Profitability, Media & Entertainment (1965-2010)

10%

8% 7.2%

4% 4.2% 2% 1.1% 0% -0.04% 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 -2%

Return on on Return Assets (%) -4%

-6%

-8% Media & Entertainment Economy Linear (Media & Entertainment ) Linear (Economy)

Source: Compustat, Deloitte analysis A43 Source: Compustat, Deloitte Analysis

ExhibitExhibit 67: Asset67: Asset Profitability Profitability Top Quartile Top and Quartile Bottom andQuartile, Bottom Media Quartile, & Entertainment, Media (1965& Entertainment-2010) (1965-2010)

40%

30% 18.3% 20% 11.3% 10% 9.5% 0%

Top Quartile Linear (Top Quartile)

20% 1.9% Return on Assets (%) on Return 0% 2.4%

-20% -22.8% -40%

-60%

-80% 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010

Bottom Quartile Linear (Bottom Quartile)

Source: Compustat, Deloitte analysis Source: Compustat, Deloitte analysis 2011 Shift Index Measuring the forces of long-term change 205

A44

Exhibit 68: Firm Topple, Media & Entertainment, (1966-2010) Exhibit 68: Firm Topple, Media & Entertainment (1966-2010)

0.80

0.70

0.60 0.55

0.50 0.53 0.37 0.40

Topple Rate 0.34 0.30

0.20

0.10

0.00 1966 1970 1974 1978 1982 1986 1990 1994 1998 2002 2006 2010

Media & Entertainment Economy Linear (Media & Entertainment) Linear (Economy)

Source:Source: Compustat Compustat,, Deloitte Deloitte Analysis analysis A45

Exhibit 69: Returns to Talent, Media & Entertainment, (2003-2010) Exhibit 69: Returns to Talent, Media & Entertainment (2003-2010)

$70,000 $63,822

$60,000 $59,366 $50,000 $46,546

$40,000 $44,066

$30,000

$10,000

$0 2003 2004 2005 2006 2007 2008 2009 2010

Media & Entertainment Economy Linear (Media & Entertainment) Linear (Economy)

Source: U.S. Census Bureau, Richard Florida's The Rise of the Creative Class, Deloitte analysis Source: US Census Bureau, Richard Florida's "The Rise of the Creative Class", Deloitte Analysis

206

Updated Appendix — Media & Entertainment Exhibit 70: Percentage participation in Inter-Firm knowledge flows, Media & Entertainment, (2011) Exhibit 70: Percentage participation in Inter-Firm knowledge flows, Media & Entertainment (2011) • Please use the exhibit to 50% 46% replace the previous exhibit named “Inter-firm 39% 45% 40% 37% 36% Knowledge Flow Index 33% 33% 39% 31% 38% Values” 30% 32% 33% Firm knowledge flows • Adjust the bar color to

- 31% 27% make it consistent with 19% 20% the exhibits in the other 18%

by participation type sections 10% • Please adjust the lines for economy based on the 0% data

Percentage participation in participation Percentage Inter Google Alerts Community Lunch Meetings Web-Casts Professional Telephone Social Media Conferences Organizations Organizations

Media & Entertainment Economy

Source:Source: Synovate Synovate,, Deloitte Deloitte Analysis analysis A47

Updated

Exhibit 71: Worker Passion Media & Entertainment, (2010) Exhibit 71: Worker Passion, Media & Entertainment (2010, 2011)

40%

10% Percentage of of by Percentage employees, category Passion 0% Disengaged Passive Engaged Passionate

2010 2011 Economy Source: Synovate, Deloitte analysis Source: Synovate, Deloitte Analysis

2011 Shift Index Measuring the forces of long-term change 207

Exhibit 72: Competitive Intensity , Process & Industrial Products, (1965-2010) Exhibit 72: Competitive Intensity , Process & Industrial Products (1965-2010)

0.16

0.14 0.14

0.12 0.11 0.10

0.08

Herfindahl Index 0.06 0.05

0.04 0.11 0.02 0.01 0.01 0.00 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010

Process & Industrial Products Economy Linear (Process & Industrial Products) Linear (Process & Industrial Products)

Source:Source: Compustat,Compustat, Deloitte Deloitte Analysis analysis

HHI Value Industry Concentration Competitive Intensity

< .01 Highly Un-concentrated Very High

0 - 0.10 Un-concentrated High

0.10 - 0.18 Moderate Concentration Moderate

0.18 - 1 High Concentration Low A65

Exhibit 73: Labor Productivity, Process & Industrial Products, (1987-2010) D Exhibit 73: Labor Productivity, Process & Industrial Products (1987-2010)

120 130.6 100 81.9

80 81.1 60 Productivity Index 40

0 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Process & Industrial Products Economy Linear (Process & Industrial Products) Linear (Economy)

Source:Source: Bureau Bureau of ofLabor Labor Statistics, Statistics, Deloitte Deloitte Analysis analysis

208

A66

D Appendix — Process & Industrial Products ExhibitExhibit 74: 74: Asset Asset Profitability, Profitability, Process Process & Industrial & Industrial Products, (1965Products-2010) (1965-2010)

8% 7.1% 7%

6% 5.5% 5.1% 5%

4% 4.2% 3% 2.9%

2% Return on on Return Assets (%) 1% 1.0%

0% 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010

Process & Industrial Products Economy A67 Linear (Process & Industrial Products) Linear (Economy)

Source:Source: Compustat Compustat,, Deloitte Deloitte Analysis analysis D

ExhibitExhibit 75: 75:Asset Asset Profitability Profitability Top Quartile Top andQuartile Bottom and Quartile, Bottom Process Quartile, & Industrial Process Products, & Industrial(1965-2010) Products (1965-2010)

20%

11.2%

10%

10.0%

20% Return on Assets (%) on Return

0% 2.3%

-20% -15.6%

-40% 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010

Bottom Quartile Linear (Bottom Quartile) Source: Compustat, Deloitte analysis Source: Compustat, Deloitte analysis

2011 Shift Index Measuring the forces of long-term change 209

A68

ExhibitExhibit 76: 76: Firm Firm Topple, Topple, Process Process & Industrial & Industrial Products, Products (1966-2010) (1966-2010)

0.80

0.70

0.60 0.57 0.54 0.50 0.40

0.40 Topple Rate 0.30 0.39

0.20

0.10

0.00 1966 1970 1974 1978 1982 1986 1990 1994 1998 2002 2006 2010

Process & Industrial Products Economy Linear (Process & Industrial Products) Linear (Economy)

Source:Source: Compustat Compustat,, Deloitte Deloitte Analysis analysis

A69

Exhibit 77: Returns to Talent, Process & Industrial Products, (2003-2010) Exhibit 77: Returns to Talent, Process & Industrial Products (2003-2010)

$70,000 $59,366 $60,000

$46,546 $40,000

$30,000

Compensation Gap ($) $20,000

$10,000

$0 2003 2004 2005 2006 2007 2008 2009 2010

Process & Industrial Products Economy Linear (Process & Industrial Products) Linear (Economy)

Source:Source: US Census Bureau Bureau, of Labor Richard Statistics, Florida's Deloitte "The Riseanalysis of the Creative Class", Deloitte Analysis

210 2011 Shift Index Measuring the forces of long-term change 210

Updated

Exhibit 78: Percentage participation in Inter-Firm knowledge flows, Process & Industrial Products, (2011) Appendix — Process & Industrial Products Exhibit 78: Percentage participation in Inter-Firm knowledge flows, Process & Industrial Products (2011)

50% 46%

39% 40% 37% 36% 41% 33% 33% 40% Firm knowledge Firm knowledge

- 31% 36% 35% 30% 34% 31% 29% 19% 25% 20%

flows by participation type 10%

0% Percentage participation in participation Percentage Inter Email Alerts Community Lunch Meetings Web-Casts Professional Telephone Social Media Conferences Organizations Organizations

Process & Industrial Products Economy

Source:Source: Synovate Compustat,, Deloitte Deloitte Analysis analysis A71

Updated

Exhibit 79: Worker Passion, Process & Industrial Products, (2010) Exhibit 79: Worker Passion, Process & Industrial Products (2010, 2011)

40%

10% Percentage of of by Percentage employees, category Passion 0% Disengaged Passive Engaged Passionate

2010 2011 Economy

Source:Source: Synovate Compustat,, Deloitte Deloitte Analysis analysis

2011 Shift Index Measuring the forces of long-term change 211

ExhibitExhibit 80: 80: Competitive Competitive Intensity, Intensity, Retail, Retail(1965-2010) (1965-2010)

0.16

0.14 0.14

0.12

0.10 0.11 0.08 Herfindahl Index 0.06 0.05 0.04 0.03 0.02 0.02 0.00 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010

Retail Economy Linear (Retail) Linear (Economy)

Source:Source: CompustatCompustat,, Deloitte Deloitte Analysis analysis

HHI Value Industry Concentration Competitive Intensity

< .01 Highly Un-concentrated Very High 0 - 0.10 Un-concentrated High A49 0.10 - 0.18 Moderate Concentration Moderate

0.18 - 1 High Concentration Low

Exhibit 81: Labor Productivity, Retail, (1987-2010) D Exhibit 81: Labor Productivity, Retail (1987-2010)

120 81.9 100

80 Productivity Index 60 68.8 40

0 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Retail Economy Linear (Retail) Linear (Economy)

Source: Bureau of Labor Statistics, Deloitte Analysis

Source: Bureau of Labor Statistics, Deloitte analysis

212

D Appendix — Retail Exhibit 82: Asset Profitability, Retail, (1965-2010) Exhibit 82: Asset Profitability, Retail (1965-2010)

7% 6.6% 6.0% 6% 4.9% 5%

4% 4.0% 4.2% 3%

2% Return on on Return Assets (%) 1% 1.0%

0% 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010

Retail Economy A51 Linear (Retail) Linear (Economy)

Source:Source: Compustat Compustat,, Deloitte Deloitte Analysis analysis D

ExhibitExhibit 83: 83: Asset Asset Profitability Profitability Top Quartile Top andQuartile Bottom and Quartile, Bottom Retail, Quartile,(1965-2010) Retail (1965-2010)

15.00%

13.0%

12.50%

10.00% 10.5% 10.2%

Top Quartile Linear (Top Quartile)

10% 5.2% 5%

Return on Assets (%) on Return 0% -0.2% -5%

-10% -10.1% -15%

-20%

-25% 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010

Bottom Quartile Linear (Bottom Quartile)

Source:Source: Compustat Compustat,, Deloitte Deloitte analysis analysis

2011 Shift Index Measuring the forces of long-term change 213

A52

Exhibit 84: Firm Topple, Retail, (1966-2010) Exhibit 84: Firm Topple, Retail (1966-2010)

0.80

0.70

0.60 0.55

0.50 0.37 0.45 0.40 Topple Rate 0.30 0.35

0.20

0.10

0.00 1966 1970 1974 1978 1982 1986 1990 1994 1998 2002 2006 2010

Retail Economy Linear (Retail) Linear (Economy)

Source:Source: Compustat Compustat,, Deloitte Deloitte Analysis analysis A53

Exhibit 85: Returns to Talent, Retail, (2003-2010) Exhibit 85: Returns to Talent, Retail (2003-2010)

$70,000 $59,366 $60,000

$50,000 $46,546 $41,189 $40,000 $31,547

Compensation Gap ($) $20,000

$10,000

$0 2003 2004 2005 2006 2007 2008 2009 2010

Retail Economy Linear (Retail) Linear (Economy) Source: US Census Bureau, Richard Florida's "The Rise of the Creative Class", Deloitte Analysis Source: U.S. Census Bureau, Richard Florida's The Rise of the Creative Class, Deloitte analysis

214

Updated Appendix — Retail Exhibit 86: Percentage participation in Inter-Firm knowledge flows, Retail, (2011) Exhibit 86: Percentage participation in Inter-Firm knowledge flows, Retail (2011)

50% 46%

39% 45% • Please use the exhibit to 40% 37% 36% 42% replace the previous 33% 33% 38% 38% 31% exhibit named “Inter-firm 30% 32% Firm knowledge flows - 30% Knowledge Flow Index 29% 19% Values” 20% • Adjust the bar color to

by participation type make it consistent with 15% 10% the exhibits in the other sections 0% • Please adjust the lines for Percentage participation in participation Percentage Inter Email Alerts Community Lunch Meetings Web-Casts Professional Telephone Social Media Conferences Organizations Organizations economy based on the data A55 Retail Economy

Source:Source: Synovate Synovate,, Deloitte Deloitte Analysis analysis Updated

Exhibit 87: Worker Passion, Retail, (2010) Exhibit 87: Worker Passion, Retail (2010, 2011)

40%

31% 31% 30% 25% 24% 24% 23% 21% 21% 20%

10% Percentage of of by Percentage employees, category Passion 0% Disengaged Passive Engaged Passionate

2010 2011 Economy Source: Synovate, Deloitte analysis Source: Synovate, Deloitte Analysis

2011 Shift Index Measuring the forces of long-term change 215

Exhibit 88: Competitive Intensity, Technology, (1965-2010) Exhibit 88: Competitive Intensity, Technology (1965-2010)

0.20

0.18 0.16 0.16

0.14

0.12 0.11 0.10

Herfindahl Index 0.08

0.06

0.04 0.03 0.02 0.01 0.00 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010

Technology Economy Linear (Technology) Linear (Economy)

Source: CompustatCompustat,, Deloitte Deloitte Analysis analysis

HHI Value Industry Concentration Competitive Intensity

< .01 Highly Un-concentrated Very High

0 - 0.10 Un-concentrated High 0.10 - 0.18 Moderate Concentration Moderate A57 0.18 - 1 High Concentration Low

Exhibit 89: Labor Productivity, Technology, (1987-2010) D Exhibit 89: Labor Productivity, Technology (1987-2010)

400 414.9

300

200 144.9 81.9

Productivity Index 100

0 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

-100 -60.4

Technology Economy Linear (Technology) Linear (Economy)

Source:Source: Bureau Bureau of Laborof Labor Statistics, Statistics, Deloitte Deloitte Analysis analysis

216

D Appendix — Technology Exhibit 90: Asset Profitability, Technology, (1965-2010) Exhibit 90: Asset Profitability, Technology (1965-2010)

15%

10% 9.0% 8.6% 5% 4.2% 1.5% 1.0% 0% 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010

Return on on Return Assets (%) -5%

-10%

-15% Technology Economy Linear (Technology) Linear (Economy) Source: Compustat, Deloitte analysis A59 Source: Compustat, Deloitte Analysis

ExhibitExhibit 91: Asset91: Asset Profitability Profitability Top Quartile Top andQuartile Bottom and Quartile, Bottom Technology, Quartile,(1965 Technology-2010) (1965-2010)

15.00%

12.6% 12.50%

12.2% 10.00%

7.50%

4.1% Return on Assets (%) on Return 10%

-10% 1.3%

-30%

-50% 2001: -70% -240% -67.9% -90% 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010

Bottom Quartile Linear (Bottom Quartile) Source: Compustat, Deloitte analysis Source: Compustat, Deloitte analysis

2011 Shift Index Measuring the forces of long-term change 217

A60

Exhibit 92: Firm Topple, Technology, (1966-2010) Exhibit 92: Firm Topple, Technology (1966-2010)

0.80

0.70

0.60 0.51 0.57

0.50 0.55

0.40 Topple Rate 0.30 0.37

0.20

0.10

0.00 1966 1970 1974 1978 1982 1986 1990 1994 1998 2002 2006 2010

Technology Economy A61 Linear (Technology) Linear (Economy) Source: Compustat, Deloitte analysis Source: Compustat, Deloitte Analysis D

Exhibit 93: Returns to Talent, Technology, (2003-2010) Exhibit 93: Returns to Talent, Technology (2003-2010)

$80,000 $71,184 $70,000

$56,317 $59,366 $60,000

$50,000 $46,546

$40,000

$30,000

$10,000

$0 2003 2004 2005 2006 2007 2008 2009 2010

Technology Economy Linear (Technology) Linear (Economy)

Source: U.S. Census Bureau, Richard Florida's The Rise of the Creative Class, Deloitte analysis Source: US Census Bureau, Richard Florida's "The Rise of the Creative Class", Deloitte Analysis

218

Updated Appendix — Technology Exhibit 94: Percentage participation in Inter-Firm knowledge flows, Technology, (2011) Exhibit 94: Percentage participation in Inter-Firm knowledge flows, Technology (2011)

50% 46% 50% 49% • Please use the exhibit to 39% 37% 40% 42% 36% 42% replace the previous 33% 38% 33% 31% 38% exhibit named “Inter-firm 30% Knowledge Flow Index

Firm knowledge flows 32% - Values” 19% 20% • Adjust the bar color to 21% make it consistent with by participation type 10% the exhibits in the other sections

0% • Please adjust the lines

Percentage participation in participation Percentage Inter Email Alerts Community Lunch Meetings Web-Casts Professional Telephone Social Media Conferences Organizations Organizations for economy based on the data Technology Economy A63 Source:Source: Synovate,Synovate, DeloitteDeloitte Analysis analysis

Updated

Exhibit 95: Worker Passion, Technology, (2010) Exhibit 95: Worker Passion, Technology (2010, 2011)

40%

31% 31% 30% 25% 24% 24% 23% 21% 21% 20%

2010 2011 Economy Source: Synovate, Deloitte analysis Source: Synovate, Deloitte Analysis

2011 Shift Index Measuring the forces of long-term change 219

Exhibit 96: Competitive Intensity , Telecommunications, (1965-2010) Exhibit 96: Competitive Intensity , Telecommunications (1965-2010)

0.30

0.25 0.26

0.20 0.17

0.15 0.14

0.10 Herfindahl Index 0.11 0.03 0.05

0.00 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 -0.05 -0.02

Telecommunications Economy Linear (Telecommunications) Linear (Economy) Source:Source: CompustatCompustat,, Deloitte Deloitte Analysis analysis

HHI Value Industry Concentration Competitive Intensity

< .01 Highly Un-concentrated Very High

0 - 0.10 Un-concentrated High 0.10 - 0.18 Moderate Concentration Moderate A65 0.18 - 1 High Concentration Low

Exhibit 97: Labor Productivity, Telecommunications, (1987-2010) D Exhibit 97: Labor Productivity, Telecommunications (1987-2010)

200 209.6

150 144.9

100

Productivity Index 81.9 50 35.0

0 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Telecommunications Economy Linear (Telecommunications) Linear (Economy)

Source:Source: Bureau Bureau of Laborof Labor Statistics, Statistics, Deloitte Deloitte Analysis analysis

220

D Appendix — Telecommunications ExhibitExhibit 98: 98: Asset Asset Profitability, Profitability, Telecommunications, Telecommunications (1965-2010) (1965-2010)

6% 5.2% 5.0%

4% 4.2% 2.4% 2% 1.0% 0% 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 -2%

-4% Return on on Return Assets (%) -6%

-8%

Telecommunications Economy Linear (Telecommunications) Linear (Economy) A67 Source:Source: Compustat Compustat,, Deloitte Deloitte Analysis analysis

Exhibit 99: Asset Profitability Top Quartile and Bottom Quartile, Telecommunications, (1965-2010) Exhibit 99: Asset Profitability Top Quartile and Bottom Quartile, Telecommunications (1965-2010)

15.00% 2003: 16.9%

12.50% 11.4% 9.7%

10.00%

7.50%

Top Quartile Linear (Top Quartile)

Return on Assets (%) on Return 10% 3.4% -10% 7.1%

-30% -33.2% -50%

-70% 2001: -152% -90% 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010

Bottom Quartile Linear (Bottom Quartile)

Source:Source: Compustat Compustat,, Deloitte Deloitte analysis analysis

2011 Shift Index Measuring the forces of long-term change 221

A68

Exhibit 100: Firm Topple, Telecommunications, (1966-2010) Exhibit 100: Firm Topple, Telecommunications (1966-2010)

4.50

4.00

3.50

3.00

2.50

2.00 Topple Rate

1.50 1.02 1.00 0.55 0.50 0.39 0.37 0.00 1966 1970 1974 1978 1982 1986 1990 1994 1998 2002 2006 2010

Telecommunications Economy Linear (Telecommunications) Linear (Economy) A69 Source:Source: Compustat Compustat,, Deloitte Deloitte Analysis analysis

Exhibit 101: Returns to Talent, Telecommunications, (2003-2010) Exhibit 101: Returns to Talent, Telecommunications (2003-2010)

$80,000

$70,000 $59,366 $60,000 $46,546 $58,560 $50,000

$40,000 $44,085

$10,000

$0 2003 2004 2005 2006 2007 2008 2009 2010

Telecommunications Economy Linear (Telecommunications) Linear (Economy)

Source: US Census Bureau, Richard Florida's "The Rise of the Creative Class", Deloitte Analysis Source: U.S. Census Bureau, Richard Florida's The Rise of the Creative Class, Deloitte analysis

222

Updated Appendix — Telecommunications Exhibit 102: Percentage participation in Inter-Firm knowledge flows, Telecommunications, (2011) Exhibit 102: Percentage participation in Inter-Firm knowledge flows, Telecommunications (2011)

50% 46%

39% 40% 37% 36% 33% 33% 31% 30% Firm knowledge flows - 30% 29% 29% 27% 19% 20% 23% 24% 21%

by participation type 17% 10%

Percentage participation in participation Percentage Inter Email Alerts Community Lunch Meetings Web-Casts Professional Telephone Social Media Conferences Organizations Organizations

Telecommunications Economy A71 Source:Source: Synovate Synovate,, Deloitte Deloitte Analysis analysis

Updated

Exhibit 103: Worker Passion, Telecommunications, (2010) Exhibit 103: Worker Passion, Telecommunications (2010, 2011)

40%

31% 31% 30% 25% 24% 24% 23% 21% 21% 20%

2010 2011 Economy

Source:Source: Synovate Synovate,, Deloitte Deloitte Analysis analysis

2011 Shift Index Measuring the forces of long-term change 223

Now in its third year, the Shift Index is the product of collaborative effort and support from many talented and dedicated people. While it is impossible to mention them all, we wish to express our profound gratitude to the many people who have made valuable contributions. At the same time, the authors take full responsibility for any errors or omissions in the Shift Index itself.

We would like to specially thank the following individuals for their contributions that made the 2011 Shift Index possible: • Dan Elbert • Joseph Fitzgerald • Ivan Alvarez • Denesh Gunasekarampulle • Dan Clingan • Jonathan Lewis • Sam Shepard • Blythe Aronowitz • Tatyana Kanzaveli • Anisha Sharma • Maggie Wooll • Josh Smith • Emily Koteff Moreano • Jodi Gray • Diana Fox-Hopkins • Karen Wiltsie • Andrew Luedke • Nelson Kunkel

Economist Intelligence Unit: Roberta Torre, William Shallcross, Catherine Colebrook, Leo Abruzzese, Richard Stein, Manuel Neumann and Vanesa Sanchez

Copymat: Darius Meykadeh and Don Concepcion

Deloitte and Deloitte Touche Tohmatsu Limited leadership and sponsors of the Center for the Edge who have sponsored and supported this research: • Jim Quigley • Barry Salzberg • Cathy Benko • Jim Moffett • Eric Openshaw • Michael Raynor • Phil Asmundson • Teresa Briggs • Ed Carey • Dan Latimore • Vikram Mahidhar • Karen Mazer • Mike Canning • Dave Rosenblum • Kevin Lynch • Jennifer Steinmann • Dave Couture

224 2011 Shift Index Measuring the forces of long-term change 224 Acknowledgements

“Gold Standard” Index Architects who generously helped with development of the index methodology: • Ambassador Terry Miller, Director of the Center for International Trade and Economics (CITE) at The Heritage Foundation • Christopher Walker, Director of Studies at Freedom House • Ataman Ozyidirim, Associate Director of Economic Research at The Conference Board • David Campbell, Lecturer, Graziadio School of Business, Pepperdine University. Formerly a consultant to Hope Street Group and helped build the Economic Opportunity Index Acknowledgements

Numerous collaborators who provided data, industry knowledge, and insights: • Laurie Salmon and Matt Russell, Bureau of Labor Statistics Office of Employment and Unemployment Statistics • Christy Randall, comScore • Robert Roche, CTIA • David Ford and Misha Edel, Leading Technology Advisory Group • Arian Hassani, Hope Street Group • Richard Jackowitz, Liberum/Wall Street Transcript • Gary Williams, Scott Morano and Bruce Corner, Synovate • Dave Eulitt and Alan Mauldin, TeleGeography, • Steven Graefe, University of Chicago Booth School of Business: Center for Research in Security Prices • Ingo Reinhardt, University of Cologne • Irene Mia, World Economic Forum • Richard Florida, Creative Class • Scott Page, University of Michigan • Carl Steidtmann and Ira Kalish, Deloitte • Steve Denning

Participants in our research workshops, who provided feedback, insights, and examples, helping us refine our thoughts and theory: • Brian Arthur, Santa Fe/Stanford • Prith Banerjee, HP/HP Labs • Jeff Benesch, Deloitte • Russell Hancock, Joint Venture Silicon Valley • Hamilton Helmer, Strategy Capital • John Kutz, Deloitte • Paul Milgrom, Stanford • Om Nalamasu, Applied Materials • Don Proctor, Cisco • Russell Siegelman, Kleiner Perkins Caufield and Byers

Our colleagues at Deloitte who provided subject matter expertise and guidance: • Center for the Edge: Blythe Aronowitz, Glen Dong, Regina Davis, Gina Battisto, and Carrie Howell • Center for the Edge Fellows (Big Shift / Shift Index Research Streams): Michelle Lally, Shalini Bhatia, Sarah Scharf, Kimberly Korinek, S.J. Lu, Joseph Fitzgerald, Ivan Alvarez, Jonathon Wong, Samuel Shepard, Josh Spry, Neda Jafarnia, Jason Trichel, Tamara Samoylova, Brent Dance, Mark Astrinos, Dan Elbert, Gautam Kasthurirangan, Scott Judd, Eric Newman, Sekhar Suryanarayanan, and Siddhi Saraiya • Center for the Edge Fellows: Maryann Baribault, Brendan Brier, Alison Coleman Rezai, Andrew de Maar, Chetan Desai, Catherine Keller, Neal Kohl, Jayant Lakshmikanthan, Adit Mane, Silke Meixner, Jagannath Nemani, Tam Pham, Vijay Sharma, Sumit Sharma, Blythe Aronowitz, Jitin Asnaani, Indira Gillingham, Bill Wiltschko, Amit Sahasrabudhe, Holly Kellar, Megan Miller, Aliza Marks, Marcelus DeCoulode, Casey Ryan, Anita Chetan, Kelsey Miller, Josh Smith, and Nancy Lan • Advanced Quantitative Services: Debarshi Chatterjee • Marketing: Frank L. Buttitta, Tatyana Kanzaveli, Christine Brodeur, Audrey Hitchings, and Kathy Dorr • Risk Review: Wally Gregory, Denesh Gunasekarampulle, Don Falkenhagen, Mark Albrecht, Rob Fitzgerald, Bill Park, and Don Schwegman • Public Relations: Vince Hulbert, Jonathan Gandal, Anisha Sharma, and Hill & Knowlton • Document & Creative Services: Dan Clingan, Paul Malabanan, Emily Koteff Moreano, Santosh G.L., and Joey Suing

2011 Shift Index Measuring the forces of long-term change 225 the Edge Deloitte Center for Deloitte Center for the Edge

The Center for The Edge focuses on the boundary, John Hagel (Co-chairman) has nearly or edge, of the global business environment where 30 years’ experience as a management strategic opportunity is the highest consultant, author, speaker, and entrepreneur and has helped companies The Deloitte Center for the Edge conducts original improve their performance by effectively research and develops substantive points of view for new applying IT to reshape business strategies. corporate growth. The Silicon Valley-based Center helps In addition to holding significant positions senior executives make sense of and profit from emerging at leading consulting firms and companies throughout opportunities on the edge of business and technology. his career, Hagel is the author of a series of best-selling Center leaders believe that what is created on the edge business books, including Net Gain, Net Worth, Out of the of the competitive landscape—in terms of technology, Box, The Only Sustainable Edge, and, most recently, The geography, demographics, markets—inevitably strikes at Power of Pull. the very heart of a business. The Center for the Edge’s mission is to identify and explore emerging opportunities John Seely Brown (JSB) (Independent related to big shifts that are not yet on the senior Co-chairman) is a prolific writer, speaker, management agenda, but ought to be. While Center and educator. In addition to his work with leaders are focused on long-term trends and opportunities, the Center for the Edge, JSB is Adviser to they are equally focused on implications for near-term the Provost and a visiting scholar at the action, the day-to-day environment of executives. University of Southern California. This position followed a lengthy tenure at Below the surface of current events, buried amid the Xerox Corporation, where he served as chief scientist and latest headlines and competitive moves, executives director of the Xerox Palo Alto Research Center. JSB has are beginning to see the outlines of a new business published more than 100 papers in scientific journals and landscape. Performance pressures are mounting. The old authored or co-authored seven books, including The Social ways of doing things are generating diminishing returns. Life of Information, The Only Sustainable Edge, The Power Companies are having harder time making money—and of Pull, and A New Culture of Learning. increasingly, their very survival is challenged. Executives must learn ways not only to do their jobs differently, Duleesha Kulasooriya (Research Lead) but also to do them better. That, in part, requires leads research at the Center for the Edge. understanding the broader changes to the operating Prior to joining the Center, Duleesha was environment: part of Deloitte’s Strategy & Operations practice. His eight years in consulting • What is really driving intensifying competitive pressures? were focused on corporate strategy and • What long-term opportunities are available? customer and market strategy and also included projects • What needs to be done today to change course? related to performance improvement, process redesign, and change management. Duleesha led the teams of Edge Decoding the deep structure of this economic shift will Fellows to design and publish the inaugural Shift Index in allow executives to thrive in the face of intensifying 2009 and has also led research streams on social software, competition and growing economic pressure. The good performance ecosystems, and institutional innovation. news is that the actions needed to address near-term economic conditions are also the best long-term measures to take advantage of the opportunities these challenges create. For more information about the Center’s unique perspective on these challenges, visit www.deloitte.com/ centerforedge.

226 Deloitte Center for the Edge

2011 Shift Index Measuring the forces of long-term change 227 The Shift Index focuses attention on both long-term challenges and opportunities facing executives and policy makers. Foundational shifts are significantly intensifying competition, leading to growing performance pressures extending well beyond the current economic downturn. As the Index reveals companies to date have generally found it very difficult to respond effectively to these performance pressures. On the other hand, the same foundational changes create new opportunities to accelerate performance improvement. The key is to find ways to participate more effectively in richer and more diverse knowledge flows. Adapting our institutions and our practices to the long-term shifts around us will be the key in turning challenge into opportunity.

The 2011 Shift Index report is both a stand-alone summary of the findings to date and an update for those who have read prior editions of the report. In this year’s report we also explore several themes that have influenced our thinking on the Big Shift. As with prior years, we look in greater detail at the questions and challenges behind the cognitive dissonance that has greeted our observations. Additionally, we add our perspective to the public discourse around the hot-button topic of unemployment, presenting our findings from the perspective of firms, an often neglected player in this discussion. Third, we discuss the shifting power dynamics between firms and individuals, and how the ‘connected individual’ is gaining power by tapping into knowledge flows.

These topics and our twenty-five metrics put a number of key questions on the leadership agenda: Are companies organized to effectively generate and participate in a broader range of knowledge flows, especially those that go beyond the boundaries of the firm? How can they best create and capture value from such flows? How can they ignite and tap into the passions of their workforce to achieve sustainable performance improvement? And most importantly, how do they measure their progress navigating the Big Shift in the business landscape? We hope that the Shift Index will help executives answer those questions — in these difficult times and beyond.

www.deloitte.com/shiftindex

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