Data Economy Report 2018 Contents
Executive summary 2 Introduction 7 Chapter 1: Drivers of the Data Economy 14 Chapter 2: Overview of National Data Economy results 26 Chapter 3: UK Data Economy results 35 Chapter 4: Ireland Data Economy results 52 Chapter 5: Germany Data Economy results 63 Chapter 6: Netherlands Data Economy results 72 Chapter 7: Emergence of data centres as key players in the Data Economy 79 Chapter 8: How to unlock the potential of data 82 About 85
DATA ECONOMY REPORT 2018 1 Executive Summary
The creation and sharing of data has always been an Simultaneously, business use of data has also increased important driver of human social and economic progress, exponentially, driven by the increasing number of digital but over the past 20 years there has been an explosion devices and sensors used on production lines, and in energy, in the rate at which new data is being created. Given the transportation and telecommunications infrastructure, as enormous increase in the amount of data and the increasing well as in vehicles used for moving freight and passengers. range of uses that businesses and Governments are finding Although the generation of data by consumers in future will for this data, the purpose of this report is to highlight and remain very significant, it is expected that an increasingly quantify the already large and increasing role that business large proportion of data will be created by businesses. This data plays in the economies of four European countries: the growth will be driven by the demand for data: to improve UK, Ireland, Germany and the Netherlands. business decision-making; to create opportunities for cost- eficiencies and revenue growth; and from opportunities for For the purposes of this report the Data Economy is defined product and service innovation. as the financial and economic value created by the storage, retrieval and analysis – via sophisticated software and other However, a review of national and sector-level documentary tools – of large volumes of highly detailed business and evidence has revealed concerns and challenges regarding organisational data at very high speeds. the extent to which businesses and other organisations are able to identify and exploit the eficiency and service The research undertaken for this report has included a innovation benefits that stand to be gained from the large-scale review of documents and data, followed by analysis of data. The most important of these constraints targeted consultations with stakeholders. However, the main include the following: source of new information has come from detailed economic modelling of the current contribution of the Data Economy, • Under-developed awareness in some businesses of the coupled with forecasting of the potential future contribution potential benefits of data analytics of data for the UK and Irish economies. • Resistance to, and fear of, potential organisational change entailed by data analytics Drivers of the Data Economy • Absence of available resources regarding the ability to Advances in digital technology and the increasing ubiquity integrate and manage large datasets of connected devices and sensors means that there has • Shortages of suficient skilled staf been a huge increase in the global rate at which data is • The lack of financial means to make the technological being generated. Moreover, the rate at which data is created and stafing investments, particularly in the case of is currently accelerating, driven by the rapidly rising number smaller businesses and organisations. of household and business applications.
The growth of consumer data is further boosted by the demand for digital entertainment and communication, ranging from video and music streaming to online computer gaming and the sharing of pictures, videos and other information on social media.
2 DATA ECONOMY REPORT 2018 Overview of results
In terms of the value of economic output (as measured by
Gross Value Added), the largest Data Economy among the Indicator UK Ireland Germany Netherlands four countries considered by this research is that of Germany
(€108 billion). However, as a proportion of the overall 2016 GVA €millions 1 89,826 9,962 108,327 24,637 national economy the German Data Economy is estimated (2016 prices) 2016 GVA as % of to be the smallest (3.8%). The largest Data Economy in 4.2% 4.0% 3.8% 3.9% national economy proportionate terms is the UK (4.2%) followed by 2016 Data Economy Ireland (4.0%). employment 1,147 61 1,323 247 (direct, ‘000s) 2016 Data Economy In terms of direct jobs, the UK is the largest Data Economy, jobs as % of total 3.3% 3.0% 3.2% 3.2% workforce jobs with 3.3% of national employment accounted for by this category. However, the diference between the UK and the other countries is quite small: in the Netherlands and Germany the proportion is 3.2%.
UK €90 billion
Germany €108 billion
Netherlands €25 billion
Ireland €10 billion
DATA ECONOMY REPORT 2018 3
1 | Note: to enable comparison the estimated value of economic output (GVA) across the four countries is provided in terms of millions of Euros. However, it should be recognised that in some other advanced economies the scale of the employment and economic output contribution of data is larger than for any of the four countries listed in the previous table. For example, in the USA the Data Economy is estimated to already contribute 5.1% of output and 4.1% of jobs, while in Canada the proportions are 4.3% and 3.4% respectively.
Among the four countries that are the principal focus of this report, the largest contribution by sector (in proportionate terms) is made by the ICT sector, with this proportion ranging from 34% in the Netherlands to nearly 50% in Ireland. In the UK the most significant contributions from other sectors come from the Financial and Professional services sectors, whereas in the other countries (especially in Germany) the Manufacturing sector is also a major component. In both the Netherlands and Ireland, Financial and Professional services are also important contributors, as is the Transport sector.
Although the UK has the most significant Data Economy in proportionate terms, there is evidence that the other countries are closing the gap. In the most recent five-year period (2012-2016), economic output attributable to the Data Economy is estimated to have grown the fastest in Ireland (64%), followed by Germany (51%) and the Netherlands (41%). The equivalent growth in the UK was 33%.
Despite the strong rate of growth of the Data Economy in all countries, there remains untapped growth potential.
The UK is estimated to be currently achieving only 58% of its current potential, with Germany achieving 55%. The worst performing country on this basis is the Netherlands, which is estimated to be currently achieving only about 49% of its potential.
4 DATA ECONOMY REPORT 2018 How to unlock the potential of data .04 Large businesses also have a potential role to play in While it is expected that the future value of the Data helping to encourage and mentor SMEs to investigate and Economy will continue to grow strongly in each country, develop data analytics infrastructure and applications. there is a danger that – unless significant constraints and There is an opportunity for larger businesses to provide barriers are not addressed – a large proportion of the support for SMEs who are members of their supply chain, potential value of the Data Economy will remain unrealised. by defining standards and by sharing best practice experience and expertise. The following is a generic set of actions focused on individual businesses, business networks and Government .05 that are relevant to all four of the countries considered in There is also a major opportunity for a larger number of this report. SMEs to begin to secure business growth and productivity gains that are available from analysis of their own data. Actions for industry groups and individual businesses Essentially, the availability of analytical functionality via Cloud computing means that tools and infrastructure .01 previously only available to larger companies are now within Businesses have a lot of work to do to build confidence the scope of smaller businesses. and trust with respect to the handling of customers’ data. Distrust and concerns about privacy and security must be .06 resolved by industry (and Government) if the full value of There is an urgent need for further investment by the the Data Economy is to be realised. private sector in recruiting workers and developing training programmes – such as digital apprenticeships – targeting .02 school leavers and returners to the workforce. There are unrealised opportunities for businesses of all sizes to utilise the data they hold across all areas of their .07 operations. Senior management in large businesses must Peak industry bodies should pool resources to campaign for therefore lead and fully integrate digital transformation in greater awareness of the value of data among businesses their companies as a key backbone of long-term business large and small. development strategy. This is especially important for businesses operating in sectors that have hitherto been .08 slower at making significant investments in data analytic Sector network groupings should each devise sector-specific capabilities, including investment in infrastructure, programmes designed to raise awareness and address equipment and software to enable advanced data analytics sector-specific constraints such as skills shortages. capabilities, but also in terms of investing in both managerial capacity and technical skills that are needed to realise the .09 opportunities more fully. It is vital that telecommunications infrastructure providers (many of whom are private sector) continue to invest in .03 telecoms infrastructure, both in terms of ultrafast broadband All large businesses (i.e. more than 250 employees) should and in the emerging fifth generation of mobile phone appoint a Chief Data Oficer reporting to the CEO to networks (5G). coordinate strategy and ensure full integration with wider business objectives.
DATA ECONOMY REPORT 2018 5 Actions for Government .05 Government has a role to play in providing the .01 regulatory framework for the next generation of fixed and Government has a role in continuing to improve the mobile telecoms infrastructure. There is also a specific curriculum and in enhancing the quality and relevance of planning policy issue with the future mobile network as 5G teaching of subjects such as mathematics, statistics and will require a much denser physical coverage of masts and computer science in secondary, further and higher education. relay stations compared to the current 4G network. This isn’t just relevant to rural areas. Investment will be needed .02 to ensure good quality of coverage within and between Government can also help to promote the Data Economy buildings in more densely populated urban areas. as a career destination for young people, especially among groups (such as females) who are traditionally .06 under-represented in computer science and There are opportunities to improve the performance of similar occupations. Government as data-led service providers: Government needs to continually rethink the way that services are .03 delivered and truly embrace a Data Economy approach. Government also has a potentially important role in helping to retrain older workers (including those who have had a period of absence from the workforce) and in providing incentives for smaller businesses to invest in workforce training.
.04 Government has a key role to play in making its own data Open Data, available and shared for others to use. Even in the UK (which is ranked top globally for openness of Government data) there is still more to do. In Ireland this is a particularly pertinent issue as Ireland has a relatively low ranking (27th) in the global Open Data Barometer rankings (albeit its position has improved – by four places – in the most recent ratings).
6 DATA ECONOMY REPORT 20186 Introduction
Purpose of the study
The creation and sharing of information and knowledge To fill this gap the purpose of this report is to quantify the has played a crucial role in the development of societies scale of the contribution of the Data Economy in terms of throughout the entirety of human history. Over the past both GVA and in terms of the levels of direct employment in 200 years, the sharing of information between humans and each country. businesses has played an increasingly important role in the economic and social development of our civilisations. The specific objectives of the research are: Over the past 20 years, huge advances in technology have led to an explosion in the rate at which new data is being • To provide a quantification of the Data Economy created: according to some sources, 90% of all data created for each country researched (UK, Ireland, Germany, throughout human history has been created in just the past Netherlands) two years.2 • To analyse current trends in the growth of the Data Economy in each country Moreover, the pace of data creation is constantly increasing. Many experts expect the amount of data generated daily to • For the UK and Ireland, also to generate predictions of increase by at least 10% per annum over the next decade. the potential scale of the future Data Economy over a medium-term timeframe (up to 2025)
Given the enormous increase in the amount of data and the • To provide insights into the factors afecting the increasing range of uses that businesses and Governments current and potential future value of the Data Economy, are finding for this data, the purpose of this report is to including identification of potential constraints and highlight and quantify the already large and increasing role hindrances that may afect the extent to which growth that business data plays in the economies of four European opportunities are realised in full countries: the UK, Ireland, Germany and the Netherlands. • To provide disaggregated comparisons of the Data Economy on a sector-by-sector basis in each country For businesses, the gathering, storage and analysis of large quantities of data from diferent parts of their operations • For the UK, Germany and Netherlands, also to provide is widely understood to be already generating significant a disaggregated assessment on a regional basis.4 opportunities for production and supply chain cost savings. Moreover, many businesses are now also using data analysis to understand and spot patterns of behaviour, so enabling the creation of improved products and services.
Although the contribution of the Data Economy is already thought to be very substantial – manifested, for example, in terms of contributions to cost savings, revenue growth and the generation of economic output in the form of Gross Value Added (GVA)3 – up-to-date and comprehensive quantified estimates of the scale of this contribution in each of the four countries have yet to be produced.
DATA ECONOMY REPORT 2018 7
2 | Åse Dragland from SINTEF is the most frequently cited source of this calculation. 3 | Gross Value Added is essentially the diference between the value of output minus the costs of intermediate consumption. GVA is also used to assess the contribution of individual businesses, industrial sectors and sub-national areas to the overall value of production in an economy (GDP). 4 | The standard regions are defined by the NUTS2 system of classification developed and maintained by the European Union (NUTS = Nomenclature d’Unités Territoriales Statistiques). What we mean by the Data Economy
In this report we define the Data Economy as the financial The economic value for the economy delivered by the Data and economic value created by the storage, retrieval and Economy derives from several sources, including: analysis – via sophisticated software and other tools – of large volumes of highly detailed business and organisational • Widespread adoption of Big Data and related data at very high speeds (so-called Big Data). technologies (such as the IoT), leading to the maintenance or acceleration of sector and economy- Opportunities for the creation of financial value for individual wide productivity growth businesses through the analysis and interpretation of • Opportunities for eficiency-driven reductions in the diferent types of Big Data include: price of goods and services ofered to customers
• Potential for the realisation of enhanced levels of • Increased potential for domestically-based businesses operational eficiency and sectors to be successful in the face of international competition, either in export or home markets • Eficiencies in the management of business procurement and supply chains • Opportunities for the creation of improvements in the quality and specification of goods and services • The making of improved strategic and tactical business decisions • Analysis of data by and for Government departments and agencies can lead to improved public services and/ • Innovation in the form of new types of products or or cost eficiencies in the delivery of services to users services that can be sold to existing or new customers. • The rising demand for Data Economy services (such The eficiencies, improved decision-making and innovations as the design and maintenance of data analytics that result from the analysis of Big Data can lead to increases storage and retrieval infrastructure and applications) in business revenues and/or cost savings, resulting in also creates opportunities for a growing ICT services enhanced profitability for individual businesses. segment of the economy stimulating growth of existing providers and opportunities for the formation of new Over time, as these gains become recognised and more businesses to supply these services widely adopted by other businesses, they can lead to the • The creation of additional and high-value employment growth of sectors and the creation of benefits for customers opportunities from the demand for highly skilled labour in the form of lower prices. required by businesses to undertake Big Data analytics or to provide other types of Data Economy services. Also included in the definition of the Data Economy is the Internet of Things (IoT). The IoT is essentially the linking of devices, sensors and other technologies to the internet which leads to the generation of very large volumes of data of great relevance to business operations. The advent of the IoT therefore creates further opportunities for the production and sharing of business relevant data.
8 DATA ECONOMY REPORT 2018 Approach
The study has involved four main stages, as follows:
.01 MOBILISATION
.02 DATA AND DOCUMENT REVIEW Mobilisation
The study mobilisation stage served to clarify the study objectives and identify sources of data, documents and other sources of insight. .03 CONSULTATIONS Data and document review
The mobilisation phase was followed by the literature review stage, which provided a detailed and extensive review of the academic and non-academic literature covering the characteristics, growth drivers and potential constraints .04 on the Data Economy. Although country-specific sources ECONOMIC were obtained where possible, the process also involved the MODELLING review of documents produced by the European Union and other pan-European entities, and there was a large number of materials identified from the United States and other non- European sources. In total, over 200 relevant documents were identified and reviewed as part of this process.
DATA ECONOMY REPORT 2018 9 Consultations by 19 sectors based on standard industrial classifications. In the case of the UK, Germany and the Netherlands the model The consultation phase was originally conceived as was also disaggregated by standard regional geographies. a mechanism to fill any gaps that remained after the completion of the literature review stage. However, because The base year for the development of estimates of measures the data and document review process resulted in the of economic performance (such as GVA and employment) identification of a much larger number of highly useful was 2016, which is the most recent year for which the resources than was originally expected, the consultations relevant data is available across all geographies. Equivalent were designed to be much more targeted and involved datasets were also assembled for the years 2012-2016 so interviews with four organisations: that the evolution of the trajectory of growth over the most recent 5-year period could be assessed. • The UK’s Digital Catapult The types of data captured for each country included • The Data Science Institute, Imperial College London the following: • Tech UK
• The Open Data Governance Board (Ireland). • Levels of business turnover and GVA • Employment data, defined in both sectoral terms The focus of the consultation interviews was to obtain (Standard Industrial Classifications) and occupational additional insights (and to test our interim conclusions) terms (Standard Occupational Classifications) on topics such as: • Productivity trend data
• The role that data is playing in the modern, knowledge- • Labour market data (such as estimates of technical driven economy skills gaps and skills shortages in key sectors)
• The general extent to which businesses and public • Business demographic data: the number of business organisations are currently exploiting the full potential units and establishments involved in the provision of of data analytics infrastructure and applications to Data Economy services achieve operational eficiencies and contribute to other • Data sourced from regular or ad-hoc business surveys. corporate objectives
• Drivers for the growth of the Data Economy The sources of data included the central statistics agency for each country, with additional data obtained from • Potential future constraints on the growth of the Data sources including Eurostat and the OECD (Organisation for Economy and what needs to be done to mitigate these Economic Co-operation and Development). potential hindrances
• Views of the future evolution of the Data Economy To enable estimates of the future growth of the Data • Views about how the utilisation of data varies across Economy it was also necessary to obtain or develop sectors and national geographies. economic forecasts for each country disaggregated by sector for the period 2016-2025. In the case of the UK, Germany and the Netherlands, sector-based regional growth forecasts Economic modelling were also developed. Insights gathered during the document review stage – supplemented with additional insights gained through the The Data Economy models used for each country are consultation process – were helpful in the development of a satellites of independent forecasting model to which we sector-based model used to estimate the current extent of subscribe and can manipulate through sensitivity testing and the Data Economy contribution in each of the four countries. scenario modelling. The model developed for each country was disaggregated
10 DATA ECONOMY REPORT 2018 The underlying econometric model for each country The sources of data and insights include: provides historic trend data (from 1981) for key economic indicators: its structure quantifies relationships between .01 factors such as consumption spending, business investment National and regional economic datasets published by and public spending, labour market indicators and Government or other statistics agencies international trade. .02 The forecast model subscription allows the introduction Data from bespoke business surveys of additional assumptions and variables to generate variant scenarios and forecasts that are not constrained to the .03 model’s central forecasts. We have used data and insights Document review: over 200 academic and other documents generated through a series of Data Economy assignments have been reviewed that pertain to the international for various clients to develop alternative scenarios for Data Economy. each economy predicated on a (positive) shock generated through:
.01 Gains for business productivity: additional investment in data analytics infrastructure and applications by businesses can be expected to generate additional productivity for factors deployed; for example, in agriculture, better use of data can reduce the need for treatment of crops with pesticides and fungicides, thereby reducing costs and increasing eficiency. Likewise, in logistics, data analytics can increase the productivity of vehicle fleets. However, the extent of this productivity boost varies by sector
.02 Opportunities for business revenue generation: new products and services utilising data and data analytics (e.g. Big Data opens opportunities for viable treatments for treatments afecting relatively small populations of patients)
.03 Net gains for the net rate of new business formation, i.e. new businesses emerging to take advantage of the opportunities for new products and services created by the advent of the Data Economy
.04 Because of 1-3, there may also be potential for net new job creation, but in some cases these gains may be ofset to some degree both within companies or in supply chains.
DATA ECONOMY REPORT 2018 11 Time frame for the assessment and scenarios
A key objective for this study was to quantify the current value of the Data .01 Economy in each country included within A CENTRAL SCENARIO its scope. The most up-to-date year for The growth expected if current which the relevant data is available across macro-economic forecasts for the two countries are achieved, and if the all four countries is 2016. The estimates currently expected trajectory of growth of current value therefore relate to the of the Data Economy is maintained. calendar year 2016.
The study also provides an analysis of the recent trajectories and sources (by sector) of Data Economy growth in each country. .02 The time frame for this analysis is the A PESSIMISTIC SCENARIO period 2012-2016. Constraints on the future growth of the Data Economy (such as skills shortages or a slow-down in business appetite for investment For two of the countries covered by the in workforce training or technology) prove to report – the UK and Ireland – there are also be greater obstacles to growth than is forward estimates of the potential future expected under the central case scenario. growth of the Data Economy under three alternative scenarios.
The timeframe for the development of .03 these scenarios is the period 2017-2025, AN OPTIMISTIC SCENARIO with the focus for reporting on the contrast The trajectory of growth is stronger because between current (2016) levels of output hindrances on the further development of the and employment associated with the Data Data Economy are addressed. For example, this scenario explores what would be expected Economy, compared to levels expected to to happen if there were accelerated levels of be achieved under each future investment in Data Economy technologies and scenario during 2025. capabilities on the part of businesses, compared to the trajectories expected under the central scenario.
12 DATA ECONOMY REPORT 2018 Structure of the report
The remainder of this report is structured as follows:
CHAPTER 1: CHAPTER 4: DRIVERS OF THE DATA ECONOMY IRELAND DATA ECONOMY RESULTS Provides an overview of the changes that are driving the Provides a similar assessment for the Data Economy of growth of the Data Economy, including technology change Ireland. As is the case for the analysis of the UK, current and and the development of business and organisational future estimates are presented on a sectoral basis for Ireland. applications. The chapter also discusses the mechanisms However, unlike for the UK, the analysis for Ireland in this through which businesses and organisations can generate chapter does not include any sub-national estimates. value through the more widespread utilisation of data, and it also identifies the factors that are potentially inhibiting CHAPTER 5: greater levels of extraction of value from the use of this GERMAN DATA ECONOMY RESULTS data across a range of key sectors such as Manufacturing, Provides an assessment of the current scale of the Data Transportation and Financial Services. Economy of Germany, both on a national and regional basis and disaggregated by sectors. CHAPTER 2: OVERVIEW OF NATIONAL CHAPTER 6: DATA ECONOMY RESULTS NETHERLAND DATA ECONOMY RESULTS Provides a summary of the country-level estimates of the Provides a similar type of analysis for the Netherlands to that current scale of the Data Economy and the sources of this for Germany described above. contribution by industrial and service sector. This chapter also provides a brief basis of comparison of the performance CHAPTER 7 & 8: of the four countries with major economies in Europe (i.e. Provides recommendations on what businesses and France and Italy) and elsewhere (specifically, with the USA, Governments need to do to increase the likely future growth Canada and Japan). trajectory of the Data Economy and to ensure that a greater proportion of the available growth potential is converted CHAPTER 3: into reality. UK DATA ECONOMY RESULTS Provides estimates of the current and expected future trajectory of growth of the Data Economy in the UK, as well as an assessment of the growth trend in the recent past (2012-2016). Estimates for key metrics are presented on both a sectoral and regional basis.
DATA ECONOMY REPORT 2018 13 1 Drivers of the Data Economy
Introduction
Advances in digital technology and the increasing ubiquity This global growth will be driven by ever larger numbers of connected devices and sensors means that there has of people connecting to digital devices for an ever larger been a huge increase in the global rate at which data is number of applications. The amount of data generated each being generated. By one reckoning, 90% of all the data day is expected to be further boosted as novel technologies generated during human history has been created in just the such as virtual reality and autonomous vehicles are 5 past two years. introduced and become widespread in their usage.
The rate at which data is created is currently accelerating, Although the generation of data by consumers in future driven by the rapidly rising number of household and will remain very significant, it is expected that in future at business applications. Consumer generation of data in least 60% of data generated globally will be created by advanced economies is driven by high levels of penetration businesses.8 The growing importance of data to businesses of smartphones and tablet computers and is further boosted will be driven by at least four mechanisms, although there is by the increasing usage of wearable health monitoring potential for overlaps between them. The mechanisms are devices (the latter, for example, generate large amounts of as follows: data every minute of each day ranging from an individual’s location and their movement, to their energy usage, heart .01 rate, sleep patterns and other data). Improved business intelligence and decision-making .02 The growth of consumer data is further boosted by the Cost-eficiencies and revenue growth demand for digital entertainment and communication, .03 ranging from video and music streaming to online computer Opportunities for product and service innovation and new gaming and the sharing of pictures, videos and other forms of enterprise information on social media. .04 Opportunities for new business creation. Simultaneously, business use of data has also increased exponentially, driven by the increasing number of digital It is worthwhile exploring each of these themes briefly in devices and sensors used on production lines, in energy, turn, as they are applicable to most if not all sectors of the transportation and telecommunications infrastructure and in economy and irrespective of whether a business is primarily vehicles used for moving freight and passengers. serving consumer or business-to-business markets.
Moreover, the rate at which data is being Later in this chapter we then turn to consider some specific generated shows no sign of abating: issues and opportunities facing some of the most important sectors of advanced modern economies (such as Financial one prediction is that the daily amount services and Manufacturing) before moving on to consider of data generated globally will increase potential constraints on growth. tenfold over the next eight years, from around 16ZB6 per day in 2017 to over 160ZB per day by 2025.7
14 DATA ECONOMY REPORT 2018
5 | 10 Key Marketing Trends for 2017, IBM. 6 | ZB = zettabyte, or roughly one trillion gigabytes. 7 | What Will We Do When The World’s Data Hits 163 Zettabytes In 2025?, Forbes, 13 April 2017. 8 | Data Age 2025, IDC, 2017. Data as a driver of business growth enables greater levels of adoption of so-called Industry 4.0 technologies creating sustainable advances in productivity Business intelligence and decision-making potential.9
It is axiomatic that the more information a business has Productivity advances and revenue growth opportunities about its operations and the markets within which it is active, through the greater use of data analytics are also available the better placed it will be to make sound business decisions. in consumer-focused areas of activity such as Wholesale & retail and Accommodation & food. For example, analysis The generation of ever greater volumes of data provides of patterns of seasonal or cyclical patterns of customer the potential for the development of more detailed insights behaviours can enable hotels, restaurants and retail into a wide range of issues and challenges facing businesses, businesses to be better prepared (via stock levels or other such as the following non-exhaustive list of opportunities forms of capacity) to anticipate future increases or decreases and themes: in customer demand for certain services or products, leading to increased revenue and lower levels of wastage. • Better insights into customer behaviour and market trends (for example, greater levels of anticipation Product and service innovation of seasonal trends and opportunities for increased revenues via more precise targeting of incentives Linked to the previous point, there are also opportunities to customers) for companies to use business, market and other data to create entirely new products and services to meet the • More eficient procurement and management of supply needs of customers. chains and inventories
• Improved environmental performance (for example, A powerful example of the new types of innovation that a reduced carbon footprint from energy savings via is possible via data analytics comes from the field of life improved vehicle fleet management, more eficient science research and development. For example, McKinsey heating and lighting of intelligent buildings, and has identified that in the United States alone the greater use reduced use of resources) of Big Data analytics in pharmaceutical R&D could generate • More cost-efective compliance with labour market, $US100 billion in additional value annually, by allowing environmental and other forms of regulation the development of new treatments and medicines, by improving the success rate of research and clinical trials and • Identification and management of business threats creating new approaches for more individualised treatments and risks. for patients.10 Many chronic and serious ailments are sufered by relatively small populations of patients, thereby Cost-eficiencies and revenue growth making R&D into treatments for these populations very expensive: productivity advances ofered by Big Data creates The generation of large amounts of data on business opportunities for significant advances in treatments at a cost operations and processes creates large opportunities to that healthcare systems can potentially aford. achieve cost savings in production.
In sectors such as Manufacturing and Construction, such eficiencies can be achieved through more eficient procurement, better utilisation of machines and vehicles, and the identification and elimination of wasted resources and energy used in production. Greater adoption of data analytics infrastructure and applications and the IoT also
DATA ECONOMY REPORT 2018 15
9 | Industry 4.0 is a term used to describe the trend of advanced automation (including robotics) and data exchange in manufacturing processes. It includes cyber-physical systems, the Internet of Things, cloud computing and cognitive computing. 10 | How big data can revolutionize pharmaceutical R&D, McKinsey, April 2013. Enterprise opportunities
While some larger companies may choose to develop in-house data storage and analytics infrastructure and expertise, there are clear opportunities for the emergence and growth of specialist companies providing data services for businesses.
According to analysis published by the European Commission, in 2016 there were 120,000 companies involved in providing services relevant to the Data Economy in the UK alone.11 Between 2008 and 2016, the population of these companies grew by an average of 4% per annum. Analysis of employment data in the UK also reveals a strong recent rate of growth of Data Economy employment: rising from around 0.97 million in 2012, to nearly 1.15 million by 2016.12
This implies an average rate of growth of over 3% in the employment base of the industry over this period. Similar rates of growth are also evident in other European countries, including in Ireland, Germany and the Netherlands. More specific details of these trends are found in later chapters of this report.
A key feature of the Data Economy business ecosystem is companies such as Digital Realty (the client for this report), who delivers Data Centre services and provides a range of data analytics support services to businesses around the world.
16 DATA ECONOMY REPORT 2018
11 | European Commission, May 2017 12 | Labour Force Survey, ONS Focus on sectors
Having introduced in broad terms the drivers of growth and the benefits for business ofered by the emergence of the Data Economy, the next step is to examine some .01 of these issues at a business sector level. Although this MANUFACTURING assessment isn’t comprehensive (i.e. not every sector of the economy is discussed in detail), individual assessment is provided for the following:
.02 TRANSPORT
.03 HEALTHCARE
.04 RETAIL
.05 MEDIA AND ENTERTAINMENT
.06 FINANCIAL SERVICES
DATA ECONOMY REPORT 2018 17 Manufacturing
Much of the recent discussion regarding the influence of Big Boston Consulting Group published a report in January Data is set within the context of a so-called fourth industrial 201715 which sets out international comparisons of how revolution, termed Industry 4.0. There is no single definition prepared industry is for Industry 4.0. The research involved of Industry 4.0, but commentators generally agree that it a survey of 1,500 business managers across five countries centres on cyber-physical links and the application of the (UK, France, Germany, the United States and China). The Internet of Things in industry. It is also related to terms study found a range of levels of preparedness for Industry such as ‘industrial internet’ and the ‘digital factory’. Various 4.0: for example, while 80% of UK companies reported they aspects have been cited as important to the Industry 4.0 had made some progress, this proportion was lower than in concept, including: the other countries, such as Germany (where the equivalent proportion was 90%) and France (89%). • Connecting production line machines and sensors • Big Data and analytics • Improved data transfer and storage.
A McKinsey report on this topic surveyed over 300 manufacturers in advanced economies.13 It found that only about half of manufacturers were ready for Industry 4.0. The executives surveyed estimated that 40-50% of today’s machines will need to be replaced or upgraded to make them suitable for Industry 4.0 processes. Such levels of investment pose a significant challenge to manufacturers. To take advantage of digitisation, the research suggested that companies will need to gather much more data and make better use of it, take digitisation into account when planning the future of the company, and to prepare for digital transformation through investing in management and workforce training and skills development.
An international survey of 2,000 businesses undertaken by PWC in 2016 found that increased digitisation was expected to both reduce costs and increase sales significantly. Some 33% of survey participants reported that they have already achieved advanced digitisation while 72% expect to have achieved it by 2020. Based on the survey findings, globally manufacturers are expecting to invest over $US900 billion in digitisation by 2020.14
18 DATA ECONOMY REPORT 2018
13 | Manufacturing’s next act, McKinsey, June 2015. 14 | Industry 4.0: Building the digital enterprise, PwC, 2016. 15 | Is UK Industry ready for the Fourth Industrial Revolution?, BCG, January 2017. Transport
The transportation sector is a vast generator of data. The potential present and future benefits of Big Data for Analysis and decision-making based on this data has the transportation have been identified as follows: potential to achieve significant eficiencies and save time and costs for drivers, passengers, freight hauliers and those .01 depending on the timely arrival of goods. Improved information for improved transport system eficiency and capacity. This includes: Vast amounts of transport-related data are gathered by information-sensing mobile devices, remote sensing, .a software logs, cameras, microphones and wireless sensor Improved transport system planning through use of networks. Global technological information per-capita technologies such as GIS (geographic information systems), capacity has approximately doubled every 40 months trafic analytics, predictive analytics, fleet analytics and since the 1980s. Some predictions show that transportation improved transport system modelling data production will be 44 times greater in 2020 than it was in 2009.16 .b Enhanced transport system design through improved The increase in transport data is manifest in the availability modelling and simulation of day-to-day road trafic information available to users in their vehicles, such as through satellite navigation .c systems. Similar passenger information applications provide Vehicle management systems (including vehicle-to-vehicle, departure and journey management information for public vehicle-to-infrastructure, integrated supervision systems, transport users. Payment for transport (ticketing and tolling) driver assistance systems and parking management is increasingly reliant on data-dependent technology, systems, etc.) applications and services. .d In all modes of transport, there are already large quantities Infrastructure management systems (including vehicle-to- of data available for operators to improve performance, infrastructure, network connectivity, trafic management, eficiency, service provision, safety and security. Data also infrastructure monitoring, and weather management, etc.) enables operators to manage demand conflicts, customer service, environmental impacts and innovation. This can .e be seen in systems such as trafic signal co-ordination, Intelligent fleet and logistics management, including for trains reporting track defects, on-line flight check-ins and logistics and distribution but also for postal services and cargo tracking. emergency services
.f Improved risk management including safety, security, system resilience. For example, for public transport operators the advent of smart ticketing has already produced reductions in the incidence of lost revenues from ticket evasion (or customers simply not having the right ticket for the journey).
DATA ECONOMY REPORT 2018 19
16 | Deriving Transport Benefits from Big Data and the Internet of Things in Smart Cities, Womble Bond Dickinson, 2017. .02 A key challenge for life science industries is translating Improved levels of customer service and experience, scientific discovery into commercially viable medicines and including the delivery of more reliable and punctual public treatments for people with various or multiple illnesses transportation services: and conditions. The process is tending to become more challenging, time consuming, risky and expensive because .a of tightening regulations and an extended timetable for Improved passenger information systems allow users to realisation which can take 15 years or more, and with manage their journeys better (for example information about an increasing proportion of potential new products not a late service could allow users to plan and implement an receiving regulatory approval along the way. alternative service) The emergence of technologies such as Big Data analytics .b make it easier to design better clinical trials accessing Integrated payment systems cut down on lost revenue national and international drug trial and healthcare data and by targeting specific patient sub-populations. .c In addition, smart ticketing saves users’ time and provides McKinsey and other commentators have forecast that Big opportunities for value added services (e.g. discounts on Data analytics could substantially reduce R&D costs for refreshments or ofers from partner retailers, etc.) pharmaceutical companies and increase the chances of drugs under development gaining approval.18 Big Data in life .03 sciences is driven by the opportunity to deliver new drugs Improved safety performance, such as trains and buses for specific patient populations, and has arisen because reporting emerging faults or trains reporting potential rail of the combined impacts of low cost genome sequencing, tracks defects the availability of electronic medical records, increasing personalised medical treatments, and the collection of .04 ongoing data once treatments have entered the market. Improved environmental performance – more eficient A linked technological development is the emergence of vehicle running reduces fuel consumption, reduces a range of wearable and other devices that can monitor production of carbon and emissions of other gases patients’ usage of medicines, monitor symptoms and and particulates treatment progress and outcomes.
The further development of transportation data systems The faster and more certain translation of scientific discovery married to a 5th generation mobile network ofers into viable healthcare treatments will, in turn, generate better opportunities for the development of driverless cars and healthcare outcomes for patients whose conditions and other autonomous vehicles. illnesses are benefited by the delivery of new medicines and treatments. Healthcare
It has already been mentioned in this chapter that McKinsey has identified very large savings and anticipated substantial productivity advances from greater use of Big Data analytics in pharmaceutical R&D. Big Data creates opportunities for afordable development of new treatments and medicines in fields such as cancer, cardio-vascular health and dementia by improving the success rate of research and clinical trials and creating new approaches for more individualised treatments for patients.17
20 DATA ECONOMY REPORT 2018
17 | How big data can revolutionize pharmaceutical R&D, McKinsey, April 2013. 18 | Big Data in pharmaceuticals, The Manufacturer, October 2014. Retail Drivers for change in these industries linked to Big Data include: Larger retailers have developed a wide range of data-driven demand forecasting tools to help them anticipate sales • Opportunities for businesses to develop a highly trends and to anticipate the evolution of customer demand detailed understanding of their customers based on patterns. Many larger retailers have also invested in card diferent types of interaction (such as product usage, schemes and other programmes that help to track customer social media interactions, etc. as well as customer purchasing behaviours and to personalise discounts and preferences and attitudes) and to use that data to build other ofers designed to maximise customer revenue and highly engaged relationships with customers reward customer loyalty trends. • Products and content: Big Data provides opportunities to produce new types of content in more sophisticated One of the most significant trends afecting the retail ways tailored to the preferences of individual sector over the past decade has been the huge growth in consumers; it can also be used to identify and to tailor online sales. For example, in the UK over 63% of the adult content suited to the personalised needs of customers population has bought an item online, and the annual value based on their histories of previous interactions of goods bought online in the UK is worth over $US84 • Media industry customers are also often a source of billion.19 Moreover, an increasing proportion of online sales content supply for the media industry is made by customers using devices such as smartphones. However, there are significant challenges: the conversion • Big Data can be used to track changing customer rate from ‘adds to basket’ to actual sales is typically only interests and preferences in a fast-moving world. 3%-6%, with smartphone conversion rates at the low end of this range. Greater use of Big Data analytics on the part of retailers may help retailers significantly increase their conversion rates thereby adding to revenues and profitability.
Many larger retailers and specialist online retailers have 63% developed highly efective online strategies, but some larger retailers, many regional and medium-sized, and most smaller retailers have not kept up with these developments. Long term competitiveness requires them to develop some form £61 of online presence, even if it is simply click and collect. On billion* this basis, greater use of data by a wider range of retailers (in terms of their size) is likely to be important in helping small to medium sized retailers stay competitive in an increasingly online world.
Media and entertainment
Media and entertainment business have generally been at the forefront of implementing new technologies including digital technology. The advent of digital platforms has reduced barriers to entry to the industry and therefore created a more competitive environment, with new opportunities such as digital advertising threatening traditional revenue sources.
DATA ECONOMY REPORT 2018 21
*$84 billion converted £61 billion, with exchange rate as at April, 2018. 19 | Northern Europe report, We are Social, January 2017. Financial services • Enhanced risk and regulatory management: over the last decade the finance sector has faced a large increase The advent of Big Data has created new opportunities in regulation and reporting requirements, but now for the growth of the financial services sector and the Big Data is improving the detection of non-compliant achievement of significant operational eficiencies. behaviours by staf as well as improving financial The financial technology sub-sector was an enthusiastic institution resilience (using simulation tests, stress- early adopter of Big Data technology. Uses include the testing and other data-driven models) combination of trader performance data, market data, • Another role of Big Data in financial services is to help unstructured news, user data, and general ledger data to detect patterns of investment or insurance fraud on the gain previously impossible insights. This enables the creation part of customers. of much more powerful real time analytical and decision- making power.20
Survey research undertaken by Accenture reveals that globally 71% of firms in the financial services sector are developing Big Data and predictive analytics, and that a 71% similar proportion state that Big Data is critically important to globally their firms.21 Based on survey responses, Accenture calculates that annual investment in $9 billion data-related capabilities is already likely to be in the order of $US9 billion annually, and that this investment is currently increasing at around 25% per annum.
Opportunities for the better utilisation of data analytics centres on the following themes: 25% • Enhanced decision-making: improved decisions based on evidence, enabling more eficient and faster identification of business problems and opportunities, including for enhanced productivity and cost-eficiency
• Service and product innovation: Big Data creates opportunities for new services and products based on the intelligent interpretation of customer behaviour and market trends
22 DATA ECONOMY REPORT 2018
20 | The Big Data dilemma, House of Commons Science and Technology Committee, 2016. 21 | Exploring Next Generation Financial Services: The Big Data Revolution, Accenture, 2016. Constraints and barriers to growth of the The benefits of data sharing are Data Economy already evident. For example, The review of national and sector-level documentary evidence reveals several concerns and challenges regarding it is estimated the value of time the extent to which individual businesses, industrial sectors saved resulting from the release and Governments are in a position to secure the eficiency and service innovation benefits that stand to be gained – of Transport for London’s both currently and in the future – as a result of the advent of the Data Economy. Open Data is c.£58 million per year, from an annual spend The most important of these constraints have been 23 identified by the European Commission as being:22 of less than £1m.
• A lack of general awareness of the functioning and the Although the UK was ranked top in the 2016 global Open potential benefits of data analytics Data Barometer, the country’s rate of progress on Open • Resistance to and fear of potential organisational Data is reported to have slowed, signalling that new political change entailed by Big Data analytics will and momentum may be needed as dificult elements of Open Data are tackled.24 Of the countries considered by the • Absence of available resources regarding the ability to 2016 report, only the Netherlands (7th) ranks in the top ten integrate and manage large datasets countries on this measure. • Shortages of skilled data-savvy staf With respect to private data, there is some evidence that • The lack of financial means to make the technological there may be growing unease or distrust with respect to and stafing investments – this is a challenge especially the ability of companies and Governments to protect the for SMEs. security of their data following several well-reported data security lapses on the part of financial service providers, Key points regarding each of these constraints are retailers and telecommunications service providers. provided below.
Some companies are also concerned about what they regard Public acceptance of data gathering and sharing as a lack of clarity in the regulatory framework with respect to data privacy, data security and protection.25 Open data is important to the growth of the Data Economy because it dramatically reduces the time and resources The introduction of the General Data Protection Regulation needed to understand what Government is doing. Because (GDPR) across the European Union in 2018 may lead to Open Data is made available in bulk and in formats that significant improvements in both public confidence and simple computer programmes can analyse, comparing and clarity over regulation. However, it also comes with risks, combining data from diferent sources becomes faster and and so the net benefits of the regulation are not currently easier. This greatly enhances the ability of policymakers and possible to forecast with confidence. others to find solutions to complex development problems and for businesses to identify and develop new commercial In particular, any increase in restrictions on the accessibility opportunities. of Open Data or the ability of private companies to store and utilise customer data – whether from GDPR or other causes – threatens to restrict the development of data applications and innovations and is a significant threat to the future growth of the Data Economy.
DATA ECONOMY REPORT 2018 23
22 | Enter the Data Economy EU Policies for a Thriving Data Ecosystem, European Commission, January 2017. 23 | Deriving Transport Benefits from Big Data and the Internet of Things in Smart Cities, Womble Bond Dickinson, 2017. 24 | Open Data Barometer Third Edition, World Wide Web Foundation, April 2016. 25 | EU Policies for a thriving data ecosystem, European Commission, 2017. Investing in data analytical systems: cultural and In modern economies the successive roll-out of the next financial barriers generation of advanced communications technology (such as high-speed broadband and high-capacity mobile Sector-based business surveys referred to earlier in this telecommunications infrastructure) tends to favour more chapter reveal the very significant level of recent, current and densely populated urban areas as these provide a higher expected future levels of investment required by companies density of household and business customers. Would-be to gather and use business data. users in less densely populated areas (and/or areas with topographical challenges) may face significant delays in Keeping abreast of required investment in data storage receiving services and, in some cases, services may never and analytical capability may require expensive investment be made available. in computer and data analytical technologies, as well as complementary investment in staf recruitment and/or staf This creates the danger that the economic and social training and development. Obviously for all businesses there advantages that stand to be created by the Data Economy are competing areas for business investment, so attaching may not be fully shared, with businesses and households in the appropriate priority to enhance data capabilities may rural or semi-rural areas facing significant disadvantage. In be a challenge for some businesses, especially smaller and addition, some industries that operate in these areas (such medium-sized businesses. as agriculture) or across these areas (such as the distribution and logistics sectors) may also be unable to exploit fully the Responses from surveys reveal that many SMEs struggle potential advantages ofered by the Data Economy because to secure the finance they need to invest in fast-evolving of spatially uneven infrastructure investment. Moreover, technologies, including advanced computer systems. the advent of new opportunities such as autonomous Even companies that recognise the longer-term competitive vehicles could be significantly delayed or constrained by imperative of increasing levels of investment in advanced the patchy nature of telecoms infrastructure in less densely technology may struggle to adequately prioritise investment populated areas. in sophisticated computing and data analytics capabilities and infrastructure.
Infrastructure and standards
In some cases, there may also be infrastructure constraints or concerns about the reliability of data. The conditions necessary for the full exploitation of the possibilities of the Data Economy include:
• Availability of high quality, reliable and trusted data from large datasets
• Availability of robust standards and interoperability of data
• Enabling infrastructure such as fast broadband, large and flexible computing resources, deployment of smart connected sensors and availability of abundant bandwidth.
24 DATA ECONOMY REPORT 2018 Skills Moreover, the shortage of skills is expected to grow remorselessly as Big Data reaches further into the economy. The availability of digital skills is reported to be approaching This shortage creates economic implications but also a crisis.26 There are two dimensions to the skills deficit: potentially puts the quality and security of this data at risk. There is a range of initiatives to help develop computing and • Digital skills shortages – the ability of companies digital skills, but the danger is that the wider set of Big Data and organisations to recruit suficient numbers of skills is not being strategically addressed. appropriately skilled staf to carry out work that is needed to grasp the opportunities created by the The ultimate risk is that businesses and organisations are digital economy unable to grow the Big Data sector at the fastest possible pace, and as a result value and job-creating opportunities • Digital skills gaps – any deficiencies in technical or are squandered. managerial skills amongst existing employees that may constrain organisations from recognising and implementing strategies to take the opportunities the Data Economy ofers.
Realisation of the full potential value of the Data Economy requires access to the right skills: data engineering skills to develop a robust data infrastructure, data analysis skills to 153,000 extract valuable insights from data, and business skills to digitally skilled apply them.27 workers
Previous work undertaken by Development Economics on behalf of telecoms provider O2 quantified that nationally an additional 153,000 digitally skilled workers per annum would be needed by the UK economy over the 2015-2020 period alone. However, the shortage of digitally skilled workers is not just confined to the UK: the growth in demand across Europe and other advanced economies has been documented by the European Union and other commentators.
The competition for workers with the necessary skillsets is intense, as these workers are also sought for other knowledge-economy activities and applications across a wide range of economic activity.
DATA ECONOMY REPORT 2018 25
26 | For example, House of Commons Science and Technology Committee, The Big Data Dilemma, 2016. 27 | Skills of the Datavores, Nesta, 2015. 2 Overview of National Data Economy Results
Introduction
The purpose of this chapter is to provide an overview and key points of comparison of the data economies of four European countries: the UK, Ireland, Germany and the Netherlands. The metrics used in this assessment are:
• The GVA associated with the Data Economy in each country in the most recent year for which data is available (2016), and the proportion of the country’s overall economic output that this represents
• The level of direct employment (measured by workforce jobs) associated with the Data Economy in each country in the most recent year for which data is available (2016)
• The composition of the overall Data Economy by industry, using standard industrial classifications, thereby enabling international comparisons to be made
• The extent to which the Data Economy in each country has grown since 2012
• The extent to which the Data Economy in each country was delivering against its full potential in 2016.
In addition to the comparisons between the four countries, the chapter also provides summary Data Economy statistics (for GVA and direct employment) enabling comparisons with five other major economies (the USA, Canada, France, Italy and Japan). Together with Germany and the UK, these additional five countries comprise the G7 group of major economies.
26 DATA ECONOMY REPORT 2018 Current (2016) size of the national data economies
This sub-section provides estimates of the scale of the Data
Economy in each of the four European countries that are the Indicator UK Ireland Germany Netherlands principal focus of this report. The metrics used to assess the scale of the Data Economy in each country are as follows: 2016 GVA €millions 89,826 9,962 108,327 24,637 (2016 prices)
2016 GVA as % of .01 4.2% 4.0% 3.8% 3.9% national economy Value of economic output – measured by GVA 2016 Data Economy employment 1,147 61 1,323 247 (direct, ‘000s) .02 2016 Data Economy The proportion of the overall size of the national economy jobs as % of total 3.3% 3.0% 3.2% 3.2% workforce jobs attributable to the Data Economy
.03 In employment terms the UK remains the largest Data Economy, with 3.3% of national employment accounted for The amount of direct employment – measured by workforce by this category. However, the diference between the UK jobs – accounted for by the Data Economy and the other countries is quite small: in the Netherlands and .04 Germany the proportion is 3.2%. The proportion of the overall employment in each economy accounted for by the Data Economy
In each case the estimates are for the year 2016, which is the latest year for which relevant data is available.
To make it easier to compare the absolute size of the GVA attributable to the Data Economy in each country, in this chapter the UK result is expressed in Euros.28 In the UK-specific chapter which follows, UK financial results are presented using Pounds Sterling.
The largest Data Economy by value among the four countries assessed here is that of Germany (€108 billion). However, as a proportion of the overall national economy the German Data Economy is the smallest (3.8%). The largest Data Economy in proportionate terms is the UK (4.2%), followed by Ireland (4.0%).
DATA ECONOMY REPORT 2018 27
28 | This conversion has used the yearly average £:€ exchange rate for 2016 (1:1.225), sourced from https://www.ofx.com/en-gb/forex-news/historical-exchange-rates/yearly-average-rates/ Comparison with other countries
The table below sets out some key metrics for the estimated size of the respective Data Economy in 2016 for the four countries that are the principal focus of this report. The benchmarks that are provided are the United States, Canada, France, Italy and Japan (which, together with Germany and the UK comprise the G7 countries).
Data Economy jobs as Data Economy GVA Data Economy GVA as Data Economy em- Country Ranking % of total workforce Ranking €millions (2016 prices) % of national economy ployment (direct) jobs
United States 858,349 5.1% 1 6,698 4.1% 1
Canada 59,443 4.3% 2 677 3.4% 2
Japan 187,499 4.2% 3 2,126 3.2% 4
UK 89,826 4.2% 3 1,147 3.3% 3
Ireland 9,962 4.0% 5 61 3.0% 7
Netherlands 24,637 3.9% 6 247 3.2% 4
France 80,206 3.6% 7 859 2.8% 8
Germany 108,327 3.8% 7 1,323 3.2% 4
Italy 51,825 3.1% 9 620 2.4% 9
When a wider set of international countries is used, United the largest Data Economy in proportionate terms Indicator France Italy Canada Japan States when GVA is considered is that of the United States
(5.1%), whereas the smallest is that of Italy (3.1%). 2016 GVA €millions 80, 206 51,825 858, 349 59,443 187,499 The extent of the Data Economy in Canada and (2016 prices) 2016 GVA as % of Japan is similar to that of the UK in terms of both 3.6% 3.1% 5.1% 4.3% 4.2% national economy output and direct employment. 2016 Data Economy 859 620 6,698 67 7 2 ,126 employment (direct)
Data Economy jobs as 2.8% 2.4% 4.1% 3.4% 3.2% % of total workforce
28 DATA ECONOMY REPORT 2018 Disaggregation of GVA by industry (2016)
The composition of the Data Economy – in terms of In the UK the most significant other contributions come from economic output – can also be assessed according to the the Financial and Professional services sectors, whereas in contributions made by business and organisation sectors. the other countries the Manufacturing sector is also a major The breakdown of these contributions in proportionate component. In the Netherlands, Financial services is also terms is summarised in the table below. important, as is the Wholesale & retail distribution sector. The largest contribution in proportionate terms in each country is made by the ICT sector, with this proportion ranging from 34% in the Netherlands to nearly 50% in Ireland.
UK Ireland Germany Netherlands Sector (Sections) % of total % of total % of total % of total
A Agriculture, forestry, fishing 0.1% 0.1% 0.1% 0.4%
B Mining & quarrying 1.2% 0.4% 0.5% 0.6%
C Manufacturing 6.4% 16.7% 19.5% 9.7%
D Electricity 1.7% 0.8% 1.8% 1.6%
E Water supply 0.4% 0.2% 0.5% 0.6%
F Construction 2.3% 0.9% 2.1% 2.0%
G Wholesale, retail 4.7% 2.4% 4.9% 6.3%
H Transport 2.9% 1.2% 2.4% 2.6%
I Accommodation & food 0.1% 0.1% 0.1% 0.2%
J ICT 41.3% 49.7% 34.7% 34.2%
K Financial services 15.8% 13.5% 9.7% 17.1%
L Real estate activities 5.0% 2.1% 4.8% 2.5%
M Professional services 7.0% 5.7% 6.1% 8.6%
N Business support services 2.3% 1.8% 2.9% 3.5%
O Public administration 3.2% 1.5% 3.8% 3.4%
P Education 2.0% 1.1% 1.8% 2.1%
Q Health 1.8% 1.2% 2.4% 3.1%
R Arts, entertainment, recreation 1.0% 0.3% 0.9% 1.0%
S Other services 0.8% 0.2% 1.1% 0.6%
Total 100.0% 100.0% 100.0% 100.0%
DATA ECONOMY REPORT 2018 29 Growth of Data Economy: 2012-2016 2012 GVA 2016 GVA 2012-2016 Change Country (millions) (millions) (%) The trajectory of growth of the Data Economy can be measured in terms of both employment and economic UK (£) 55,284 73,327 33% output. Depending on which measure is used, the messages about which country has been growing most strongly over Ireland (€) 6,065 9,962 64% the 2012-2016 period varies slightly. Germany (€) 71,741 108,327 51%
The first table provides inflation-adjusted data on value of Netherlands (€) 17,494 24,637 41% economic output associated with the Data Economy in both 2012 and 2016. From this perspective, the fastest growing data economies are in Ireland (64% growth between 2012 and 2016) and Germany (51%). The UK grew at 33%, which was nearly half the rate at which the Irish Data Economy grew over this period.
Another perspective is ofered by comparison of the changing proportion of overall employment in each country contributed by the Data Economy. In the UK this grew by around 8.3% between 2012 and 2016, whereas in Ireland it grew by nearly 31%. On this basis the German job growth performance wasn’t as strong as was the case with GVA, with the proportion of overall employment accounted for by the Data Economy growing by just over 11% compared to nearly 14% in the Netherlands.
2012 Data Economy jobs as % 2016 Data Economy jobs as % 2012-2016 Change Country 2012-2016 Change (%) of National Workforce of National Workforce (percentage points)
UK 3.06% 3.31% 8.3% 0.25pp
Ireland 2.33% 3.05% 30.9% 0.72pp
Germany 2.91% 3.24% 11.3% 0.33pp
Netherlands 2.81% 3.20% 13.9% 0.39pp
30 DATA ECONOMY REPORT 2018 Change in composition: 2012-2016
The change in the size of the GVA contribution of the Data Data summarising the proportionate contributions to overall Economy can be viewed in several ways: change occurring between 2012 and 2016 (with adjustments made for inflation) are set out in the table on the next page. • First, the proportionate contribution made to the The data indicates that the ICT sector was the largest overall change occurring between 2012 and 2016 contributor to growth in each country, ranging from 32% in each economy in the Netherlands to nearly 50% in Ireland. Notable other contributions include: • Second, the proportionate change in the absolute size of the contributions made by each business sector in • Manufacturing – accounting for nearly 24% of growth in each country over the same period. Ireland and 17% in Germany
The first approach is useful because it reveals where the • Financial services – accounting for 10% of growth in the largest sources of growth have occurred. The second Netherlands and nearly 12% in the UK approach is also useful because it highlights the sectors • Professional services – accounting for between 7% and that are growing the fastest (albeit in some cases from a 10% of growth in each country. low base).
Manufacturing 24%+ Ireland
17%+ Germany
Financial services 10%+ Netherlands
12%+ UK
Professional services 7-10% in each country
DATA ECONOMY REPORT 2018 31 Some notable variations are also evident:
• Transportation made a much larger contribution to the • Business support services made a significant growth of the Data Economy in the UK compared to its contribution to the growth of the Data Economy in the contribution to the other three countries Netherlands but much less so elsewhere
• Wholesale and retail trade made a significant • Education and Health made much more significant contribution to Data Economy growth in the contributions in Germany and the Netherlands Netherlands but only a very small contribution in compared to the UK and Ireland. Ireland, and a similar pattern also occurred with respect to real estate services
UK Ireland Germany Netherlands Sector (Sections) 2012-2016 % % of total % of total % of total
A Agriculture, forestry, fishing 0.2% 0.2% 0.2% 0.8%
B Mining & quarrying 1.7% 0.5% 1.0% 1.2%
C Manufacturing 4.3% 23.5% 16.9% 9.5%
D Electricity 2.8% 0.5% 1.2% 0.8%
E Water supply 0.9% 0.3% 0.9% 0.6%
F Construction 4.1% 1.5% 3.4% 3.2%
G Wholesale, retail 6.3% 1.7% 6.4% 9.5%
H Transport 4.9% 1.0% 3.1% 3.4%
I Accommodation & food 0.3% 0.2% 0.2% 0.3%
J ICT 41.7% 49.6% 34.2% 32.6%
K Financial services 11.5% 8.4% 7.6% 10.0%
L Real estate activities 5.1% 1.7% 4.8% 3.6%
M Professional services 7.7% 7.2% 7.1% 9.2%
N Business support services 2.7% 2.3% 2.9% 5.3%
O Public administration 1.0% 0.3% 3.2% 2.6%
P Education 0.9% 0.2% 1.8% 2.1%
Q Health 2.2% 0.5% 2.9% 3.4%
R Arts, entertainment, recreation 0.7% 0.1% 0.9% 1.1%
S Other services 1.1% 0.1% 1.4% 0.8%
Total 100.0% 100.0% 100.0% 100.0%
32 DATA ECONOMY REPORT 2018 The second table shows the relative extent of growth in each and Construction, albeit in most cases these sectors are sector. Some of the largest growth sectors in proportionate growing from a comparatively small base. terms including Agriculture, Accommodation & food services
UK Contributions Ireland Contributions Germany Contributions Netherlands Contributions Sector (Sections) to overall change to overall change to overall change to overall change 2012-2016 (%) 2012-2016 (%) 2012-2016 (%) 2012-2016 (%)
A Agriculture, forestry, fishing 101% 159% 113% 154%
B Mining & quarrying 52% 93% 164% 137%
C Manufacturing 20% 123% 41% 40%
D Electricity 71% 33% 28% 18%
E Water supply 95% 84% 147% 40%
F Construction 82% 186% 119% 89%
G Wholesale, retail 49% 39% 81% 77%
H Transport 72% 48% 79% 59%
I Accommodation & food 101% 100% 95% 109%
J ICT 33% 64% 50% 38%
K Financial services 22% 32% 36% 20%
L Real estate activities 33% 47% 52% 73%
M Professional services 37% 98% 65% 45%
N Business support services 41% 100% 51% 79%
O Public administration 8% 9% 39% 29%
P Education 12% 10% 51% 41%
Q Health 41% 20% 68% 47%
R Arts, entertainment, recreation 22% 19% 52% 48%
S Other services 48% 25% 79% 70%
Total 33% 64% 51% 41%
DATA ECONOMY REPORT 2018 33 Current size of the Data Economy versus potential
A further basis of comparison is an assessment of the extent to which the data is being utilised to its full potential in each country.
This assessment involves the production of current (2016) estimates of the size of the Data Economy in each country, which is then compared to the estimated size it could have reached if constraints (both on demand side and the supply side) were not in place. For example, if issues such as skills gaps and skills shortages were no longer a factor limiting the size of the Data Economy in each country.
The table below sets out estimates for 2016 of both the current actual size and estimated full potential size of the Data Economy of each country. The final column is simply the proportion of actual size compared to potential size.
On this basis, the UK is estimated to be currently achieving 58% of its potential, with Germany achieving 55%. The worst performing country on this basis is the Netherlands, which is estimated to be currently achieving only about 49% of its potential.
2016 2016 2016 Country Data economy Data Economy full Data Economy as GVA potential GVA % of potential
UK 89,826 153,936 58% (€millions)
Ireland 9,962 19,108 52% (€millions)
Germany 108,327 196,269 55% (€millions)
Netherland 24,637 49,838 49% (€millions)
34 DATA ECONOMY REPORT 2018 3 UK Data Economy Results
Introduction 2016 GVA £millions Sector (Sections) % of total (2016 prices) The focus of this chapter is the production of estimates A Agriculture, forestry, of the current and potential future size of the UK’s Data 71 0.1% fishing Economy. The most recent year for which data is available is 2016. The recent trajectory of change over the 2012-2016 B Mining & quarrying 881 1.2% period is also assessed. The principal metric is GVA, although C Manufacturing 4,702 6.4% there are also estimates for employment and business turnover/cost savings generated through the utilisation D Electricity 1, 236 1.7% by businesses and organisations of their data. Future estimates are provided for the year 2025. All financial values E Water supply 315 0.4% are provided in terms of millions of Pounds Sterling using F Construction 1,653 2.3% a 2016 price base. As well as providing current estimates and future predictions on a sectoral basis, the chapter also G Wholesale, retail 3,440 4.7% provides a sub-national spatial assessment using standard UK regional geographies. H Transport 2 ,111 2.9%
I Accommodation 100 0.1% Current (2016) size of the UK Data Economy & food
J ICT 30, 267 41.3% The UK Data Economy is estimated to have generated economic output (GVA) worth £73.3 billion in 2016. K Financial services 11,605 15.8% The largest contributors to this total were provided by the ICT, Financial services and Professional services sectors: L Real estate activities 3,670 5.0% these together accounted for 64% of the total. M Professional services 5,136 7.0%
N Business support 1,709 2.3% services
O Public administration 2 , 329 3.2%
P Education 1,469 2.0%
Q Health 1, 327 1.8%
R Arts, entertainment, 702 1.0% £73.3 recreation billion in 2016 S Other services 602 0.8%
Total 73, 327 100%
DATA ECONOMY REPORT 2018 35 The scale of the estimated contribution varies significantly 2016 GVA £millions Region % of total by sector. This pattern is influenced by several variables, (2016 prices) including: North East 1,818 2.5%
North West 5,736 7.8% • The relative importance of each of the sectors to the economy as a whole: all other things being equal, the Yorkshire & Humber 3,667 5.0%
contribution of large sectors such as Financial services East Midlands 3, 235 4.4% will exceed that of smaller sectors such as Water supply West Midlands 4, 268 5.8% • The extent to which sectors have been growing relative East of England 5,600 7.6% to the rest of the economy in recent years: fast- developing sectors such as Professional services are London 23,664 32.3%
more likely to have been leaders in expanding their use South East 12 ,634 17.2% of technologies such as data analytics South West 4, 542 6.2% • Related to the last point, the absorption rate of new Wales 1,72 2 2.3% technologies varies across sectors. Generally, more knowledge-intensive sectors (such as advanced Scotland 4,607 6.3%
manufacturing, pharmaceuticals, media industries and Northern Ireland 1,099 1.5% ICT) have a greater propensity to invest in advanced Ex-regio 734 1.0% technologies such as data analytics. Most of these are also the fastest growing parts of the economy referred Total 73, 327 100.0% to in the previous point, but there are some exceptions. Note: Ex-regio is the relatively small amount of GVA that cannot be allocated to specific UK regions. The estimated overall GVA generated by the UK economy in 2016 is approximately £1,747 million. On this basis, the Data Economy accounted for approximately 4.2% of the national total for economic output in 2016.
The UK Data Economy can also be estimated by region. The largest contributors are London (32.3%) and the South East of England (17.2%), reflecting in part the greater importance of ICT, financial and professional services in those areas.
36 DATA ECONOMY REPORT 2018 The pattern of contribution by region is influenced by a few In addition to direct jobs, additional employment stimulus is factors, particularly: created via indirect (procurement) and induced (multiplier) efects. The overall number of additional jobs in the UK • The relative scale of the underlying economy in economy supported through indirect and induced efects each region: for example, the economy of London is in 2016 is estimated to be 505,000. (Note: this estimate significantly larger than that of North East England excludes the potential efects of double-counting of ICT or Northern Ireland. As a result, the size of the Data sector supply chain jobs generated by demand for Data Economy in London would also be expected to be Economy services by the rest of the UK economy). larger even if all other things were equal • Of course, the distribution of activity is not evenly The combined direct, indirect spread across all regions. The knowledge intensity of regions indeed varies significantly, with the economies and induced employment of London, South East England and the East of England hosting an above-average share of knowledge-driven stimulus attributable to the sectors such as Financial and Professional services and Data Economy is estimated to ICT. The North of England, the West Midlands, Wales and Northern Ireland on the other hand possess above be 1.652 million jobs in 2016. average representation of other types of industry. In addition, outside of London and the ‘greater South East’ (including the East of England region), sectors such as Construction form a larger relative proportion of the economy as a whole
• Another important factor that favours London and the South East is that the distribution of higher-order corporate functions is more concentrated in that area. That is, high-knowledge activities even for companies that are not operating in what is traditionally thought of as the knowledge-intensive sectors (e.g. retailing). This further implies that a greater proportion of corporate command and control activities (including data analytical functions) are likely to be located in those regions. 1.652 million jobs The total number of direct jobs associated with the Data Economy in 2016, based on second quarter data sourced from the ONS (Ofice for National Statistics) Labour Force Survey, was 1.147 million. This estimate is based on national data disaggregated by occupational category, so cannot be set out by region or industry.
By 2016, direct employment in the Data Economy was estimated to account for 3.31% of the overall number of workforce jobs estimated to be present in the UK economy.
DATA ECONOMY REPORT 2018 37 Growth trajectory since 2012
The UK Data Economy has grown significantly over the past five years, from £55.28 billion in 2012 to £73.33 billion in 2016. This change amounts to an average annual rate of growth of 7.3% p.a. over this period. Annual rate of Comparing the estimates for 2012 to those for 2016, growth of the most significant increases (in absolute terms) have 7.3% p.a. occurred in ICT, Financial and Professional services, and in the Distribution sector (Wholesale & retail trade). However, in proportionate terms the most significant increases have occurred in the Agriculture, forestry & fishing and Accommodation & food sectors, albeit from a comparatively low base.
GVA 2012 GVA 2016 Change Change Sector (Sections) (£millions) (£millions) (£millions) (%)
A Agriculture, forestry, fishing 36 71 36 101%
B Mining & quarrying 579 881 302 52%
C Manufacturing 3,933 4,702 769 20%
D Electricity 72 2 1, 236 514 71%
E Water supply 162 315 154 95%
F Construction 910 1,653 743 82%
G Wholesale, retail 2 , 302 3,440 1,138 49%
H Transport 1, 230 2 ,111 881 72%
I Accommodation & food 50 100 50 101%
J ICT 2 2 ,735 30, 267 7, 532 33%
K Financial services 9, 538 11,605 2 ,067 22%
L Real estate activities 2 ,750 3,670 921 33%
M Professional services 3,742 5,136 1, 394 37%
N Business support services 1, 216 1,709 493 41%
O Public administration 2 ,152 2 , 329 17 7 8%
P Education 1, 308 1,469 161 12%
Q Health 939 1, 327 388 41%
R Arts, entertainment, recreation 575 702 127 22%
S Other services 406 602 196 48%
Total 55,284 73,327 18,043 33%
38 DATA ECONOMY REPORT 2018 These trends may have occurred in part because of a The out-performance of the East of England region may be relative slow-down in the rate of absorption of data analytical influenced in part by the growth of a world-class healthcare technologies amongst some of the ‘traditional’ leading and pharmaceuticals R&D hub centred on Cambridge. The sectors in the Data Economy field, such as Financial services. pharmaceutical sector alone accounts for about one fifth of However, there is some survey-based evidence from the all UK commercial R&D activity, and Cambridge is emerging UK which has detected a noticeable reluctance on the part as the centre of a leading world-class life science R&D hub. of UK manufacturers (compared to major international As discussed above, data analytics ofers considerable competitors) to invest in advanced technologies including productivity and value generating growth potential for advanced automation, robotics, data analytics and other healthcare, which includes not only pharmaceutical research, Industry 4.0 developments.29 It is also notable that but also the development and manufacture of medical Manufacturing is one of the slowest growth sectors in the devices and technologies which are directly linked to the table preceding. The reasons for the technology investment growth of the Data Economy. gap in UK manufacturing are complex and relate in part to the above-average proportion of SMEs in UK manufacturing As mentioned earlier in this chapter, the UK Data Economy compared to other international economies. is estimated to have contributed 4.2% of UK economic output (GVA) in 2016. The equivalent proportion in 2012 is It is also worthwhile to consider the diferential growth of the estimated to be 3.7%. The current size of the Data Economy Data Economy in terms of the UK regions. The table below has also been assessed in terms of the impact on business sets out the relevant data for 2012 and 2016. and organisation turnover and cost savings. It is estimated that the efect on business/organisation turnover and costs Whereas the increase in the size of the Data Economy for in 2016 was worth a total of £165 billion. The equivalent the UK as a whole over the past five years was 33% (i.e. figure for 2012 is estimated to be just under £123 billion, an average annual growth rate of 7.3% per annum), the which is an overall increase of about 35%. The sectoral and performance of individual UK regions has difered markedly, spatial breakdowns of this benefit for business is very similar with the East of England growing the strongest (37%) and to that for GVA set out in the tables preceding. Northern Ireland the slowest (19%). The increase in the number of Change Change Region 2012 2016 (£millions) (%) direct jobs associated with the North East 1, 356 1,818 463 34%
North West 4,401 5,736 1, 335 30% Data Economy over the 2012-
Yorkshire & 3,047 3,667 621 20% Humber 2016 period (sourced from the East Midlands 2 ,483 3, 235 751 30% ONS Labour Force Survey) West Midlands 3, 289 4, 268 979 30%
East of 4,095 5,600 1, 506 37% was 166,000. England
London 17, 527 23,664 6,138 35% This was equivalent to an increase of 16.9% over this period. South East 9, 507 12 ,634 3,128 33% Over the 2012-2016 period the proportion of workforce jobs South West 3,401 4, 542 1,140 34% attributable to the UK Data Economy is estimated to have Wales 1, 380 1,72 2 343 25% increased from 3.06% to 3.31%.
Scotland 3,439 4,607 1,169 34%
Northern 920 1,099 179 19% Ireland
Ex-regio 482 734 252 52%
Total 55, 284 73, 327 18,043 33%
DATA ECONOMY REPORT 2018 39
29 | The evidence comes from unpublished surveys of European manufacturers undertaken during 2015, 2016 and 2017 by Development Economics on behalf of Barclays Bank. Current size of Data Economy versus current potential
Estimates have also been produced of the current (2016) These estimates are presented in a table below, size of the UK Data Economy compared to the extent it disaggregated by business sector. The table shows current could have reached by this point if all constraints (both on levels of performance (in terms of GVA) and the proportion the demand side and the supply side) had been addressed. of overall potential value generation that this is estimated For example, if the awareness and preparedness of business to represent. to utilise data solutions and implement them to their full current potential were at optimum levels (i.e. match those of the best performing companies in their respective sectors) and if issues such as skills gaps and skills shortages were no longer a factor.
2016 2016 Full Potential GVA Actual GVA as % Sector (Sections) Actual GVA Full Potential GVA minus Actual GVA of Full Potential
A Agriculture, forestry, fishing 71 178 107 40%
B Mining & quarrying 881 1,603 72 2 55%
C Manufacturing 4,702 9, 219 4, 517 51%
D Electricity 1, 236 2 ,168 932 57%
E Water supply 315 584 269 54%
F Construction 1,653 3,756 2 ,103 44%
G Wholesale, retail 3,440 6,491 3,051 53%
H Transport 2 ,111 4, 398 2 , 287 48%
I Accommodation & food 100 2 28 128 44%
J ICT 30, 267 41,748 11,480 73%
K Financial services 11,605 20, 359 8,754 57%
L Real estate activities 3,670 7,646 3,976 48%
M Professional services 5,136 9,691 4, 555 53%
N Business support services 1,709 3,884 2 ,175 44%
O Public administration 2 , 329 4,658 2 , 329 50%
P Education 1,469 2 ,825 1, 356 52%
Q Health 1, 327 3,087 1,760 43%
R Arts, entertainment, recreation 702 1,633 931 43%
S Other services 602 1, 505 903 40%
Total 73,327 125,660 52,335 58%
40 DATA ECONOMY REPORT 2018 Overall, the UK economy market appeal of accommodation and food service providing businesses. is estimated to be currently .Skills gaps and shortages utilising only around 58% A more significant issue for many businesses is the dificulty of the full potential of data in recruiting or retaining workers with the skills needed to develop and maintain data analytical systems. At a national to boost revenues and level, the UK is already facing a severe digital skills shortage which has been acknowledged in the findings of Parliamentary productivity. committees and in reports produced by leading advisory agencies such as the UK Commission on Employment and Skills. However, some sectors, such as Agriculture, forestry & The UK was already expected to experience an annual digital fishing appear to perform significantly worse than the overall skills shortage of over 150,000 digital workers per annum UK average. up to 2020, and it is important to note that these forecasts pre-date the decision of the UK to leave the European The reasons why the UK economy operates well-within the Union. The decision to leave the EU is likely to afect the levels of possibility currently ofered by the full extent of the future ability of the UK to attract talent in the form of Data Economy relate to the following: mathematicians, statisticians, computer scientists and other expertise required to build and develop a Data Economy. .Under-investment by businesses Especially (but not exclusively) small and medium sized companies. This under-investment is linked in many cases to a failure to fully recognise the competitive advantages and cost eficiencies that stand to be gained through analysis of their operational and customer data. That is, a failure on the part of some businesses to appropriately prioritise investment in their data analytics capability (including infrastructure, technical skills and business expertise to grasp the opportunities fully). However, there is also 58% evidence that in some cases business have recognised the potential advantages and gains that stand to be realised, but they have struggled to make a successful case for financial resources to lenders so that their business plans can be implemented.
.Inadequate infrastructure In some cases, business development potential may be stymied by inadequate telecommunications infrastructure. For example, it is reported that the implementation of precision farming technologies (involving use of more precise applications of fertiliser, pesticides, fungicides and other inputs) is constrained in many areas due to poor levels of 4G mobile telecommunications (as these approaches rely on location mapping using GIS technologies). Poor telecommunications infrastructure can also restrict the
DATA ECONOMY REPORT 2018 41 Expected future size of the Data Economy
The future size of the UK Data Economy focusing on the period 2017-2025 has also been assessed. This has involved the production of annual breakdowns of the future value of the UK Data Economy across all regions and business sectors. However, for purposes of brevity we report here only regional and national sector totals for the final year of the forecasting period (2025).
Continuation of current trends scenario
Under the first scenario, current trends are expected to continue with no improvement to or worsening of existing constraints. The scenario is predicated on the expected underlying growth trends for each sector on a region-by- region basis, plus a continuation of the annual rates of penetration of Data Economy services in each region and sector as evident in the 2012-2016 data described earlier in this chapter.
The next table sets out the levels of GVA generated by the UK Data Economy attributable to each sector that are expected to be generated annually under this scenario by 2025. It should be noted that a 2016 price base is used, so that increases in the value of production are expressed in real terms (i.e. the efect of future inflation is excluded).
The conclusion of this assessment is that the UK Data Economy can be expected – on the basis of current trajectories – to be worth £94.6 billion per annum by 2025 (2016 prices). Apart from the ICT sector, the largest contributors to this growth, in absolute terms, are expected to be Financial services and Professional services.
42 DATA ECONOMY REPORT 2018 GVA GVA Increase in GVA Increase in GVA Sector (Sections) 2016 2025 (£millions) (%)
A Agriculture, forestry, fishing 71 74 3 5%
B Mining & quarrying 881 905 23 3%
C Manufacturing 4,702 5,468 767 16%
D Electricity 1, 236 1, 515 279 23%
E Water supply 315 371 56 18%
F Construction 1,653 1,97 7 325 20%
G Wholesale, retail 3,440 4, 236 796 23%
H Transport 2 ,111 2 ,462 351 17%
I Accommodation & food 100 124 24 24%
J ICT 30, 267 42 ,819 12 , 552 41%
K Financial services 11,605 13, 539 1,934 17%
L Real estate activities 3,670 4,627 956 26%
M Professional services 5,136 7,161 2 ,025 39%
N Business support services 1,709 2 , 298 589 34%
O Public administration 2 , 329 2 ,428 99 4%
P Education 1,469 1, 57 7 108 7%
Q Health 1, 327 1, 527 200 15%
R Arts, entertainment, recreation 702 830 128 18%
S Other services 602 663 61 10%
Total 73,327 94,602 21, 274 29%
Despite this growth, the UK Data Economy is by 2025 and capabilities lags significantly behind international still expected to be operating well within its potential full benchmarks. On this basis, there is significant evidence that capacity and capability. The main reasons why the economy the underlying trajectory of investment will continue to be is expected to continue to operate sub-optimally to a sub-optimal. significant extent include the following: .Skills deficits expected to continue to exert .Inadequate business investment an influence As of 2017 many businesses had not recognised the The UK has a widely acknowledged digital skills deficit competitive advantages of data analytics, and this situation that is not expected to lessen over the 2017-2025 period. is not expected to be completely remedied in the future Indeed, the potential efect of the decision to leave the EU either. Even in knowledge-driven sectors such as financial is expected by some to worsen the shortage as, despite services, around 30% of companies do not appear to Government assurances that a system to encourage skilled have accorded investment in data analytics the level of migration will be put in place, there is still a danger that the prioritisation that would appear to be appropriate. In sectors UK could be increasingly perceived to be an unwelcoming such as Manufacturing, the proportion of UK companies destination for skilled immigrants. that are prioritising investment in Industry 4.0 technologies
DATA ECONOMY REPORT 2018 43 The regional breakdown of the expected future size of the On the other hand, the data economies of the North East, UK Data Economy by 2025 has also been estimated. The Wales and Northern Ireland are expected to grow at a forecasts are set out in the table below, with the 2016 levels significantly slower rate than that expected for the UK also set out for ease of reference. as a whole. These are the regions which have the lowest proportion of knowledge-driven sectoral and business functional activity, and also the lowest proportion of skilled Increase GVA GVA Increase in Region in GVA Data Economy workers and the lowest birth rate for digital 2016 2025 GVA (%) (£millions) economy businesses. North East 1,818 2 , 235 417 23%
North West 5,736 7, 279 1, 543 27% Based on current rates of job growth, it is expected that Yorkshire & 3,667 4, 561 894 24% the total number of direct jobs attributable to the UK Data Humber Economy will increase from 1.147 million in 2016, to about 1.52 East Midlands 3, 235 4,078 843 26% million by 2025 (i.e. an overall increase of about 371,000). West Midlands 4, 268 5, 351 1,083 25% In addition, there is expected to be a further 668,000 jobs East of 5,600 7, 257 1,656 30% England supported throughout the rest of the UK economy via
London 23,664 31, 395 7,731 33% indirect (i.e. procurement) and induced (multiplier) efects.
South East 12 ,634 16,804 4,169 33% The overall level of employment attributable to the UK Data Economy by 2025 under the central case scenario is South West 4, 542 5,728 1,186 26% therefore expected to be 2.127 million. Wales 1,72 2 2 ,113 391 23%
Scotland 4,607 5,694 1,087 24%
Northern 1,099 1, 355 257 23% Ireland
Ex-regio 734 751 17 2%
Total 73, 327 94,602 21, 274 29%
The overall average increase expected is 29%, but some areas (notably London and the South East) are expected to grow their regional data economies at a faster rate than this. As previously noted, the principal reasons for the expected above-average performance of London and the other ‘greater South East’ regions are related to:
• Above average representation of knowledge economy sectors such as Financial services, Professional services, Life Science R&D, Media and Creative industries
• Above average representation of high-order corporate command and control functions across a range of business sectors (and also some public services)
• Above average rate of business formation in the ICT sector and specifically in the delivery of digital economy services
• Greater density of advanced communications infrastructure
• Above average densities of highly skilled workers.
44 DATA ECONOMY REPORT 2018 Alternative scenario 1: Constraints worsen
The first alternative scenario models a hypothetical situation in which existing constraints on the growth of the UK Data Economy (such as skills gaps and shortages, and/or a failure of potential business users to recognise the potential productivity and/or revenue growth opportunities ofered by more extensive and eficient use of data) become a greater hindrance to the growth of this segment of the economy than is expected to be the case under the central scenario. The diferential assumptions that are made under this scenario include the following:
.Absorption rates of data analytics and IoT The overall proportion of businesses developing capabilities or using data analytics services is assumed to be, on average, 7% per annum lower under this scenario compared to the current trends scenario. By 2025 the overall proportion of businesses using some form of Data Economy approach across the economy as a whole under this scenario is expected to reach only 69%, compared to 74% under the current trends scenario.
.Business capital investment Levels of annual aggregate business capital investment in data analytics infrastructure is assumed to be between 8% and 17% lower (varying by sector) compared to levels expected under the current trends scenario.
.Business human resource investment Average annual expenditure in training and development of staf is assumed to be between 6% and 11% lower (varying by sector) compared to levels expected under the current trends scenario.
.Skills shortages The average national deficit of skilled workers is assumed to be 15% worse than is the case under the current trends scenario.
The next table sets out the levels of GVA attributable to each sector that is expected to be generated annually under this lower growth scenario by 2025. A 2016 price base is used, so that increases in the value of production are expressed in real terms (i.e. the efect of future inflation is excluded).
DATA ECONOMY REPORT 2018 45 Reduction in GVA GVA GVA 2025 Change Change Reduction in GVA Sector (Sections) (£millions) cf Main 2016 Worsened Constraints 2016-2025 (£millions) 2016-2025 (%) (%) cf Main Case Case A Agriculture, forestry, 71 73 2 2.7% 1 1.8% fishing
B Mining & quarrying 881 892 11 1.2% 13 1.4%
C Manufacturing 4,702 4,943 242 5.1% 525 9.6%
D Electricity 1, 236 1, 383 147 11.9% 132 8.7%
E Water supply 315 345 30 9.4% 26 7.0%
F Construction 1,653 1,848 195 11.8% 130 6.6%
G Wholesale, retail 3,440 3,941 500 14.5% 296 7.0%
H Transport 2 ,111 2 , 316 205 9.7% 146 5.9%
I Accommodation & 100 113 13 12.6% 11 9.1% food
J ICT 30, 267 37,979 7,712 25.5% 4,840 11.3%
K Financial services 11,605 12 ,831 1, 2 27 10.6% 707 5.2%
L Real estate activities 3,670 4,172 501 13.7% 455 9.8%
M Professional services 5,136 6, 279 1,142 22.2% 882 12.3%
N Business support 1,709 2 ,014 305 17.8% 284 12.4% services
O Public administration 2 , 329 2 , 382 53 2.3% 46 1.9%
P Education 1,469 1, 527 58 4.0% 49 3.1%
Q Health 1, 327 1,434 107 8.0% 93 6.1%
R Arts, entertainment, 702 777 74 10.6% 54 6.4% recreation
S Other services 602 635 33 5.5% 28 4.2%
Total 73,327 85,883 12 , 556 17.1% 8,719 9.2%
Under this scenario the UK Data Economy is expected to Compared to the central case future scenario, the average grow from £73.3 billion in 2016 to about £85.9 billion by 2025. overall reduction across the UK is 9.2%, but Scotland (7.9%) The overall scale of reduction across the UK economy as a and North East England (7.8%) face slightly lower reductions. whole under this scenario would be expected to be just over The most significant erosion of potential growth under this £8.7 billion, which is a reduction of about 9% compared to scenario is expected to occur in the South East and London, the central case defined by the current expected trajectory both around 10%. of change. However, the impact across the diferent sectors of the economy is much more varied, with sectors such as Mining and Public Administration comparatively little afected, but with sectors such as Business support services and Professional services much more significantly constrained.
The regional breakdown of the expected future size of the UK Data Economy by 2025 under this more constrained hypothetical scenario has also been estimated, with results set out in the next table.
46 DATA ECONOMY REPORT 2018 GVA Change Change Reduction in GVA GVA Reduction in GVA Region 2025 2016-2025 2016-2025 (£millions) 2016 (%) cf Main Case Worsened Constraints (£millions) (%) cf Main Case
North East 1,818 2 ,062 243 13.4% 173 7.8%
North West 5,736 6,631 895 15.6% 648 8.9%
Yorkshire & Humber 3,667 4,182 515 14.0% 379 8.3%
East Midlands 3, 235 3,711 476 14.7% 367 9.0%
West Midlands 4, 268 4,890 62 2 14.6% 462 8.6%
East of England 5,600 6, 569 968 17.3% 688 9.5%
London 23,664 28, 313 4,649 19.6% 3,082 9.8%
South East 12 ,634 15,125 2 ,491 19.7% 1,678 10.0%
South West 4, 542 5, 230 688 15.2% 498 8.7%
Wales 1,72 2 1,943 2 21 12.8% 170 8.0%
Scotland 4,607 5, 242 635 13.8% 452 7.9%
Northern Ireland 1,099 1, 246 147 13.4% 109 8.1%
Ex-regio 734 740 6 0.8% 11 1.5%
Total 73, 327 85,883 12 , 556 17.1% 8,719 9.2%
Under this more pessimistic scenario, we expect the total In addition, under this scenario there is expected to be number of direct jobs attributable to the UK Data Economy a reduced figure of a further 650,000 jobs supported to increase from 1.147 million in 2016, to about 1.48 million throughout the rest of the UK economy via indirect (i.e. by 2025. This would represent a reduction in the overall procurement) and induced (multiplier) efects. increase in employment (compared to the predicted level The overall level of employment attributable to the UK Data under the central case) of just over 42,000 jobs; i.e. the Economy by 2025 under this scenario is therefore expected overall expected increase in jobs in this more scenario is to be 2.127 million. about 2.8% less than the gain expected under the central case scenario.
DATA ECONOMY REPORT 2018 47 Alternative scenario 2: Constraints relaxed
The second alternative scenario models a more optimistic situation, in which some constraints on the growth of the UK Data Economy are eased through policy initiatives (e.g. designed to address skills shortages and skills gaps) or through accelerated investment by businesses in Data Economy technology, or both.
The diferential assumptions that are made under this scenario include the following:
.Absorption rates of data analytics and IoT The overall proportion of businesses developing capabilities or using data analytics services is assumed to be, on average, 4% per annum higher under this scenario compared to the current trends scenario. By 2025 the overall proportion of businesses using some form of Data Economy approach is expected to reach 81% under this scenario, compared to 74% under the current trends scenario.
.Business capital investment Levels of annual aggregate business capital investment in data analytics infrastructure is assumed to be between 5% and 11% higher (varying by sector) compared to levels expected under the current trends scenario.
.Business human resource investment Average annual expenditure in training and development of staf is assumed to be between 4% and 9% higher (varying by sector) compared to levels expected under the current trends scenario.
.Skills shortages The average national deficit of skilled workers is assumed to be 10% lower than is the case under the current trends scenario.
48 DATA ECONOMY REPORT 2018 Increase in GVA GVA GVA 2025 Change Change Increase in GVA Sector (Sections) (£millions) 2016 Eased Constraints 2016-2025 (£millions) 2016-2025 (%) (%) cf Main Case cf Main Case
A Agriculture & forestry 71 75 4 5.7% 1 1.1%
B Mining & quarrying 881 915 34 3.9% 11 1.2%
C Manufacturing 4,702 5,925 1, 2 23 26.0% 456 8.3%
D Electricity 1, 236 1, 596 360 29.1% 81 5.4%
E Water supply 315 386 71 22.4% 15 4.0%
F Construction 1,653 2 ,078 425 25.7% 101 5.1%
G Wholesale, retail 3,440 4, 524 1,083 31.5% 287 6.8%
H Transport 2 ,111 2 , 561 450 21.3% 99 4.0%
I Accommodation & 100 130 30 30.1% 6 5.0% food
J ICT 30, 267 46,920 16,653 55.0% 4,101 9.6%
K Financial services 11,605 14, 216 2,611 22.5% 67 7 5.0%
L Real estate activities 3,670 4,876 1, 206 32.8% 249 5.4%
M Professional services 5,136 7,767 2 ,631 51.2% 606 8.5%
N Business support 1,709 2 ,457 748 43.8% 159 6.9%
O Public administration 2 , 329 2 ,452 123 5.3% 24 1.0%
P Education 1,469 1,603 134 9.1% 26 1.6%
Q Health 1, 327 1, 582 254 19.1% 54 3.5%
R Arts, entertainment, 702 867 165 23.4% 37 4.4% etc.
S Other services 602 67 7 75 12.5% 14 2.1%
Total 73,327 101,606 28, 279 38.6% 7,005 7.4%
The above table sets out the levels of GVA attributable to The regional breakdown of the expected future size of each sector that are expected to be generated annually the UK Data Economy by 2025 under the higher growth under this increased growth scenario by 2025. Once again, a scenario has also been estimated, with results set out in 2016 price base is used. the next table.
Under this more optimistic scenario, the UK Data Economy is expected to grow from £73.3 billion in 2016 to about £101.6 billion by 2025. The overall scale of increase in the Data Economy across the UK economy (compared to the central case) under this more scenario is expected to be just over £7.0 billion, representing an increase of around 7.4% compared to the central case. Sectors such as Professional Services and Manufacturing are expected under this more scenario to experience enhanced rates of growth compared to the central case scenario.
DATA ECONOMY REPORT 2018 49 Compared to the central case future scenario, the average overall increase in Data Economy GVA across the UK under the more optimistic scenario is 7.4%, but some regions – most notably London (8.1%) and South East England (8.1%) – would be expected to experience more pronounced increases in economic activity.
Under this more scenario we also expect the total number of direct jobs attributable to the UK Data Economy to increase from 1.147 million in 2016, to about 1.55 million by 2025. This would be a gain of just over 31,000 jobs (i.e. an overall increase of 2.1%) over the anticipated central case scenario outcome.
In addition, under this scenario there is expected to be a further 682,000 jobs supported throughout the rest of the UK economy via indirect (i.e. procurement) and induced (multiplier) efects.
The overall level of employment attributable to the UK Data Economy by 2025 under this more optimistic scenario is therefore expected to be 2.233 million.
Increase in GVA GVA GVA 2025 Change Change Increase in GVA Region (£millions) 2016 Eased Constraints 2016-2025 (£millions) 2016-2025 (%) (%) cf Main Case cf Main Case
North East 1,818 2 , 371 553 30.4% 136 6.1%
North West 5,736 7,794 2 ,058 35.9% 515 7.1%
Yorkshire & Humber 3,667 4,863 1,195 32.6% 302 6.6%
East Midlands 3, 235 4, 366 1,131 35.0% 288 7.1%
West Midlands 4, 268 5,716 1,448 33.9% 365 6.8%
East of England 5,600 7,802 2 , 202 39.3% 545 7.5%
London 23,664 33,913 10, 249 43.3% 2 , 518 8.0%
South East 12 ,634 18,164 5, 530 43.8% 1, 360 8.1%
South West 4, 542 6,119 1, 57 7 34.7% 391 6.8%
Wales 1,72 2 2 , 246 523 30.4% 133 6.3%
Scotland 4,607 6,050 1,443 31.3% 356 6.3%
Northern Ireland 1,099 1,442 343 31.2% 87 6.4%
Ex-regio 734 760 26 3.6% 9 1.2%
Total 73, 327 101,606 28, 279 38.6% 7,005 7.4%
50 DATA ECONOMY REPORT 2018 Conclusions The chapter has also looked at a range of future scenarios for the growth of the UK Data Economy. Under the currently The current scale of the contribution of the UK Data expected trajectory of growth, the value of the Data Economy is estimated to amount to some £73.3 billion per Economy is expected to reach nearly £95 billion (in real annum. The contribution has grown from around £55 billion terms) by 2025, which is growth of 30% compared to current in 2012 with a recent growth rate of over 7% per annum, well levels. However, this contribution could be significantly lower ahead of the annual growth rate for the economy as a whole. if skills deficits and other potential constraints (including the general business appetite for investment in Data Economy Already by 2016 the Data capabilities) turn out to be worse than currently expected. Economy accounted for over On the other hand, the performance by 2025 could be significantly raised if business investment in technology 4% of national economic and skills runs ahead of currently anticipated trends, and if output and over 3% of infrastructure constraints are addressed (for example, if the expected roll out of a national 5G network happens more national employment. quickly than expected under the current trends scenario).
The main sources of this contribution in sector terms are ICT services, Financial services and Professional services. Geographically, well over 50% of the UK Data Economy is in just three regions: London, the South East and the East of England. This is primarily because of the above-average representation of knowledge-economy activities and high- order corporate command and control functions located in those areas.
Despite the impressive growth of the Data Economy over the past five years, there is abundant evidence that the UK Data Economy is operating well-within its full potential. It is estimated that 42% of potential value remains unrealised. The main causes of the squandered potential for additional business turnover, economic output and growth of employment are considered to be: 4% • Underinvestment by businesses in Data Economy of national capabilities, influenced in part by a failure of some economic businesses to recognise the relevance and potential output of data analytics for their business, but also in some cases an inability to access business finance to allow the implementation of cogent business plans
• Infrastructure issues afecting some areas and sectors
• Skills deficits, in the form of unfilled vacancies for digitally skilled workers and also in some cases skills gaps on the part of workers with responsibilities for undertaking data analytics tasks for their employers.
DATA ECONOMY REPORT 2018 51 4 Ireland Data Economy Results
Introduction Current (2016) size of the Republic of Ireland Data Economy The focus of this chapter is the production of estimates of the current and potential future size of the Republic of Based on a similar modelling approach to that used for the Ireland’s Data Economy. As was the case with the previous UK, it is estimated that the Republic of Ireland (hereafter, chapter which focused on the UK, the most recent year for Ireland) Data Economy generated economic output which data for Ireland is available is 2016. Growth trends over (Gross Value Added) worth €9.96 billion in 2016. The the 2012-2016 period are also assessed in this chapter, and largest contributors to this total were provided by the ICT, future estimates are provided for the year 2025. Manufacturing and Financial services sectors, which together accounted for 80% of the total Irish Data Economy. All financial values reported in this chapter are provided in terms of millions of Euros using a 2016 price base. It should 2016 GVA be noted that because of the limitations imposed by the Sector (Sections) % of total €millions availability of data, the assessment in this chapter focuses on A Agriculture, forestry, the national economy only; i.e. there is no disaggregation by 14 0.1% fishing regions or other types of sub-national geography. B Mining & quarrying 41 0.4%
C Manufacturing 1,662 16.7%
D Electricity 82 0.8%
E Water supply 24 0.2%
F Construction 91 0.9%
G Wholesale, retail 239 2.4%
H Transport 120 1.2%
I Accommodation & food 14 0.1%
J ICT 4,956 49.7%
K Financial services 1, 349 13.5%
L Real estate activities 204 2.1%
M Professional services 564 5.7%
N Business support 178 1.8% services
O Public administration 148 1.5%
P Education 108 1.1%
Q Health 118 1.2%
R Arts, entertainment, 33 0.3% recreation
S Other services 18 0.2%
Total 9,962 100.0%
52 DATA ECONOMY REPORT 2018 The pattern of the contribution by sector is influenced by In addition to the direct jobs, the Data Economy also various factors: supports jobs via supply chain and multiplier efects. These indirect and induced efects are estimated to amount to an • The contribution of dominant sectors (such as additional 23,200 jobs across Ireland in 2016. Manufacturing and Financial services) is naturally larger than small sectors such as Utilities and Minerals The amount of total • Sectors with a higher level of knowledge-intensity (such as ICT and Financial services) have a greater propensity employment attributable to to invest in data analytics infrastructure and skills. the Data Economy in 2016 is At first glance the scale of the contribution of the estimated to amount to just Manufacturing sector in Ireland is perhaps surprising, but the contribution of the sector to the Irish economy is over 84,000 jobs. very significant: the sector accounts for nearly a quarter of national economic output. In addition, one of the most important sub-sectors is pharmaceuticals, which includes important players such as Pfizer and Shire. It was noted in chapter 1 of this report that life sciences (which falls within the Manufacturing category) is a key generator of commercial R&D and is increasingly reliant on data analytics.
On the other hand, the scale of the contribution of the Financial services sector is not surprising: over the past several decades Ireland has received significant levels of inward investment from international financial services companies.
The overall amount of GVA generated by the Irish economy in 2016 is estimated to be just over €247 million. On this basis, the Irish Data Economy accounted for approximately 4.0% of Irish economic output in 2016.
The total number of direct jobs associated with the Data Economy in 2016 (based on data sourced from Eurostat) was just over 61,000. By 2016, direct employment in the Data Economy was estimated to account for 3.05% of the overall number of jobs in the Irish economy.
DATA ECONOMY REPORT 2018 53 Growth trajectory since 2012 Irish business/organisation turnover and costs in 2016 is estimated to have been worth a total of €22.4 billion. Overall, the financial value (in terms of GVA) of the Irish Data The equivalent figure for 2012 is estimated to be around Economy is estimated to have grown from €6.07 billion in €13.3 billion (in terms of 2016 prices). This implies an overall 2012 to €9.96 billion in 2016. increase in value of about 68%. The sectoral breakdown of this increase is very similar to that for GVA set out in the This implies an average table below. annual increase of around The increase in the number of jobs associated with the Data Economy over the 2012-2016 period (using data sourced
13.2% over this period, which from Eurostat and the Central Statistics Ofice (CSO) of is nearly double the rate Ireland) is estimated to amount to approximately 18,500 jobs. This is an increase of around 43% compared to the estimated for the UK in the 2012 position. previous chapter. Over the 2012-2016 period the proportion of workforce jobs attributable to the Irish Data Economy is estimated to have Comparing the Irish estimates for 2012 to those for 2016, the increased from about 2.3% to just over 3.0%. most significant increases (in absolute terms) have occurred in ICT, Manufacturing, Financial services and Professional services. However, in proportionate terms above-average GVA 2012 GVA 2016 Change Change Sector (Sections) €millions €millions (€millions) (%) increases have occurred in a range of other sectors, including A Agriculture, forestry, 5 14 8 159% Construction, Business support services and Agriculture, fishing forestry & fishing. B Mining & quarrying 21 41 20 93%
One factor that may have influenced the growth trend since C Manufacturing 745 1,662 917 123% 2012 is the high level of importance to the Irish economy D Electricity 61 82 20 33% of international investment, especially from the United E Water supply 13 24 11 84% States. Over the past few decades Ireland has become F Construction 32 91 59 186% a major European business headquarters location for large numbers of multi-national corporations (including G Wholesale, retail 171 239 67 39% technology manufacturers) across a range of knowledge H Transport 81 120 39 48% economy sectors. For example, it is estimated that the level I Accommodation & food 7 14 7 100% of US foreign investment in Ireland exceeds that which has J ICT 3,021 4,956 1,935 64% flowed to the BRIC countries (Brazil, Russia, India and China) combined. It is also estimated that over 700 US companies K Financial services 1,020 1, 349 329 32% now have significant operations in Ireland. These companies L Real estate activities 139 204 65 47% include major knowledge-economy players such as Dell, M Professional services 285 564 279 98% Intel, Hewlett Packard, IBM, Pfizer, Google and Facebook. N Business support 89 178 89 100% Many of these companies will have located high-level services corporate command and control functions within their Irish O Public administration 135 148 12 9% operations. This is likely to have played a significant role P Education 98 108 10 10% in accelerating the level of investment of Data Economy Q Health 98 118 20 20% functions and activities within the Irish economy. R Arts, entertainment, 28 33 5 19% recreation The current size of the Irish Data Economy has also S Other services 14 18 4 25% been assessed in terms of the impact on business and Total 6,065 9,962 3,897 64% organisation turnover and cost savings. The efect on
54 DATA ECONOMY REPORT 2018 Current size of Data Economy versus current potential
Estimates of the current (2016) size of the Irish Data The principal factors that hinder full exploitation of the Economy have also been compared to the extent it could Data Economy in Ireland are similar to the ones that were have reached by this point if all constraints (both on the discussed regarding the UK economy in the previous demand side and the supply side) were not operating. chapter. These are: These estimates are presented in the next table, • Under-investment by businesses, in particular SMEs: disaggregated by business sector. The table shows current this may because some businesses do not fully grasp levels of performance (in terms of GVA) and the proportion the growing importance of data analytics to the future of overall potential value generation that this is estimated competitiveness of their business but, in some cases, to represent. companies may understand its importance yet lack the expertise or financial resources to realise the The estimates suggest that whereas, in 2016, the Irish Data opportunity Economy was worth around €9.96 billion, the full potential value that could have been generated that year was just over • Skills gaps and shortages: a significant issue for many €19.14 billion. businesses is the recruitment and/or retention of workers with the skills needed to develop and maintain data analytical systems. Therefore, in 2016 the Irish Data Economy was estimated to be currently worth about
52% of its full potential in terms of contributions to 52% revenue generation and productivity.
However, some sectors, such as Health and Business support services perform significantly worse than the overall Ireland average whereas sectors such as Financial services appear to be achieving a greater-than-average proportion of the existing potential (albeit with plenty of scope for improvement remaining).
DATA ECONOMY REPORT 2018 55 Full Poten- An additional factor that is very likely to be relevant are the 2016Full 2016 tial GVA Actual GVA Potential policies of the Irish Government towards Open Data. Sector (Sections) Actual GVA minus Actu- as % of Full GVA €millions al GVA Potential €millions €millions A Agriculture, forestry, 14 36 22 38% fishing It is notable that the global B Mining & quarrying 41 78 37 53% Open Data Barometer accords C Manufacturing 1,662 3,422 1,760 49% Ireland a much lower ranking D Electricity 82 151 69 54%
E Water supply 24 47 23 51% (27th) compared to the UK F Construction 91 217 126 42% (1st). The ranking is also lower G Wholesale, retail 239 473 234 51% than the other countries H Transport 120 262 142 46%
I Accommodation & food 14 33 19 43% considered in this report:
J ICT 4,956 8,971 4,015 55% the Netherlands (7th) and K Financial services 1, 349 2,485 1,136 54% Germany (11th). L Real estate activities 204 447 243 46%
M Professional services 564 1,118 554 50% The relative lack of openness of data in Ireland may be hindering the development of public sector eficiency N Business support 178 426 248 42% services (as well as accountability) and may also be limiting the O Public administration 148 310 162 48% development of commercial opportunities and eficiencies
P Education 108 218 110 50% derived from the analysis of this data.
Q Health 118 288 170 41%
R Arts, entertainment, 33 81 48 41% recreation
S Other services 18 46 28 39%
Total 9,962 19,108 9,146 52%
56 DATA ECONOMY REPORT 2018 Expected future size of the Data Economy GVA GVA Increase Increase in Sector (Sections) 2016 2025 in GVA GVA (%) €millions €millions (€millions) Estimates for the potential future size of the Data Economy A Agriculture, forestry, 14 17 4 27% of Ireland have been developed for the period 2017-2025. fishing
This has involved the production of annual breakdowns of B Mining & quarrying 41 49 9 22% the future value of the Irish Data Economy for all business C Manufacturing 1,662 2 ,045 383 23% sectors. However, for purposes of brevity the estimates produced for the final year of the forecasting period (2025) D Electricity 82 112 30 37% only are reported here. E Water supply 24 33 9 38%
F Construction 91 128 37 41% In short, three alternative scenarios have been assessed: G Wholesale, retail 239 340 102 43%
.01 H Transport 120 159 39 32% A continuation of current trends (i.e. the current trajectories I Accommodation & food 14 19 6 42% of change are maintained) J ICT 4,956 7,023 2 ,068 42%
.02 K Financial services 1, 349 1,826 47 7 35% A more pessimistic scenario, using the same set of macro- L Real estate activities 204 288 83 41% economic trend assumptions as for the first scenario, but M Professional services 564 909 345 61% whereby current constraints on the operation of the Data N Business support 178 288 110 61% Economy (such as skills gaps and shortages) are assumed to services become more of a hindrance to growth in future O Public administration 148 154 6 4%
.03 P Education 108 133 25 23% A more optimistic scenario, whereby current constraints and Q Health 118 156 38 33% R Arts, entertainment, restrictions on the future growth of the Data Economy are 33 45 12 36% recreation assumed to be eased (but not removed entirely). S Other services 18 23 5 28%
Continuation of current trends scenario Total 9,962 13,749 3,787 38%
Under the first scenario, current macro-economic and Data Under this scenario the Irish Data Economy is expected to Economy growth trends afecting Ireland are expected to grow in real terms from €9.96 billion in 2016 to around €13.75 continue with no improvement to or worsening of existing billion by 2025. This is an increase of about €3.79 billion, or constraints. The scenario is predicated on the expected 38% in proportionate terms. underlying growth trends for each sector on a sector-by- sector basis.
The right hand table sets out the levels of GVA generated by the Data Economy in Ireland under this scenario by 2025 disaggregated by sector. It should be noted that a 2016 price base is used, so that increases in the value of production are expressed in real terms (i.e. the efect of future inflation is excluded).
DATA ECONOMY REPORT 2018 57 Despite this increase, the Irish Data Economy is still expected In addition to the direct jobs, it is expected that a further to be operating well within its potential full capacity and 27,000 jobs are supported via indirect (procurement) and capability over this future period. The principal reasons why induced (multiplier) efects. the Irish Data Economy is expected to continue to operate sub-optimally in this future period are: The overall number of attributable jobs expected under this central case scenario by 2025 is therefore 99,500. .Under-investment by businesses and data- generating organisations Alternative scenario 1: Constraints worsen Significant numbers of businesses are expected to under- value the business competitiveness implications of data The first alternative scenario models a more pessimistic analytics. However, even where businesses do have a high potential situation, in which existing constraints on the level of awareness, it is anticipated that large numbers of growth of the Irish Data Economy (such as the business businesses (especially SMEs) will either lack the managerial appetite, or ability, to invest) become an even greater expertise to develop an appropriate strategy or, where hindrance to the growth of this segment of the economy the need for such strategies is recognised, in some cases than is expected to be the case under the central scenario. businesses (especially SMEs) will be unable to accumulate suficient financial and/or technical resources to implement The specific assumptions that are made under this scenario an appropriate strategy successfully. include the following:
.Skills shortages and skills gaps .Absorption rates of data analytics and IoT Skills deficits are expected to continue to exert a significant The overall proportion of businesses developing capabilities negative influence on the ability of Irish companies and or using data analytics services is assumed to be, on average, organisations to make full use of their data. 5% per annum lower under this scenario compared to the current trends scenario. .The relative reluctance of the Irish Government to embrace and implement Open Data policies .Business capital investment Although this situation is expected to improve (the 2016 Levels of annual aggregate business capital investment ranking was an increase over the previous year’s ranking, in data analytics infrastructure is assumed to be between by four places) under the current trends scenario Ireland is 6% and 13% lower (varying by sector) compared to levels not expected to become a top ten performer with respect to expected under the current trends scenario. openness of data. .Business human resource investment Notwithstanding the expected influence of these constraints, Average annual expenditure in training and development of the contribution of the Data Economy to some sectors is staf is assumed to be between 5% and 10% lower (varying expected to be significantly greater than the overall average, by sector) compared to levels expected under the current with Business support services, Professional services and trends scenario. Wholesale & retail trade expected to experience the greatest increases in GVA. .Skills shortages The average national deficit of skilled workers is assumed to Under this ‘maintained trajectory of change’ scenario, it is be 12% worse than is the case under the current anticipated that the total number of direct jobs attributable trends scenario. to the Irish Data Economy will increase from 61,100 in 2016, to around 72,000 by 2025 (i.e. an overall increase of about .Open Data 11,000, which is equivalent to an 18% increase). The recent improvement in the relative ranking of Ireland in terms of Open Data is assumed to stall.
58 DATA ECONOMY REPORT 2018 The below table sets out the levels of GVA attributable to Economy would be expected to be around 10% smaller each sector that are expected to be generated annually (compared to the current trends scenario) under this more under this this lower growth scenario by 2025. A 2016 price pessimistic scenario in which constraints such as skills base is used, so that increases in the value of production are shortages and skills gaps exert a greater influence on the expressed in real terms (i.e. the efect of future inflation future growth trajectory of the Data Economy sector. is excluded). In industrial terms, the sectors that are comparatively most Under this more pessimistic scenario – in which constraints likely to be adversely afected (compared to the situation on future growth are exacerbated – the Irish Data Economy expected under the central case scenario) are Business is still expected to grow significantly, from €9.96 billion in support services and Professional services. 2016 to just under €12.4 billion by 2025. Under this more pessimistic scenario, it is expected that However, compared to the central case the scale of overall the total number of direct jobs attributable to the Irish Data growth is expected to be lower under this scenario. The Economy will increase from just over 61,000 in 2016, to about overall scale of reduction across the Irish economy as a 67,000 by 2025. This represents an increase over 2016 levels whole under this scenario is expected to be around €1.35 of about 5,800 jobs (9.4%). billion. Expressed another way, the size of the Irish Data
Decrease in GVA cf Decrease in GVA cf GVA 2016 GVA 2025 Change 2016-2025 Change 2016-2025 Sector (Sections) Main case Main case €millions €millions (€millions) (%) (€millions) (%)
A Agriculture & forestry 14 16 -1 -7.9% 2 17%
B Mining & quarrying 41 46 -3 -6.6% 6 14%
C Manufacturing 1,662 1,883 -162 -7.9% 2 21 13%
D Electricity 82 99 -13 -11.7% 17 21%
E Water supply 24 29 -4 -12.0% 5 22%
F Construction 91 115 -14 -10.6% 24 26%
G Wholesale, retail 239 306 -34 -10.0% 68 28%
H Transport 120 144 -15 -9.3% 24 20%
I Accommodation & 14 17 -3 -12.9% 3 23% food
J ICT 4,956 6, 335 - 689 -9.8% 1, 379 28%
K Financial services 1, 349 1,669 -157 -8.6% 320 24%
L Real estate activities 204 251 -36 -12.6% 47 23%
M Professional services 564 7 72 -138 -15.1% 207 37%
N Business support 178 238 -49 -17.2% 60 34%
O Public administration 148 151 -2 -1.5% 3 2%
P Education 108 123 -11 -8.0% 15 14%
Q Health 118 140 -17 -10.6% 2 2 19%
R Arts, entertainment, 33 41 -4 -8.7% 8 24% etc.
S Other services 18 20 -2 -9.3% 3 16%
Total 9,962 12 , 396 -1, 353 -9.8% 2 ,435 24%
DATA ECONOMY REPORT 2018 59 However, compared to the central case scenario, this predicted outcome represents a reduction in the overall increment in employment (compared to the predicted level under the central case) of just over 5,000 jobs (i.e. the overall expected increase in jobs under this more pessimistic scenario is about 8% less than the gain expected under the central case scenario). In addition to the direct jobs, it is anticipated that there would be a further 25,400 jobs supported via indirect (procurement) and induced (multiplier) efects. The overall number of attributable jobs expected under this scenario by 2025 is therefore 92,300.
Alternative scenario 2: Constraints relaxed
The second alternative scenario models a more optimistic situation, in which some of the existing constraints on the growth of the Irish Data Economy are eased through policy initiatives (e.g. designed to address skills shortages and skills gaps) or through accelerated investment by businesses in Data Economy capabilities, or both.
The diferential assumptions that are made under this scenario include the following:
.Absorption rates of data analytics and IoT The overall proportion of businesses developing capabilities or using data analytics services is assumed to be, on average, 5% per annum higher under this scenario compared to the current trends scenario.
.Business capital investment Levels of annual aggregate business capital investment in data analytics infrastructure is assumed to be between 6% and 13% higher (varying by sector) compared to levels expected under the current trends scenario.
.Business human resource investment Average annual expenditure in training and development of staf is assumed to be between 5% and 9% higher (varying by sector) compared to levels expected under the current trends scenario.
.Skills shortages the average national deficit of skilled workers is assumed to be 8% lower than is the case under the current trends scenario.
60 DATA ECONOMY REPORT 2018 The table below sets out the levels of GVA attributable to services, Financial services and Wholesale & retail each sector that are expected to be generated annually trade sectors. under this increased growth scenario by 2025. Again, a 2016 price base is used. Under this more optimistic scenario, it is expected that the total number of direct jobs attributable to the Irish Under this more optimistic scenario, the Irish Data Economy Data Economy will increase from 61,100 in 2016, to about is expected to grow from €9.96 billion in 2016 to about 75,900 by 2025, which would represent a gain of just under €14.87 billion by 2025, equivalent to a 49% increase. The 14,800 jobs compared to 2016 levels. This level of outcome overall scale of increase in the Data Economy across the Irish represents additional growth in employment of around 3,800 Data Economy as a whole (compared to the central case) compared to the central case scenario, which is an additional under this scenario is expected to be just over €4.9 billion, job growth uplift of around 5.3%. representing an increase of around 8% compared to the central case. In addition to the direct jobs, it is expected that a further 28,800 jobs would be supported via indirect (procurement) The largest proportionate increases (on a sector-by-sector and induced (multiplier) efects. The overall number of basis) under this optimistic scenario (compared to the attributable jobs expected under this scenario by 2025 is central case) are expected to occur in the Professional therefore 104,800.
Increase in GVA GVA GVA 2025 Change Change Increase in GVA (%) cf Sector (Sections) (€millions) 2016 Eased Constraints 2016-2025 (€millions) 2016-2025 (%) Main Case cf Main Case
A Agriculture & forestry 14 19 1 7.2% 5 36%
B Mining & quarrying 41 52 3 6.0% 12 29%
C Manufacturing 1,662 2 ,152 107 5.2% 490 29%
D Electricity 82 123 11 9.6% 41 50%
E Water supply 24 37 3 10.0% 13 52%
F Construction 91 143 15 11.4% 52 57%
G Wholesale, retail 239 384 44 12.9% 145 61%
H Transport 120 172 14 8.6% 52 44%
I Accommodation & 14 21 2 9.6% 8 55% food
J ICT 4,956 7, 519 495 7.1% 2 , 563 52%
K Financial services 1, 349 2 ,025 199 10.9% 676 50%
L Real estate activities 204 315 27 9.4% 110 54%
M Professional services 564 1,040 130 14.3% 475 84%
N Business support 178 325 37 12.8% 146 82%
O Public administration 148 155 1 1.0% 7 5%
P Education 108 141 8 5.8% 33 31%
Q Health 118 169 13 8.0% 51 43%
R Arts, entertainment, 33 49 4 9.1% 16 48% etc.
S Other services 18 24 1 6.2% 6 36%
Total 9,962 14,865 1,115 8.1% 4,903 49%
DATA ECONOMY REPORT 2018 61 Conclusions
The current scale of the contribution of the Irish Data The chapter has also looked at a range of future scenarios Economy is estimated to amount to nearly €10 billion per for the growth of the Irish Data Economy. Under the annum. The contribution has grown from just over €6 billion currently expected trajectory of growth, the value of Data in 2012. Economy is expected to reach nearly €14 billion (in real terms) by 2025, which would be growth of around 40% compared to current levels. However, this contribution could The recent growth be significantly lower if skills deficits and other potential trajectory is therefore constraints (including a stalling of a recent improvement in the Irish Open Data ranking) turn out to be worse than over 13% per annum. currently envisaged.
This is well ahead of the annual growth rate for the Irish On the other hand, the performance by 2025 could be economy as a whole, and it is about double the growth rate significantly raised if business investment in technology experienced by the UK economy over the same period. and skills runs ahead of currently anticipated trends, and if the Irish Government accelerates its progress towards By 2016 the Data Economy accounts for over 4% of implementing Open Data policies. Irish national economic output and over 3% of national employment. Nevertheless, the Irish Data Economy continues to operate well-within its full potential. It is estimated that nearly 50% of potential value remained unrealised in 2016.
The main causes of the lost potential for additional business turnover, economic output and growth of employment from the analysis of data are:
• Underinvestment by business in Data Economy capabilities
• National skills deficits, in the form of unfilled vacancies for digitally skilled workers and skills gaps on the part of currently employed workers
• A relative slowness of the Irish Government to embrace and implement Open Data policies in comparison with many European and other advanced economies.
62 DATA ECONOMY REPORT 2018 5 Germany Data Economy Results
Introduction 2016 GVA Sector (Sections) % of total €millions The focus of this chapter is the production of estimates of A Agriculture, forestry, 128 0.1% the current and potential future size of the Data Economy of fishing
Germany and its 16 regions. As is the case with the assessment B Mining & quarrying 560 0.5% of the other European countries, the focus is on assessing the C Manufacturing 21,155 19.5% current contribution for the year 2016 and the trajectory of change over the 2012-2016 period. D Electricity 1,939 1.8%
E Water supply 564 0.5% As was the case for the UK, the assessment also provides a F Construction 2 , 285 2.1% regional breakdown of estimated Date Economy economic output using GVA calculations. G Wholesale, retail 5, 259 4.9%
H Transport 2 , 576 2.4% The financial value of the Data Economy of Germany is I Accommodation & food 142 0.1% expressed in terms of millions of Euros using a 2016 price base. J ICT 37, 536 34.7% K Financial services 10, 516 9.7%
Current (2016) size of the German Data Economy L Real estate activities 5,162 4.8%
M Professional services 6, 591 6.1% It is estimated that the German Data Economy generated GVA N Business support 3,098 2.9% worth just over €108 billion in 2016. The largest contributors to services this total were provided by the ICT, Manufacturing and Financial O Public administration 4,120 3.8% services sectors, which together accounted for 63.9% of the total P Education 1,955 1.8% German Data Economy. The contribution of the Manufacturing sector (19.5%) is especially notable and reflects (in part) the Q Health 2 , 570 2.4% R Arts, entertainment, great importance of this sector to the German economy. 986 0.9% recreation
S Other services 1,183 1.1% There is evidence (based on a number of business surveys) that the level of absorption of advanced production Total 108,327 100% technologies in sectors such as Manufacturing and Transport are generally higher in Germany compared to most other European countries, especially the UK and Italy. For example, the total population of advanced robots operating in Germany is estimated to be about 10 times greater than the number of robots operating in the UK.30 Investment in advanced robotics can be taken as a proxy for investment in Industry 4.0 technologies generally (a term, incidentally, which is believed to have originated in Germany), which in terms of the production economy (i.e. the non-service sector part of the economy) is also linked to the emergence of the Data Economy.
DATA ECONOMY REPORT 2018 63
30 | International Federation of Robotics, 2017. Such investment has helped to raise the level of Manufacturing productivity (and productivity in other production sectors) to levels that are significantly higher than European averages.
The overall amount of GVA generated by the German economy in 2016 is estimated to be just over €2.82 trillion. Given that the size of the Data Economy is currently estimated to be €108 billion, the implication is that the Data Economy accounted for approximately 3.8% of German national economic output in 2016.
The German Data Economy can also be disaggregated across its 16 standard regions, and this data is set out in the table below.
The three largest 2016 GVA €million Region % of total German regions – (2016 prices) Baden- 16,483 15.2% Nordrhein-Westfalen, Württemberg Bayern 19,463 18.0% Baden-Württemberg Berlin 6,114 5.6% and Bayern – together Brandenburg 2,829 2.6% account for just over 53% Bremen 760 0.7% of the German national Hamburg 3,011 2.8%
Data Economy. Hessen 8,906 8.2%
Mecklenburg- 1,441 1.3% Vorpommern
Niedersachsen 8,759 8.1%
Nordrhein-Westfalen 22,053 20.4%
Rheinland-Pfalz 5,084 4.7%
Saarland 1,114 1.0%
Sachsen 4,619 4.3%
Sachsen-Anhalt 2,056 1.9%
Schleswig-Holstein 3,342 3.1%
Thüringen 2,293 2.1%
Total 108,327 100.0%
64 DATA ECONOMY REPORT 2018 The distribution of the German Data Economy across the 16 In addition to these direct jobs, the Data Economy also regions is influenced by a number of factors: supports jobs via supply chain and multiplier efects. These indirect and induced efects are estimated to amount to an • The relative scale of the underlying economy in each additional 629,000 jobs across the German economy in 2016. region. For example, the economies of Bavaria (Bayern) and Nordrhein-Westfalen are considerably larger than those of city-regions such as Bremen or smaller regions Therefore, in total, the amount such as Saarland of employment attributable to • The distribution of economic activity by sector is unevenly spread. One diferentiator is that between the German Data Economy in the city-region economies such as Berlin, Bremen and 2016 is estimated to amount Hamburg compared to regions with a mixture of major cities and rural hinterland (such as Bayern) or smaller to just over 1.952 million jobs. cities with a large rural hinterland (such as Schleswig-Holstein)
• There is also a distinction to be made with the regions of the former DDR (East Germany) which are still in the process of post-reunification restructuring and regeneration. Metrics of economic development (such as GDP per capita) indicate that regions such as Brandenburg, Thüringen, Sachsen and Sachsen- Anhalt are still lagging significantly behind German national averages. For example, GDP per capita levels in Brandenburg are around 38% lower than equivalent levels in Bayern.
The total number of direct jobs associated with the German Data Economy in 2016 (based on data sourced from Eurostat) was approximately 1.32 million. Employment in the Data Economy in Germany is estimated to account for 3.24% of the overall number of jobs in the economy as a whole in 2016. 1.952 million jobs
DATA ECONOMY REPORT 2018 65 Growth trajectory since 2012
Overall, the financial value (in terms of GVA) of the German The German growth rate therefore exceeds that achieved Data Economy is estimated to have grown from just over by the UK but is lower than that estimated for Ireland. €74.7 billion in 2012 to just over €108.3 billion in 2016. Comparing the sector-level estimates for 2012 to those for 2016, the most significant increases (in absolute terms) have This is an overall increase occurred in ICT, Manufacturing, Professional services and of 51%, and implies an average Wholesale & retail trade. annual increase of 10.9% in However, significant increases (more than 100%) have the size of the German Data occurred in sectors including Agriculture, forestry & fishing, Mining & quarrying, Water supply and Construction. Economy over this period.
GVA 2012 GVA 2016 Change Change Sector (Sections) €millions €millions (€millions) (%)
A Agriculture, forestry, fishing 60 128 68 113%
B Mining & quarrying 212 560 348 164%
C Manufacturing 14,975 21,155 6,180 41%
D Electricity 1, 517 1,939 422 28%
E Water supply 2 28 564 336 147%
F Construction 1,044 2 , 285 1,241 119%
G Wholesale, retail 2 ,905 5, 259 2,354 81%
H Transport 1,437 2 , 576 1,139 79%
I Accommodation & food 73 142 69 95%
J ICT 25,025 37, 536 12,511 50%
K Financial services 7,731 10, 516 2,785 36%
L Real estate activities 3,400 5,162 1,762 52%
M Professional services 3,999 6,591 2,592 65%
N Business support services 2 ,048 3,098 1,050 51%
O Public administration 2 ,954 4,120 1,166 39%
P Education 1, 298 1,955 657 51%
Q Health 1, 526 2 , 570 1,044 68%
R Arts, entertainment, recreation 647 986 339 52%
S Other services 661 1,183 522 79%
Total 71,741 108,327 36,586 51%
66 DATA ECONOMY REPORT 2018 The distribution of overall Data Economy growth by sector A regional disaggregation of growth over the 2012-2016 reflects several trends: period can also be estimated for Germany. This analysis – set out in the table below – reveals that although the largest • The underlying growth rates of some sectors (such as shares of the growth of the Data Economy (in absolute Professional services and Business services) is above terms) is occurring in the large regions (such as Baden- the average rate for the economy as a whole; such Württemberg and Nordrhein-Westfalen), the fastest growth sectors can naturally be expected to have grown the in the German Data Economy is occurring in city-regions Data Economy component of their output faster than such as Berlin, Bremen and Hamburg the economy-wide average It is also notable that while Nordrhein-Westfalen still • The absorption rate of Data Economy technologies and accounts for the largest single share of the German Data the recruitment of Data Economy workers is generally Economy, between 2012 and 2016 this region had a below- faster in knowledge-driven sectors such as advanced average level of growth in this segment of the economy. manufacturing and ICT.
2012 GVA 2016 GVA Change Change Region (€millions) (€millions) (€millions) (%)
Baden-Württemberg 10,398 16,483 6,085 59%
Bayern 12,780 19,463 6,683 52%
Berlin 3,731 6,114 2,383 64%
Brandenburg 1,918 2,829 911 47%
Bremen 452 760 308 68%
Hamburg 1,865 3,011 1,146 61%
Hessen 5,992 8,906 2,914 49%
Mecklenburg- 1,020 1,441 421 41% Vorpommern
Niedersachsen 5,772 8,759 2,987 52%
Nordrhein-Westfalen 15,081 22,053 6,972 46%
Rheinland-Pfalz 3,410 5,084 1,674 49%
Saarland 751 1,114 363 48%
Sachsen 3,190 4,619 1,429 45%
Sachsen-Anhalt 1,422 2,056 634 45%
Schleswig-Holstein 2,361 3,342 981 42%
Thüringen 1,597 2,293 696 44%
Total 71,741 108,327 36,586 51%
DATA ECONOMY REPORT 2018 67 The trend towards faster growth in the German city-regions over €262 billion in total. The equivalent figure for 2012 is highlights that the Data Economy may be largely (but not estimated to be worth approximately €183 billion (in terms exclusively) an urban phenomenon. Factors that are likely of 2016 prices). This implies an overall increase in value of to be encouraging the growth the of Data Economy in more about 43%. The sectoral breakdown of this increase is very urbanised areas of advanced economies such as Germany similar to that for GVA set out in the preceding table. include the following:
• Major customers for the ICT sector itself come from The number of jobs estimated other knowledge-driven sectors such as Financial to be associated with the services, Professional services, Media and creative industries, as well as often hosting the major German Data Economy is headquarters functions of companies (across all sectors) and Government, all of which tend to be estimated to have increased located in cities from about 1.132 million in • Linked to the previous point, cities also tend to possess the largest density of knowledge economy businesses 2012 to 1.323 million jobs by and workers compared to their host countries as 2016, based on data sourced a whole
• The most advanced networks of telecommunications from Eurostat. and other necessary infrastructure is found in cities Therefore, the increase in the number of jobs associated • Major universities are often located in cities, providing with the German Data Economy over the 2012-2016 period is businesses with a source of highly skilled graduate and estimated to be around 191,000 (17%). post-graduate workers.
Over the 2012-2016 period the proportion of workforce jobs All of the above are factors in the observed tendency for attributable to the German Data Economy is estimated to knowledge-intensive activities to increasingly aggregate have increased from about 2.91% to 3.24%. as clusters in major cities such as London, Berlin, Munich, Amsterdam, London and Dublin. In Germany, it is apparent that cities such as Hamburg and Bremen are also enjoying growth.
Clusters are widely acknowledged to be particularly important to knowledge-intensive and high value business activities, such as ICT, telecoms, advertising and the financial sector. These are all industries driven by innovation and the constant creation of new services, products and applications and as a result, as has already been discussed, are sectors driving the growth of the Data Economy.
The recent trend (2012-2016) in the growth of the German Data Economy in terms of the impact on business and organisation turnover and cost savings has also been assessed. The estimated efect on German business/ organisation turnover and costs in 2016 was worth just
68 DATA ECONOMY REPORT 2018 Current size of Data Economy versus current potential
Estimates of the current (2016) size of the German Data Economy compared to the extent it could have reached by this point if all constraints (both on the demand side and the supply side) were addressed have also been produced.
The main types of constraints that are pertinent in Germany are as follows:
.Under-investment by businesses Although in general German businesses appear to have an above-average appetite for investment in new technology, clearly this is not true for all businesses. One of the notable features of the German economy is the relative strength and importance of medium sized companies (the so-called Mittelstand) across a range of sectors, many of whom are family-owned. Many of these companies are also active in exporting. However, there are some concerns that some medium sized companies that are competing internationally may find it more dificult to identify and implement data analytics strategies compared to larger competitors both domestically and internationally.
.Skills gaps and shortages A significant issue for many German businesses is dificulty recruiting or retaining workers with the skills needed to develop and maintain data analytical systems.
.Open data There is some evidence that the relative German ranking for openness of data is falling. Based on the update of the most recent global Open Data Barometer, Germany is no longer a top ten country for Open Data (it is now ranked 11th).
DATA ECONOMY REPORT 2018 69 The estimates for the extent of the achievement of Data Moreover, sectors such as Health and Arts, entertainment Economy actualisation are presented in the table below, & recreation are operating at a level that is significantly disaggregated by business sector. The table shows current lower (in terms of unfulfilled potential) than the economy- levels of performance (in terms of GVA) and the proportion wide average. On the other hand, sectors such as Mining of overall potential value generation that this is estimated & quarrying and Manufacturing appear to be achieving a to represent. greater-than-average proportion of their existing potential.
The estimates suggest that whereas, in 2016, the German Data Economy was worth around €108 billion, the full potential value that could have been generated that year was approximately €196 billion. Therefore, in 2016 the actual German Data Economy was only operating at around 55% of its full potential in terms of contributions to revenue generation and productivity.
Full Potential GVA minus 2016 Actual GVA 2016 Full Potential GVA Actual GVA as % Sector (Sections) Actual GVA €millions €millions of Full Potential €millions
A Agriculture, forestry, fishing 128 287 160 44%
B Mining & quarrying 560 917 357 61%
C Manufacturing 21,155 33,185 12,029 64%
D Electricity 1,939 3,402 1,463 57%
E Water supply 564 1,044 480 54%
F Construction 2 , 285 5,194 2,909 44%
G Wholesale, retail 5, 259 9,923 4,664 53%
H Transport 2 , 576 5,368 2,791 48%
I Accommodation & food 142 323 181 44%
J ICT 37, 536 64,718 27,181 58%
K Financial services 10, 516 18,448 7,933 57%
L Real estate activities 5,162 10,754 5,592 48%
M Professional services 6,591 12,437 5,845 53%
N Business support services 3,098 7,041 3,943 44%
O Public administration 4,120 8,241 4,120 50%
P Education 1,955 3,759 1,804 52%
Q Health 2 , 570 5,978 3,407 43%
R Arts, entertainment, recreation 986 2,292 1,307 43%
S Other services 1,183 2,959 1,775 40%
Total 108,327 196,269 87,942 55%
70 DATA ECONOMY REPORT 2018 Conclusions
The current scale of the contribution of the German Data Economy is estimated to amount to just over €108 billion per annum. The contribution has grown from around €71 billion in 2012. The recent growth trajectory is therefore nearly 11% per annum. This is well ahead of the annual growth rate for the German economy as a whole, and it is also significantly faster than the most recent growth rate for the UK economy over the same time period.
Despite this impressive rate of growth, the German Data Economy continues to operate well-within its full potential. It is estimated that nearly 45% of available value-adding potential remained unrealised during 2016.
The main causes of the lost potential for additional business turnover, economic output and growth of employment from the analysis of data are:
• Inadequate investment by many businesses – particularly SMEs – in developing and grasping the potential value to be created through the analysis of their operational, market and other data
• Skills deficits, in the form of an inability to fill vacancies for digitally skilled workers in good time, along with underdeveloped technical and/or managerial skills on the part of some currently employees
• The continued relative under-development of some regions of the German economy, notably the areas (other than Berlin) that were formerly part of the DDR prior to reunification
• A slight but growing concern that Germany is starting to fall behind some other European and international countries in terms of Open Data policies.
DATA ECONOMY REPORT 2018 71 6 Netherlands Data Economy Results
Introduction 2016 GVA Sector (Sections) % of total €millions The focus of this chapter is the production of estimates of A Agriculture, forestry, 89 0.4% the current and potential future size of the Data Economy of fishing the Netherlands and its four regions. As with the other country B Mining & quarrying 149 0.6% chapters, the focus of the assessment is on the year 2016, and C Manufacturing 2 , 388 9.7% also the growth trend for 2012-2016. The main metric used in the assessment is GVA, but there are also estimates provided D Electricity 394 1.6% for employment and business turnover/cost savings generated E Water supply 154 0.6% by the business use of data. F Construction 492 2.0%
All financial values are provided in terms of millions of Euros G Wholesale, retail 1, 557 6.3% using a 2016 price base. H Transport 652 2.6%
I Accommodation & food 46 0.2% Current (2016) size of the Netherlands Data Economy J ICT 8,418 34.2% K Financial services 4, 2 25 17.1% It is estimated that the Netherlands Data Economy generated L Real estate activities 616 2.5% GVA worth just over €24.6 billion in 2016. The largest contributors M Professional services 2 ,121 8.6% to this total were provided by the ICT, Financial services, N Business support 860 3.5% Manufacturing and Professional services sectors, which together services accounted for 69.6% of the total Netherlands Data Economy. O Public administration 828 3.4%
P Education 509 2.1% The level of the contribution by sector is driven by several factors including: Q Health 752 3.1% R Arts, entertainment, 241 1.0% recreation • The absolute size of the sector compared to the economy S Other services 146 0.6% as a whole Total 24,637 100.0% • Businesses operating within sectors that possess a higher level of knowledge-intensity (such as pharmaceuticals and the media) generally have a greater propensity to invest in data analytics infrastructure and skills
• One notable feature of the sector breakdown for the Dutch Data Economy (compared to the other three countries considered in this report) is the relatively larger contribution from agriculture. The use of data in agriculture is increasingly important driven by the advent of precision farming technologies which allow for much more targeted use of agri-chemical inputs such as fertilisers, pesticides and fungicides.
72 DATA ECONOMY REPORT 2018 The overall amount of GVA generated by the Dutch • Major universities are often located in cities, providing economy in 2016 is estimated to be just over €627 billion. knowledge-driven businesses with a source of highly On this basis, the Netherlands Data Economy accounted for skilled graduate and post-graduate workers. approximately 3.9% of national economic output in 2016. The total number of direct jobs associated with the The Netherlands Data Economy can also be disaggregated Netherlands Data Economy in 2016 (based on data sourced by its four standard regions. The largest contributors to the from Eurostat) was slightly over 247,000. Employment in the Data Economy in spatial terms is West-Nederland (53%), Data Economy in the Netherlands during 2016 is estimated reflecting not only the greater size of that region but also to account for 3.20% of the overall number of jobs in the the greater concentrations of ICT, Financial services and Dutch economy as a whole. Professional services activity in that area. In addition to these direct jobs, the Data Economy also supports jobs via supply chain and multiplier efects. These 2016 GVA €millions Region % of total indirect and induced efects are estimated to amount to over (2016 prices) 101,000 jobs across the Netherlands in 2016. Noord-Nederland 2,065 8.4% Oost-Nederland 4,677 19.0% Therefore, the total amount West-Nederland 13,068 53.0% of employment attributable Zuid-Nederland 4,827 19.6%
Total 24,637 100.0% to the Netherlands Data Economy in 2016 is estimated This spatial distribution of activity is almost certainly linked to amount to just over to the location within West-Nederland of some of the country’s largest cities, including Amsterdam, Rotterdam, 349,000 jobs. The Hague and Haarlem. There is strong evidence that the Data Economy is growing fastest in the largest cities of advanced economies, for the following reasons:
• Clustering of the ICT sector in major cities, driven by the presence in those places of demand for ICT services on the part of other knowledge-driven sectors such as Financial services, Professional services, Media and creative industries and Government - these sectors tend to be concentrated in major cities
• As a corollary, major cities also tend to possess the largest density of knowledge economy businesses and workers compared to their host countries as a whole 349,000 jobs • The most advanced and densest networks of telecommunications and other necessary infrastructure is usually found in cities, and the largest cities tend to be where the next generation of telecoms technology tends to be rolled out first
DATA ECONOMY REPORT 2018 73 Growth trajectory since 2012
Overall, the financial value (in terms of GVA) of the Comparing the estimates for 2012 to those for 2016, the Netherlands Data Economy is estimated to have grown from most significant increases (in absolute terms) have occurred just under €17.5 billion in 2012 to just over €24.6 billion in in ICT, Financial services, Manufacturing, Professional 2016. services and Wholesale & retail sectors. However, in proportionate terms significant increases have occurred in a This implies an average range of other sectors including the Agriculture, forestry & fishing and the Mining & quarrying sectors. annual increase of around 8.9% in the size of the Data Economy over this period.
GVA 2012 GVA 2016 Change Change Sector (Sections) €millions €millions (€millions) (%)
A Agriculture, forestry, fishing 35 89 54 154%
B Mining & quarrying 63 149 86 137%
C Manufacturing 1,708 2 , 388 680 40%
D Electricity 335 394 59 18%
E Water supply 110 154 44 40%
F Construction 260 492 232 89%
G Wholesale, retail 878 1, 557 679 77%
H Transport 409 652 243 59%
I Accommodation & food 2 2 46 24 109%
J ICT 6,092 8,418 2,326 38%
K Financial services 3, 513 4, 2 25 712 20%
L Real estate activities 357 616 259 73%
M Professional services 1,466 2 ,121 655 45%
N Business support services 481 860 379 79%
O Public administration 643 828 185 29%
P Education 361 509 148 41%
Q Health 512 752 240 47%
R Arts, entertainment, recreation 163 241 78 48%
S Other services 86 146 60 70%
Total 17,494 24,637 7,143 41%
74 DATA ECONOMY REPORT 2018 A regional disaggregation can also be estimated for both Over the same period the number of direct jobs associated 2012 and 2016. This analysis – set out in the table below – with the Data Economy is estimated (using data sourced reveals that the West-Nederland region is growing its share from Eurostat) to have increased from about 210,000 to just of the Dutch Data Economy, from 51.5% in 2012 to 53.0% by over 247,000. Therefore, the increase in the number of direct 2016. Moreover, this region accounted for 56% of the overall jobs attributable to the Netherlands Data Economy over the growth of the Dutch Data Economy over this period. 2012-2016 period is estimated to be around 38,000 (18%).
Over the 2012-2016 period the proportion of workforce jobs 2012 GVA 2016 GVA Change Change Region (€millions) (€millions) (€millions) (%) attributable to the Netherlands Data Economy is estimated to have increased from about 2.8% to 3.2%. Noord- 1,565 2,065 500 32% Nederland
Oost- 3,527 4,677 1,150 33% Nederland
West- 9,022 13,068 4,046 45% Nederland
Zuid-N 3,381 4,827 1,447 43% ederland
Total 17,494 24,637 7,143 41%
These trends again underline the clustering trend for the Data Economy in major urban areas that have the densest networks of customers, suppliers, advanced telecoms infrastructure and the availability of highly skilled workers and graduates.
The current size of the Netherlands Data Economy in terms of the impact on business and organisation turnover and cost savings has also been estimated. The estimated efect on Dutch business/organisation turnover and costs in 2016 was worth a total of €56.9 billion. The equivalent figure for 2012 is estimated to be around €39.9 billion (in terms of 2016 prices). This implies an overall increase in value of about 43%. The sectoral breakdown of this increase is very similar to that for GVA set out in the table above.
DATA ECONOMY REPORT 2018 75 Current size of Data Economy versus current potential
Estimates have also been produced of the current (2016) size of the Netherlands Data Economy compared to the extent it could have reached by this point if all constraints (both on the demand side and the supply side) had been addressed.
The main constraints that hinder the growth of the Dutch Data Economy are as follows:
.Under-investment by businesses In particular SMEs who may not recognise the potential that is ofered by data analytics, or who may struggle to access financial resources and expertise needed to design and implement appropriate data strategies.
.Skills gaps and shortages A significant issue for many businesses is dificulty recruiting or retaining workers with the skills needed to develop and maintain data analytical systems.
The estimates of the actual versus full potential of the Netherlands Data Economy are presented in the next table, disaggregated by business sector. The table shows current levels of performance (in terms of GVA) and the proportion of overall potential value generation that this is estimated to represent.
76 DATA ECONOMY REPORT 2018 Full Potential GVA minus 2016 Actual GVA 2016 Full Potential GVA Actual GVA as % Sector (Sections) Actual GVA €millions €millions of Full Potential €millions
A Agriculture, forestry, fishing 89 241 152 37%
B Mining & quarrying 149 292 143 51%
C Manufacturing 2 , 388 5,056 2 ,668 47%
D Electricity 394 747 353 53%
E Water supply 154 308 154 50%
F Construction 492 1,208 716 41%
G Wholesale, retail 1, 557 3,172 1,615 49%
H Transport 652 1,468 816 44%
I Accommodation & food 46 113 67 41%
J ICT 8,418 15,675 7, 257 54%
K Financial services 4, 2 25 8,005 3,780 53%
L Real estate activities 616 1,385 7 70 44%
M Professional services 2 ,121 4,323 2 , 201 49%
N Business support services 860 2,111 1, 251 41%
O Public administration 828 1,790 961 46%
P Education 509 1,058 549 48%
Q Health 752 1,889 1,137 40%
R Arts, entertainment, recreation 241 605 364 40%
S Other services 146 394 248 37%
Total 24,637 49,838 25, 201 49%
The estimates suggest that whereas, in 2016, the Moreover, sectors such as Agriculture, forestry & fishing Netherlands Data Economy was worth around €24.64 billion, and Health are operating at a level that is significantly the full potential value that could have been generated that worse (in terms of unfulfilled potential) than the economy- year was approximately €49.8 billion. wide average. On the other hand, sectors such as Financial services and Electricity appear to be achieving a greater- Therefore, in 2016 the actual than-average proportion of the existing potential (albeit with substantial scope for improvement still remaining). Netherlands Data Economy was only operating at around
49% of its full potential in terms of contributions to revenue generation and productivity.
DATA ECONOMY REPORT 2018 77 Conclusions
The current scale of the contribution of the Netherlands Data Economy is estimated to amount to over €24 billion per annum. The contribution has grown from €17 billion in 2012. The recent growth trajectory is therefore nearly 9% per annum. 9% This is well ahead of the annual growth rate for the Dutch per annum economy as a whole, and it is also significantly faster than the most recent growth rate for the UK economy over the same time period. It is however, slightly slower than the equivalent growth rate for Germany (8%).
Despite this level rate of recent growth, the Netherlands Data Economy currently operates well within its full potential. It is estimated that slightly over half of the available value- adding potential remained unrealised during 2016. The main causes of the lost potential for additional business turnover, economic output and growth of employment from the analysis of data are:
• Under-investment by many businesses – particularly SMEs – in developing and utilising the potential value to be created through the analysis of their operational, market and other data
• Skills shortages (the inability of businesses to fill vacancies for digitally skilled workers in good time)
• Skills gaps: a deficit in technical and/or managerial skills on the part of some currently employed workers (which could be addressed through workforce development and training).
78 DATA ECONOMY REPORT 2018 7 Emergence of Data Centres as Key Players in the Data Economy
The earlier chapters have concentrated on how much In the UK context, ONS data indicates that UK-based value is being, or could be, garnered from data. Data itself, data centres have become a significant feature of the however, also has its needs: it needs to be stored, managed, UK economic landscape (in terms of turnover and GVA accessed and analysed. Data centres are crucial to doing generated) in recent years. For example, between 2008 that at the scale at which the modern Data Economy needs and 2015, companies operating data centres in the UK have to operate. This chapter, therefore, considered their role in experienced increases in the following metrics: more detail. .Turnover Data centres are specialised buildings primarily housing Increased from £5.3 billion to £8.9 billion (67% overall computer equipment combined with high-capacity increase, CAGR31 = 7.6% p.a.). telecommunications infrastructure, storage systems and energy supply. Data centres enable the receipt, storage, .GVA transmission and processing of very large quantities of Increased from £3.4 billion to £6.2 billion (80% overall digital data generated because of the increasing number of increase, CAGR = 8.8% p.a.) digital devices and functions across a range of applications. .Workforce Data centres have emerged over the past 20 years or so Increased from approximately 39,000 to 46,000 (18% overall as a consequence of the huge increase in the creation of increase, CAGR = 2.1% p.a.) digital data across a range of sources, including telecoms, financial services, retail, transport, health, entertainment and However, the main economic contribution of data centres social media. The emergence of data centres also reflects is indirect rather than direct: this indirect economic the increasing tendency to house IT resources in specialist contribution is driven by the role data centres play in purpose-built facilities with resilient power supply and high providing vital IT services for many other businesses that capacity fibre connectivity rather than on company premises use their services. The provision of these services enables (such as in server rooms or basements). other businesses to operate more eficiently and with higher degrees of productivity than would be possible otherwise. In the early days of the data industry data hosting was typically carried out on-site, with a business (or Government department) accommodating its own data on servers located within their own buildings. As the demand for data grew and services became more diverse, data hosting increasingly became outsourced. This was coupled with the emergence of high-capacity data storage providers operating out of their own large and resilient data centres.
Data centres are increasingly important economic assets in their own right. Firstly, they require substantial investment to build and fit out, with often over £100 million of investment required for each data centre. Data centres also require a highly skilled workforce to maintain and operate the equipment provided within each centre.
DATA ECONOMY REPORT 2018 79
31 | Compound Annual Growth Rate. Data centres tend to be located in key clusters, primarily in the world’s major financial and business service centres, including London, Frankfurt, Amsterdam and Tokyo. Important drivers influencing the location of data centres in Europe include the following:
.Customers Major cities tend to have the densest concentration of major sources of demand, including major financial institutions, media and entertainment activities, and professional services activities.
.Infrastructure Major cities tend to have the highest density of high capacity telecommunications infrastructure.
.Skills Major cities have the largest and deepest labour markets and they also have the ability to attract and retain highly skilled knowledge-industry workers. They also tend to host major universities providing an important source of skilled graduates and post-graduates and therefore provide a constant source of new workers helping to expand the workforce of a growing industry.
The European Data centres Marketview identifies four European cities as ‘Tier 1’ locations for data centres in the European context. These cities are London, Frankfurt, Amsterdam and Paris. The latest data on the relative capacity of the four Tier 1 centres and the changes occurring since 2015 are summarised below:
Market Market Change Change Vacant Vacant Location capacity 2017 capacity 2017 2015-2017 2015-2017 capacity capacity Q3 (MW) Q3 (MW) (MW) (%) (MW) (%)
London 437 354 83 23% 74 16.9%
Frankfurt 240 184 56 30% 42 17.5%
Amsterdam 240 164 76 46% 41 17.1%
Paris 156 140 16 11% 27 17.3%
The largest increase in capacity in absolute terms between 2015 and 2017 occurred in London, but the relative capacity of Frankfurt and Amsterdam increased at a faster rate over this period. The data centre capacity located in Amsterdam increased the fastest of all, at a rate of 46% between 2015 and 2017.
80 DATA ECONOMY REPORT 2018 Nevertheless, London still provided 41% of overall Tier 1 capacity in 2017, only slightly down from 42% in 2015.
According to the European Datacentres Marketview (CBRE, 3rd quarter, 2017) there are over 500 data centres located in the UK, with 70% of these located within or around the M25. London is identified by this source as the second largest data centre market in the world, providing nearly twice as much capacity as the next largest European centres (Frankfurt and Amsterdam). Within the UK, the next most important location after London is identified as Manchester.
Data available for the UK also enables the contribution of each data centre to be calculated: the average amount of GVA per data £397-£436 centre is estimated to lie million p.a. for newly built been £291 million and £320 data centres million p.a. This range is significantly higher for newly built data centres, which add between £397 million and £436 million p.a.
The capacity of data centres in Ireland is not covered by the CBRE annual Marketview report. However, there are separate estimates of the size of the Irish data centre sector provided within a specific report produced by Host in Ireland. This report, dating from 2017, identifies a total of around 100- 120 MW of co-location data centres in Ireland. This type of facility is comparable to the data in the previous table for London, Frankfurt, Amsterdam and Paris.
In addition, there is estimated to be around 300MW of so- called hyperscale private data centres located in Ireland and operated by such household names as Amazon, Google and Facebook.
DATA ECONOMY REPORT 2018 81 8 How to Unlock the Potential of Data
The assessment in the preceding chapters identifies that .c between 50% and 60% of the potential of the Data Economy Companies that hold customer data also need to have a is not being realised in each of the four countries that have robust set of policies in place that safeguard customer been considered. While it is expected that the value of the data from illegal, unethical or inappropriate. Data Economy will continue to grow in each country, there is a danger that – unless significant constraints and barriers .02 are not addressed – a larger proportion of the increasing There are unrealised opportunities for businesses of all potential value of the Data Economy will remain unrealised. sizes to utilise the data they hold across all areas of their operations, from data held on customers through to all Across all four countries the types of constraints and relevant areas of operations, such as (depending on the hindrances are similar in nature, although they vary in nature of the individual business): production lines, logistics, intensity to some extent both between countries and management of premises, R&D, etc. Many companies have between sectors and regions within individual countries. achieved excellent results in some operational and customer focused areas, but there may be other parts of the business Provided below is a set of actions focused on individual where opportunities for eficiency and/or enhanced revenue businesses, business networks and Government that are generation remain. Senior management in large businesses relevant to all four of the countries considered in this report. must therefore lead and fully integrate digital transformation Additional points that are particularly relevant to the UK and in their companies as a key backbone of long-term business Ireland are highlighted in a small number of instances. development strategy. This is especially important for businesses operating in sectors that have hitherto been Actions for industry groups and slower at making significant investments in data analytic individual businesses capabilities, including investment in infrastructure, equipment and software to enable advanced data analytics .01 capabilities, but also in terms of investing in both managerial Business have a lot of work to do to build confidence and capacity and technical skills that are needed to grasp the trust with respect to the handling of customers’ data. opportunities more fully. Distrust and concerns about privacy and security must be resolved by industry (and Government) if the full value of .03 the Data Economy is to be realised. In particular: All large businesses (i.e. more than 250 employees) should appoint a Chief Data Oficer reporting to the CEO to .a coordinate strategy and ensure full integration with wider Companies that hold customer data must minimise or business objectives. prevent cyber-attacks by investing in infrastructure, software, staf training and other safeguards to protect .04 the integrity of customer data Large businesses also have a potential role to play in helping to encourage and mentor SMEs to investigate and .b develop data analytics infrastructure and applications. Companies should also work with suppliers and through There is an opportunity for larger businesses to provide business networks to share best practice experience and support for SMEs who are members of their supply chain, information to help raise the standard of data security by defining standards and by sharing best practice and protection experience and expertise.
82 DATA ECONOMY REPORT 2018 .05 .09 There is also a major opportunity for a larger number of It is expected that the advent of a fifth generation (5G) of SMEs to begin to secure business growth and productivity mobile telephony and ultrafast broadband will facilitate a gains that are available from analysis of their own data within further acceleration of data opportunities, ranging from video what data protection rules permit. Essentially, the availability and audio streaming, through to online computer gaming, of analytical functionality via Cloud computing means that virtual and augmented reality applications, and autonomous tools and infrastructure previously only available to larger vehicles. It is therefore vital that telecommunications companies are now within the scope of smaller businesses. infrastructure providers (many of whom are private sector) continue to invest in telecoms infrastructure capacity, .a both in terms of ultrafast broadband and in the emerging SMEs can start by identifying all sources of customer and 5G networks. business performance data generated by their business.
.b The next step is to consolidate the data into a single tool, such as a customer relationship management system.
.c The small or medium sized business is then able to use the data to produce analytical reports and performance dashboards so that useful information can be produced and acted upon. For example, analysis of customer contact data can be used to better predict future patterns of customer behaviour and/or to deal better with customer feedback and complaints.
.06 There is an urgent need for further investment by the private sector in recruiting workers and developing training programmes – such as digital apprenticeships – targeting school leavers and returners to the workforce.
.07 Peak industry bodies - such as the CBI, the Institute of Directors and the Federation of Small Businesses (FSB) in the UK - should pool resources to campaign for greater awareness of the value of data (and the reasons why this value will increase in the next few years) among businesses large and small.
.08 Sector network groupings - such as the Sector Skills Councils in the UK context - should each devise sector-specific programmes designed to raise awareness and address sector-specific constraints such as skills shortages.
DATA ECONOMY REPORT 2018 83 Actions for Government
Investing in education and skills Telecommunications infrastructure
Realising the full value of the Data Economy requires access Government has a role to play in providing the regulatory to the right technical and professional skills, including data framework for the next generation of fixed and mobile engineering skills to develop a robust data infrastructure, telecoms infrastructure. There is also a specific planning data analysis skills to extract valuable insights from data, and policy issue with the future mobile network as 5G will require business skills to apply them. a much denser physical coverage of masts and relay stations compared to the current 4G network. This isn’t just relevant .01 to rural areas: investment will be needed to ensure good Government has a role in continuing to improve the quality of coverage within and between buildings in more curriculum and in enhancing the quality and relevance densely populated urban areas. of teaching of subjects such as mathematics, statistics and computer science in secondary, further and Better use of data by Government in delivering services higher education. There are opportunities to improve the performance of .02 Government as data-led service providers: Government Government can also help to promote the Data Economy needs to continually rethink the way that services are as a career destination for young people, especially delivered and truly embrace a Data Economy approach. For among groups (such as females) who are traditionally example, in the UK it is estimated that only about 10% of under-represented in computer science and similar central government workloads have moved to cloud storage, occupations. and in parts of the health sector or local government it is estimated to be as a low as 2%. .03 Government also has a potentially important role in helping to retrain older workers (including those who have had a period of absence from the workforce) and in providing incentives for smaller businesses to invest in workforce training.
Open Data policies
Government has a key role to play in making its own data Open Data, available and shared for others to use. Even in the UK (which is ranked top globally for openness of Government data) there is still more to do. In Ireland this is a particularly pertinent issue as Ireland has a relatively low ranking (27th) in the global Open Data Barometer rankings (albeit its position has improved – by four places – in the most recent ratings).
84 DATA ECONOMY REPORT 2018 About Digital Realty Contact us
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