Digital era Technology Operating Models Volume 1 | Digital Technologies, Digital Disruption and Digital Strategy 2017-10 Content 1 Preface 3 “Digital technologies are doing for 2 Why is Digital such a big thing? 7 human brainpower what the steam engine and related technologies did 3 Digital Innovation and Disruption 17 for human muscle power. They’re allowing us to overcome many 4 Digital Economy Paradigm Shifts 24 limitations rapidly and to open up new frontiers with unprecedented speed. 5 Digital Technologies 33 It’s a very big deal. But how exactly it will play out is uncertain” 6 Digital Strategy 53 – Andrew McAfee 7 Appendices 63 © 2017 Deloitte The Netherlands Digital Era Technology Operating Models - Deloitte Point of View 2 1. Preface © 2017 Deloitte The Netherlands Digital Era Technology Operating Models - Deloitte Point of View 3 Digital technologies force enterprises to rethink their strategy. This technology push is not going away as the most disruptive ones will take at least a decade to develop into mainstream Human augmentation Quantum computing Brain-computer interfaces > > 10 years Social robotics Virtual Reality Augmented Reality Conversational Computing Virtual Assistance Blockchain, Smart Contracts Artificial Intelligence Cognitive Computing Commercial drones Emerging Driverless vehicles Sensors & The Autonomous things Internet of Things 3D printing Additive manufacturing Algorithmic automation Cloud Computing Big Data analytics Social media & Digital platforms Mobile endpoint devices & Apps Maturing Internet Enterprise systems © 2017 Deloitte The Netherlands Digital Era Technology Operating Models - Deloitte Point of View 4 As digital technologies proliferate, new opportunities abound. To capture them, however, the Technology Operating Model must evolve Evolving Technology Operating Models There’s no question that technologies like the internet, mobile, social, and cloud created unprecedented disruption. In today’s digital age, however, the pace of disruption is only set to increase. As new technologies—such as the Internet of Things (IoT), artificial intelligence, robotics, and virtual reality—proliferate, organizations are coming under mounting pressure to rethink not just their technology strategy but their entire operational strategy. In some sectors, the impact of these trends is so significant that companies will need to change their core business models if they hope to survive. Not surprisingly, these shifts are forcing companies to re-examine their Technology Operating Model (TOM)—the way in which they configure their operations to execute on their business technology strategy. In this digital age, this is no simple task. Increasingly, organizations will need to strike a balance between a range of difficult choices: security versus openness, proprietary versus shared, vanilla versus best-of-breed, reliable and predictable versus fast failure. They will need to tailor their TOM to meet their current organizational needs while anticipating their future digital information and technology Technology requirements. Most critically, they will need to optimize their TOM to capture both short- Operating and long-term benefits. Model To help organizations address these challenges, we have identified nine big shifts that will influence the TOM of the future. While every company will be affected differently by these shifts, there is no doubt that organizations of all sizes, in all sectors, will feel their impact. The goal of this report is to provide a clear overview on how the TOM will evolve over time, and share a toolset companies can use to assess how these big shifts will affect their TOM. With the resulting insights, we hope to help management reconfigure their TOM in time to benefit from the digital economy. © 2017 Deloitte The Netherlands Digital Era Technology Operating Models - Deloitte Point of View 5 Companies understand that change is required—they’re just not prepared for it 2016 findings: 87% anticipate disruption, 44% are prepared 2017 findings: 61% score their digital maturity at 1-5 on a 10-point scale In a survey conducted in 2016, roughly 3,700 organizations across the globe were asked The 2017 report (Achieving Digital Maturity) revealed similar results. While 85% agreed that how susceptible their industries were to digital disruption and how prepared they were to being a digital business is important to the success of their organization, 61% rated their deal with these challenges. The results—released in Aligning the Organization for Its Digital digital maturity (i.e. their ability to leverage digital technologies and capabilities to improve Future, a report by MIT Sloan and Deloitte University Press—were quite revealing: while processes, engage talent across the organization, and drive new value-generating business 87% of respondents anticipated moderate to great disruption to their industry, only 44% felt models) at five or lower on a 10-point scale, with only 13% ranking themselves at eight or prepared to deal with it. higher. To what extent do you believe digital technologies will disrupt your industry? Organization’s digital maturity level 61% ≤ 5 26% 6 or 7 13% ≥ 8 59% 28% 9% 3% 18% 16% 16% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 14% 14% 14% 13% Great extent Moderate extent Small extent Not at all Don't know 12% 12% 11% 10% My organization is adequately preparing for disruptions projected to occur in my 8% industry due to digital trends 8% 7% 6% 11% 33% 23% 25% 6% 4% 3% 2% 2% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 0% Strongly agree Agree Neither agree nor disagree Disagree Strongly disagree Don't know 1 2 3 4 5 6 7 8 9 10 Source: MITSloan Management Review / Deloitte University Press - Aligning the Organization for Its Digital Future - 2016 Source: MITSloan Management Review / Deloitte University Press – Achieving Digital Maturity - 2017 © 2017 Deloitte The Netherlands Digital Era Technology Operating Models - Deloitte Point of View 6 2. Why is Digital such a big thing? © 2017 Deloitte The Netherlands Digital Era Technology Operating Models - Deloitte Point of View 7 Deloitte identifies four amplifying forces that – in combination – explain why Digital is such a big thing, now and in the decade(s) ahead of us 1. Exponential Growth 3. Combinatorial Innovation The foundational technologies (processing power, storage, The nature of digital technologies allows them to be deployed in bandwidth) have been subject to exponential growth (Moore’s conjunction with each other. Each new digital innovation becomes law) for almost five decades. This pattern of doubling every 2 a building block that can be used to create new combinations to years (for processing power) has brought us at a point where innovate and disrupt. As the number of digital technologies things are now possible that have long been unthinkable. increases, so does the number of possible combinations and the innovation potential. Innovation potential is not “used up” but increases in a combinatorial way, with every new building block. This is what Gartner calls the ‘nexus of forces’. 2. Dissemination Speed 4. Emerging Technologies Digital solutions have the potential to scale rapidly and Finally, what we call ‘Digital’ relates to a heterogeneous set of disseminate quickly if the solution answers a fundamental need. technologies in various phases of maturity. Some of the This has two dimensions. From a technical perspective, technologies that are expected to be most transformational, such technologies such as cloud and mobile allow for quick replication as Machine Intelligence, Internet of Things and Social Robotics, and dissemination of digital assets. What adds to this is the social are still in their infancy and reaching their plateau of productivity sharing aspect that is fueled by the exponential growth of social in the next decade. The disruption that will be caused by these media. emerging technologies is still ahead of us. © 2017 Deloitte The Netherlands Digital Era Technology Operating Models - Deloitte Point of View 8 1 The driving force that brought us here: for 50 years, processing power followed Moore’s law, doubling the number of transistors for the same price every 2 years Cost of computing Total # transistors per chip Size per transistor (nm) Date $ per GFLOPS 100000000001E+10 10000 1961 $ 1,100,000,000,000.00 1984 $ 18,750,000.00 10000000001E+09 1997 $ 30,000.00 1000 2000 Apr $ 1,000.00 100000000 2000 May $ 640.00 10000000 2003 $ 82.00 100 2007 $ 48.00 1000000 2011 $ 1.80 2012 $ 0.75 100000 10 2013 Jun $ 0.22 10000 2013 Nov $ 0.16 2013 Dec $ 0.12 1000 1 2015 $ 0.08 1970 1980 1990 2000 2010 2020 1970 1980 1990 2000 2010 2020 Source: Wikipedia - FLOPS Source: Wikipedia – Transistor Count (Intel) Source: Wikipedia – Transistor Count (Intel) © 2017 Deloitte The Netherlands Digital Era Technology Operating Models - Deloitte Point of View 9 1 A similar growth happened in bandwidth, following Jakob Nielsen's Law of Internet Bandwidth: the speed of a high-end connection grows by 50% per year Exponential growth of maximum connection speed (Mb/s) Exponential growth of total IP traffic on AMS-IX 1000 10000 FttH DOCSIS 3, FttH 100 ADSL2+ 10 ADSL, DOCSIS 1000 ADSL 1 1985 1990 1995 2000 2005 2010 2015 ISDN 0,1 100 V32 Modem 0,01 10 V22 Modem 0,001 05 06 07 08 09 10 11 12 13 14 15 16 17 Source: Deloitte analysis Source: https://ams-ix.net/technical/statistics/historical-traffic-data © 2017 Deloitte The Netherlands Digital Era Technology Operating Models - Deloitte Point of View 10 1 Moore’s law, that accurately described exponential growth in performance/price of integrated circuits (computer chips) is now reaching its physical limits The deceptive nature of exponential growth Illustration: iPhone generations New technologies need time to develop into maturity. After their first introduction, they As an illustration, we compared benchmarks of iPhone generations. First, we see an enter a period of improvement in which prices drop and performance increases. In the first astonishing increase in iPhone computing power as the latest iPhone has 70 times (7000%) period of development, improvement often follows an exponential pattern: doubling every of the computing power of the iPhone 3G.