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A Final Report 16 September 2021 Department for Digital, Culture, Media & Sport: Assessing the UK’s Regional Digital Ecosystems Steer Economic Development has prepared this material for Department for Digital, Culture, Media & Sport. This material may only be used within the context and scope for which Steer Economic Development has prepared it and may not be relied upon in part or whole by any third party or be used for any other purpose. Any person choosing to use any part of this material without the express and written permission of Steer Economic Development shall be deemed to confirm their agreement to indemnify Steer Economic Development for all loss or damage resulting therefrom. Steer Economic Development has prepared this material using professional practices and procedures using information available to it at the time and as such any new information could alter the validity of the results and conclusions made. A Final Report 16 September 2021 Department for Digital, Culture, Media & Sport: Assessing the UK’s Regional Digital Ecosystems Prepared by: Prepared for: Steer Economic Development 61 Mosley Street Manchester M2 3HZ Department for Digital, Culture, Media & Sport 100 Parliament Street London SW1A 2BQ United Kingdom +44 (0)161 261 9154 www.steer-ed.com 240-458-01 Department for Digital, Culture, Media & Sport: Assessing the UK’s Regional Digital Ecosystems | A Final Report 16 September 2021 Contents Executive Summary ....................................................................................................... i 1 Introduction ......................................................................................................... 1 2 Approach and Methodology ............................................................................... 4 3 The Digital Economy in a UK Context ............................................................. 16 4 Summary Dashboards ...................................................................................... 22 East Midlands – Summary Dashboard ................................................................ 25 East of England – Summary Dashboard ............................................................. 35 London – Summary Dashboard .......................................................................... 45 North East – Summary Dashboard ..................................................................... 55 North West – Summary Dashboard .................................................................... 65 Northern Ireland – Summary Dashboard ............................................................ 75 Scotland – Summary Dashboard ........................................................................ 85 South East – Summary Dashboard ..................................................................... 95 South West – Summary Dashboard .................................................................. 105 Wales – Summary Dashboard .......................................................................... 115 West Midlands – Summary Dashboard ............................................................. 125 Yorkshire and The Humber – Summary Dashboard ......................................... 135 5 Conclusions ..................................................................................................... 145 Appendices A: SIC and SOC Codes for the ‘Digital Economy’ used by the Study B: Sources for the longlisted metrics considered for characterising the enabling domains of the digital economy ecosystem C: Summary Dashboards for each of the UK’s NUTS2 regions D: Write-up of the Rapid Evidence Review which informed the Study’s approach and method Department for Digital, Culture, Media & Sport: Assessing the UK’s Regional Digital Ecosystems | A Final Report 16 September 2021 List of Acronyms Acronym Definition ABS Annual Business Survey APS Annual Population Survey BRES Business Register and Employment Survey DCMS Department for Digital, Culture, Media & Sport ESF European Social Fund (ESF) FTE Full Time Equivalent job GVA Gross Value Added - a measure of the value of goods and services produced in an area, industry or sector of an economy. It is calculated as the value of outputs minus the value of intermediate consumption HE Higher Education HESA Higher Education Statistics Agency IDBR Inter-Departmental Business Register KPI Key Performance Indicator LQ Location Quotient - an analytical statistic that measures a region’s industrial specialisation relative to a larger geographic unit (usually the nation) NUTS Nomenclature of Territorial Units for Statistics - a geocode standard for referencing the subdivisions of countries for statistical purposes ONS Office for National Statistics REF Research Excellence Framework STER Scottish Technology Ecosystem Review SIC Standard Industrial Classification - a system for classifying industries by a four-digit code SOC Standard Occupational Classification - a coding framework used to classify occupations, enabling comparisons of occupations across different datasets VC Venture Capital Department for Digital, Culture, Media & Sport: Assessing the UK’s Regional Digital Ecosystems | A Draft Report 13 August 2021 | i Executive Summary Overview 1. This report summarises the findings of research into the digital ecosystems of the UK’s nations and regions, commissioned by the Department for Digital, Culture, Media and Sport (DCMS). 2. The study has developed a framework for characterising digital ecosystem performance across five ‘enabling domains’: • Digital Tech Businesses, Employment and GVA; • Place and Infrastructure; • Ideas and Innovation; • Investment and Business Environment; and • People, Skills and Inclusion. 3. Within each of these domains, various metrics have been selected and gathered, to present as full a view as possible at each of three geographic levels (NUTS1, NUTS2, and NUTS3). The metrics have been normalised (e.g. for population size) and presented in a way that shows each area’s performance relative to all other UK areas at that level of geography. This approach was chosen to avoid comparing regional performance against a ‘UK average’, which is in practice skewed highly by London and the South East. 4. The quantitative analysis for the study has been complemented with a series of roundtable discussions with stakeholders in each of the 12 NUTS1 regions, discussing the digital ecosystems of each nation and region. Findings 5. The digital sector1 represents a substantial share of the UK economy. It employed around 1.66 million people (between October 2019 – September 2020), accounting for 4.9% of all employment. In terms of Gross Value Added (GVA), the sector contributed £148 billion to the UK economy in 20192 (constant prices), which was 7.6% of the UK total. 6. This research confirms that every nation and region of the UK is seeing vibrant growth in their digital ecosystems. Growth is particularly strong in larger cities, which benefit from agglomeration economies and cluster effects. Larger cities offer people a wide range of job opportunities, providing firms with a large addressable labour market and stronger networks of industry contacts. 1 See Figure 2-1 for how the ‘digital sector’ and ‘digital occupations’ have been defined for the purpose of this study 2 DCMS Sectors Economic Estimates 2019 (provisional): Gross Value Added Department for Digital, Culture, Media & Sport: Assessing the UK’s Regional Digital Ecosystems | A Draft Report 13 August 2021 | ii 7. By continuing to support and strengthen digital ecosystems throughout the UK, indicative modelling projects that the UK’s digital sector annual GVA could grow by an additional £41.5 billion by 2025, creating a further 678,000 jobs3. 8. Drawing on a variety of indicators, this report paints a nuanced picture in which each nation and region has a different mix of strengths and challenges in their digital ecosystem. 9. The study highlights that there is much commonality between regions in the specific parts of the digital economy where stakeholders consider there to be good prospects for future growth. FinTech, Cyber Security, HealthTech, Big Data, Artificial Intelligence and the digital transformation of traditional industries (including Advanced Manufacturing) were each explicitly highlighted as promising areas, and the study’s assessment of the data on high growth companies confirms that these are of key importance to almost all regions. 10. Beyond the tech hotspots of London and the South East, there are clusters of specific specialisms, for example: FinTech (e.g. Scotland and Wales), Cyber Security (e.g. Northern Ireland and South West), HealthTech (e.g. East Midlands and Scotland), e-Commerce and AdTech (e.g. North West and Northern Ireland), Big Data (East of England and Wales), EdTech (West Midlands and North West), AgriTech (e.g. East of England and Yorkshire and the Humber), Internet of Things (e.g. South West and Wales), Space Tech (e.g. Yorkshire and the Humber), the digitisation of advanced manufacturing (e.g. West Midlands and North East), and the digital delivery of public services (e.g. North East and Scotland). 11. However, it should also be stressed that each of the nations and regions has extensive digital activities beyond the specific examples cited above. As a result, ensuring that there are the right enabling conditions in which all parts of the digital ecosystem can flourish must be a key imperative for economic development policy. 12. The shift to remote working practices enforced by COVID-19 is likely to endure, to a significant extent, post-pandemic. This has the potential to work to the advantage of the digital ecosystems beyond London, since it could reduce geographical barriers and widen the pool of experienced talent available to firms across the UK. 13. However, the study also found that the increased willingness of London-based firms, and even Silicon Valley firms, to employ remote workers was leading to wage inflation for experienced talent in other regions. This is making it somewhat harder for non-London based businesses to recruit locally in some regions, as they are increasingly competing with London-based firms for talent living in their areas. 14. Access to talent was consistently highlighted as the most important barrier to growth for regional digital ecosystems. More could be done to encourage school 3 Methodology described in paragraph 2.35 Department for Digital, Culture, Media & Sport: Assessing the UK’s Regional Digital Ecosystems | A Draft Report 13 August 2021 | iii leavers to gain competencies in programming, data science and computer science, promote computing-related pathways at university, and inspire more UK- based students to set up their own tech businesses after university. Industry, educators and Government should work together to upskill more people (both our current and future workforce) into digital occupations so they can share in the prosperity of the digital sector.. 15. For companies located outside London and the South East, it can be very difficult to attract experienced talent from elsewhere in the UK or from overseas – especially mid-career programmers and senior executives with experience in successfully scaling tech businesses. This is because digital ecosystems beyond London and the South East are yet to reach a ‘critical mass’ of activity which makes it relatively easier to attract and retain talent. 16. The availability of growth capital is also heavily skewed geographically. Data from Beauhurst4 shows that out of the £15.5 billion of private funding raised in the digital sector5 between 2016 and 2020, 73% (£11.3 billion) went to London-based businesses. In the roundtable discussions several people expressed the view that it is difficult to persuade some venture capitalists (VCs) to make digital sector investments beyond London and the South East, due to the large number of investment opportunities that already exist in those regions. 17. Agglomeration effects are at work here too, i.e. if a region has relatively few investment opportunities at an appropriate scale, quality and stage, then venture capitalists may consider the region to be too small to be worth exploring, and/or too small to sustain a scale-up. 18. All of the UK’s nations and regions have key assets which are essential for supporting thriving digital ecosystems, albeit to differing degrees between the regions. These key assets include: • Universities, with world-class excellence in digital-related research, and with substantial numbers of students enrolled on computing courses; • Digital-focused incubator facilities, and accelerator programmes for start-up and scale-up; • Industry-led tech cluster organisations, acting as catalysts for networking and knowledge exchange; • Tech-focused networks/events, including large annual conferences, which help bring people together, raise the profile of the region’s digital sector, and create the virtuous circles of collaboration; and • Emerging clusters of some particular industrial specialisms (e.g. cyber security, FinTech, HealthTech), providing foundations for further growth.. 19. In London, and increasingly in some of the UK’s other major cities such as Birmingham, Edinburgh, Leeds, and Manchester, there is also a further critical 4 Search conducted and data downloaded on 28 April 2021 5 Defined by DCMS Digital Sector SIC codes as listed in Appendix A Department for Digital, Culture, Media & Sport: Assessing the UK’s Regional Digital Ecosystems | A Draft Report 13 August 2021 | iv ingredient for world-class digital ecosystems: scale. With a diverse mix of employers, an extensive labour market, and large numbers of job opportunities at every level of seniority, London’s scale is a key factor in driving its unrivalled growth. Going Forward 20. In the light of these findings, this study proposes that the following should be considered by DCMS and other Government departments when developing policy in this area: • Careful consideration should be applied to the scope of economic activity that policy interventions are trying to support. There are various ways of defining the digital economy, and the current DCMS definition of the ‘Digital Sector’ is very broad. For example, it includes publishing, TV broadcast activities and motion picture projection activities, as well as telecommunications and computer programming. While this may be appropriate for statistical reporting purposes, it could hinder the development of world-class interventions that address the diverse needs of such a broadly defined sector. An alternative approach could focus on software engineering-intensive businesses, irrespective of domain, that operate under ‘internet economy’ principles. • A sustained and long-term cross-government approach is required to address the skills and talent issues highlighted. Fundamental to this would be to increase the capacity of schools to teach computer science, and to improve computer science participation in schools throughout the UK - especially amongst girls and other under-represented groups. • Although it is a much broader issue, the problems of digital poverty have been brought into sharp focus by COVID-19 restrictions. Consideration should be given to the options for ensuring that young people from disadvantaged backgrounds are not de facto excluded from experimenting with computers and seeking digital occupations in the future, as a result of them lacking appropriate devices and broadband at home. • Adult education can provide opportunities for people at various life-stages and from diverse backgrounds to direct their careers towards digital industries, recognising that a large majority of the people who will make up the UK’s workforce in 2030 are already in the workplace. This should be a well-funded and enduring feature of policy, building on initiatives such as CodeClan in Scotland and DCMS’ Local Digital Skills Partnerships and digital skills bootcamps delivered in many of England’s main cities. • The issue of university key performance indicators (KPIs) and incentives to improve innovation development and entrepreneurship emerged in some of the roundtable discussions. We propose that this area should be considered within the policy development process, seeking to ensure that universities are appropriately encouraged to grow the local base of skilled personnel, to increase spin-outs and industry collaborations, and to ensure that students are exposed to entrepreneurship education. • Grassroots industry-led cluster organisations play a critical role in developing local tech communities. Government might consider how best to provide practical support for such initiatives, for example in their core funding, Department for Digital, Culture, Media & Sport: Assessing the UK’s Regional Digital Ecosystems | A Draft Report 13 August 2021 | v business support programmes, locations for meetings, and remote participation facilities. • Support might also be considered for the various tech events and conferences held throughout the country – helping with speakers, facilitating remote participation, and ensuring that these events expose local tech communities to international contacts for business opportunities and international best practice in growing tech businesses. • While all Nations and regions in the UK have some digital incubators, they vary considerably in terms of capacity and local/national profile, and hence in their ability to act as a flagship physical hub for the local digital ecosystem. The Government should consider how it can ensure that every major city has sufficient incubator capacity of an appropriate type, with the financial support necessary to offer low rents to start-up tenants, easy-in/easy-out terms, and with the ability to provide founders with support and education in managing growth. Facilitating networks of relevant incubators at regional or even national levels may be helpful in strengthening connections within the tech community. • Insufficient access to growth finance is clearly a challenge to the development of digital ecosystems outside London and the South East. The Government should work with venture capitalists and local tech cluster groups to consider how best to address this critical issue. • The capacity of public sector leadership organisations to develop high performing digital ecosystems varies significantly between different places. DCMS should consider how best to ensure a joined up and adequately resourced approach is taken by the public sector to enable growth based on the different circumstances across the UK’s regions. Department for Digital, Culture, Media & Sport: Assessing the UK’s Regional Digital Ecosystems | A Final Report 16 September 2021 | 1 Purpose of the Study 1.1 In March 2021, the Department for Digital, Culture, Media and Sport (DCMS) commissioned Steer Economic Development (Steer-ED) and its subcontractors6 to assess the ecosystems operating across the UK to support the digital economy. For the purpose of this report, the ‘digital economy’ is defined as businesses and organisations producing products and services in digital sectors, plus those job roles in sectors not classified as digital but which require digital skills and activity (such as a software developer working for, for example, a logistics company). 1.2 DCMS’ objective in commissioning the study was to better understand the factors that are shaping and enabling these ecosystems and, informed by this, to provide a ‘snapshot review’ of the capacities of these ecosystems. The work was envisaged to have two outcomes: • Stage 1: Developing a comprehensive framework for analysing regional digital economy ecosystems, which could be used to assess − The performance of the digital ecosystem in differing regions; − Regions’ ability to support digital economy growth; and − Existing inter-and intra-regional disparities in the way the digital economy ecosystem works in different places. • Stage 2: Undertaking a comprehensive review of regions’ strengths, specificities, and institutions, assessing specifically: − Digital specialisms and assets within regions that support the digital economy; and − Regions’ abilities to optimise digital economy prosperity. 6 DMS Research Consulting, John Holden from The University of Manchester, and Geek Talent Ltd 1 Introduction Department for Digital, Culture, Media & Sport: Assessing the UK’s Regional Digital Ecosystems | A Final Report 16 September 2021 | 2 1.3 The work was undertaken at the level of the UK’s 12 NUTS1 regions7. For the ecosystem in each NUTS1 region, the study sought to identify the strengths, opportunities, digital technology specialisms, and the barriers to digital economy growth on a consistent and systemic basis, drawing on the latest data (both quantitative and qualitative) from national datasets, specialist data providers, reports/literature, and regional consultees. 1.4 This report sets out the findings of this work, which was undertaken between March and August 2021. Context for the Study 1.5 DCMS has a long-standing commitment to driving better outcomes for places and communities. Reflecting its more recent policy responsibilities for the digital economy, the DCMS Secretary of State’s 10 Tech Priorities8 sets out a series of commitments through which the Department ‘will deploy digital tech to ‘build back better’, safer, and stronger from COVID[-19], and shape a new golden age for tech in the UK’. Of these 10 priorities, Priority 9 was the highly influential driver for this study: DCMS Tech Priority 9: Levelling up digital prosperity across the UK ‘As we turbocharge our tech sector, we will ensure long-term digital prosperity is evenly spread across the entire country. Many of our most exciting tech companies are already based outside of London, and we will continue to support these hubs by building on regional innovation, regional strengths and regional specialisms, while enabling businesses in every UK postcode to seize the opportunities of the digital economy’. 1.6 Against this background, in commissioning the study, DCMS wished to develop a stronger evidence base to assess on a consistent basis the breadth and depth of NUTS1 regional ecosystems in support of their digital economies. This work seeks to identify how regions can develop their strengths and level-up further to those areas of existing ecosystem strength, and how and where ‘areas for development’ might be progressed. Whilst the data on the digital economy are wide and extensive, using a well-developed framework of analysis this work sought to provide a systemic, replicable, and importantly holistic view of how and why digital ecosystems across the UK are performing 7 Nomenclature of Territorial Units for Statistics (NUTS) is a hierarchical classification of administrative areas, used for statistical purposes. In the UK, there are 12 such areas - Northern Ireland, Scotland, and Wales, and the nine statistical regions in England - East of England, East Midlands, London, North East, North West, South East, South West, West Midlands, and Yorkshire and The Humber. Note that ONS has recently adopted the new UK classification of International Territorial Levels (ITL) in place of the NUTS classification. This transition has not changed the names of regions, or the areas covered by them; it is simply a change to the codes used. 8 Our Ten Tech Priorities, 2021, DCMS Department for Digital, Culture, Media & Sport: Assessing the UK’s Regional Digital Ecosystems | A Final Report 16 September 2021 | 3 Structure of this Report 1.7 This remainder of this report is structured with the following sections: • Section 2: Approach and Methodology – describes how the study was designed and framed, and the work which was undertaken practically; • Section 3: The Digital Economy in a UK Context – discusses the characteristics of the UK digital sector, providing the UK-wide backdrop against which individual NUTS1 region ecosystems for the digital economy are working; • Section 4: Summary Dashboards – This Section, the core of the report, sets out, using standard profiles for each of the UK’s 12 NUTS1 regions, a summary assessment of Strengths, Opportunities and Specialisms, Barriers to Growth, and how the ‘Prosperity Prize’ offered by the digital economy can be seized; and • Section 5: Conclusions – this final Section draws the study’s findings together and provides thoughts on ways forward for the Government. 1.8 The Main Report is supported by four technical appendices, as follows: • A: SIC and SOC Codes for the ‘Digital Economy’ used by the Study; • B: Sources for the longlisted metrics considered for characterising the enabling domains of the digital economy ecosystem; • C: Summary Dashboards for each of the UK’s NUTS2 regions; and • D: A write-up of the Rapid Evidence Review which informed the study’s approach and method. Department for Digital, Culture, Media & Sport: Assessing the UK’s Regional Digital Ecosystems | A Final Report 16 September 2021 | 4 Purpose 2.1 This Section sets out the approach adopted by the study, and then introduces the streams of work which it progressed. It explains how the ‘digital economy’ was defined, the data sources and metrics used, and how these are presented in this report. The Section also outlines the process used to engage with stakeholders across the UK’s 12 NUTS1 regions. Approach Three Phases 2.2 From the outset, this was recognised as a high-profile and challenging study, with 12 UK NUTS1 regions in view, and a large amount of data – both qualitative and quantitative - relating to the digital economy, be this in terms of ‘sector’ or ‘occupations’. 2.3 Reflecting this complexity and the need to draw-out messages and themes of value to DCMS’ policy makers and partners in the NUTS1 regions, the approach to the study was designed to comprise three stages of work: • Phase A: developing an analytical framework with which to assess the ecosystem for the digital economy in each of UK’s 12 NUTS1 regions; • Phase B: informed by the above, developing and designing metrics and an analytical tool with which to report coherently, communicably, and with as much comprehensiveness as possible how the digital economy ecosystem in each of the NUTS1 region was performing; and • Phase C: undertaking a detailed ecosystem assessment for each of the UK NUTS1 regions using the tool developed under Phase B. This was then augmented with qualitative inputs from regional consultation, resulting in a blended (i.e. quantitative and qualitative) assessment of each UK NUTS1 region’s digital economy ecosystem. Method 2.4 Informed by the approach above, the practical work done to deliver the study comprised the following elements: 1. Rapid Evidence Review 2.5 Much work has been undertaken over the last 35 years to understand the concept of the ‘economic ecosystem’, and the role this plays in the development of sectors, clusters, and agglomeration. The launch point for much of this thinking 2 Approach and Methodology Department for Digital, Culture, Media & Sport: Assessing the UK’s Regional Digital Ecosystems | A Final Report 16 September 2021 | 5 was Michael Porter’s path-finding study in 1989, The Competitiveness of Nations, with much research work done since, including by DCMS itself9. Figure 2-1: Definitions of digital sector and digital occupations used in this report Definitions of ‘Digital’ – Economy, Sector, and Occupations For the purpose of this report, the ‘digital economy’ was defined as businesses and organisations producing products and services in digital sectors, plus those job roles in sectors not classified as digital but which require digital skills and activity (e.g. a software developer working for a logistics company). Thus, when looking at the digital economy, the study considered both the ‘digital sector’ and ‘digital occupations’, which is in line with DCMS’ definition of the digital economy10. The ‘digital sector’, in terms of constituent firms, was defined according to DCMS’ published four-digit Standard Industrial Classification (SIC) Code definition. This definition includes 43 sub-sectors across the broad sections of Information and Communication, Manufacturing, and Wholesale and Retail Trades. Additionally, for datasets where only two-digit SIC Codes were available, the study used SIC Codes 58-63. In-scope SIC Codes are given in Appendix A. For ‘digital occupation’ or job roles, the digital sector was defined using DCMS’ published digital sector Standard Occupational Classification (SOC) Codes. A full list of these SOC Codes is presented in Appendix A. To give an overall picture of the extent of digital economy employment in each region, SIC-based and SOC-based data have been combined, showing both the employment in digital sector firms (using SIC Codes) and the digital occupation employment (using SOC Codes) – while taking account of the overlaps between these two (i.e. digital occupations within digital sector firms). 2.6 Accordingly, a key first activity for the study was to undertake a Rapid Evidence Review to unearth the range of analytical approaches taken in national and regional reports (or related studies) to characterise, define and then measure the digital economy and assess its potential for growth and prosperity. 2.7 A set of more than twenty papers and presentations were identified as potentially relevant. Of these, 10 were selected for further detailed review; these papers 9 This includes in-house desk research on the role of economic agglomeration and clustering, Smart Specialisation, and the role of Higher Education-driven innovation in regional ecosystems, and what this might mean for the Digital Economy at the regional level. 10 DCMS, 2019, DCMS economic estimates: employment. The digital economy was defined as "all those employed in the Digital Sector as well as those in Digital Occupations outside the Digital Sector." Department for Digital, Culture, Media & Sport: Assessing the UK’s Regional Digital Ecosystems | A Final Report 16 September 2021 | 6 were chosen based on public standing and their potential to provide insight into the essential components of a successful digital economy ecosystem, including the range of factors, enablers, and indicators used to assess it. The papers comprised the following: • National-level − The future UK tech built (2021)11; − Places of Innovation: The role of Districts, Quarters, Corridors and other venues of the COVID-19-adjusted innovation economy (2021)12; − Digital Industries in the UK (2016)13; − The prospects for regional disparities in the UK in the times of Brexit and COVID (2020)14; and − Blueprint for cities and regions as launch pads for digital transformation (2016)15. • Regional-level: − Matrix Digital’s ICT Report (2016)16; − Lancashire’s Digital Landscape (2019)17; − Scotland’s Digital Technologies (2019)18 ; − Sheffield City Region Digital, Digital Action Plan (2018)19; and − West Midlands Digital Roadmap (2021)20. 2.8 In addition, helpful wider framing was provided by the review undertaken by Mark Logan (formerly COO of Skyscanner) in 2020 for the Scottish Government to undertake the Scottish Technology Ecosystem Review (the ‘STER’). With a focus on software engineering-intensive start-ups and scale-ups that exhibit – or aspire to exhibit - characteristics common to successful tech start-ups internationally, it 11 The Future UK Tech Built, 2021, Tech Nation 12 Places of Innovation: The role of Districts, Quarters, Corridors and other venues of the Covid- adjusted innovation economy, 2021, Catapult 13 Digital Industries in the UK, 2016, Tech Partnership 14 The prospects for regional disparities in the UK in times of Brexit and Covid-19, 2020, Arnab Bhattacharjee, David Nguyen, and Tony Venables 15 Blueprint for cities and regions as launch pads for digital transformation, 2016, Strategic Policy Forum on Digital Entrepreneurship 16 Matrix Digital’s ICT Report, 2016, Matrix Digital ICT Panel 17 Lancashire’s Digital Landscape, 2019, Lancashire Enterprise Partnership 18 Scotland’s Digital Technologies: Research & Analysis Report, 2019, Digital Scotland Business Excellence Partnership 19 Sheffield City Region (SCR) Digital Action Plan, 2018, SCR LEP 20 West Midlands Digital Roadmap, 2021, West Midlands Combined Authority Department for Digital, Culture, Media & Sport: Assessing the UK’s Regional Digital Ecosystems | A Final Report 16 September 2021 | 7 proposes a set of 34 recommendations across three areas: Education and Talent; Infrastructure; and Funding. 2.9 A comprehensive overview of the findings from each report reviewed is set out at Appendix D. The key summary findings from the Rapid Evidence Review were as follows: • According to a report from the Strategic Policy Forum on Digital Entrepreneurship21, the key dimensions which trigger the digital transformation of an area include: Governance and Leadership; Communication and Collaboration; Entrepreneurs and businesses; Talent Pools; Finance; Infrastructure; Support Structures; and Digital Technology; • Another paper conceptualises the four core dimensions needed for a regional ecosystem to thrive and generate a critical mass of start-ups and high-growth companies as the following: Economic Demand drivers; the Enabling Infrastructure; the Skills Base; and the Framework Conditions for business and investment; • Studies most frequently made use of well-known administrative data sources, principally the: Interdepartmental business register (IDBR), Annual Population Survey (APS) and Annual Business Survey (ABS). Other public sources cited included the Higher Education Statistics Authority (HESA) and Ofcom's statistical publications. In addition, some ‘non-standard’ data sources were referenced, such as Dealroom, Streetbees, and Geek Talent; • Skills Demand and Supply were assessed as vital factors for assessing the digital economy; and • Regional specialisms and sub-sectors (such as HealthTech, FinTech etc.) had an important role to play in regional development. Measures which captured these should be sought, although the appropriate measure may vary between regions. 2. Framework Development 2.10 Informed by the Rapid Evidence Review and extended iterative dialogue between the Consultancy Team and the Study Steering Group, a framework with which to analyse the performance of regional ecosystem for the digital economy was developed progressively. Summarised in Figure 2-2, this envisages five ‘enabling domains’, which individually and jointly help to create the conditions to enable digital economy growth and resilience. The five domains, and their importance are set out below: Enabling Domain 1: – digital technology businesses, their employment, and the value creation 2.11 Key to any functional digital economy ecosystem is a viable stock of digital economy businesses, which provide the products/services and employment opportunities to create value and wealth. Without this key enabling domain, the 21 Blueprint for cities and regions as launch pads for digital transformation, 2016 Department for Digital, Culture, Media & Sport: Assessing the UK’s Regional Digital Ecosystems | A Final Report 16 September 2021 | 8 wealth-creating heart of the ecosystem is missing, and growth cannot happen effectively. Key considerations in characterising this domain include the mix of businesses (business numbers, specialisms, survival rates, productivity, growth potential etc), the share of the digital sector as a proportion for the wider economy, and the export orientation of the business base. Figure 2-2: A framework for assessing regional ecosystems for the digital economy Source: Steer-ED, 2021 Enabling Domain 2: – Place, Infrastructure, and Assets 2.12 Despite the increasing virtualisation of business activity, much still happens physically in places, premises, and facilities. These places, their infrastructures, and the support assets which accompany them all have a key influence on the wealth-creating process which good businesses embody. So, for example, are premises of the right type, in the right places, and at the right price point, and are wider assets that businesses need (for example lab and testing facilities, incubators, and accelerators etc) in place. An additional critical consideration here is how well-served these aspects are by connectivity (both physical and digital to allow the easy movement of products and services, and to allow firms to access seamlessly talent pools and supply chains. Department for Digital, Culture, Media & Sport: Assessing the UK’s Regional Digital Ecosystems | A Final Report 16 September 2021 | 9 Enabling Domain 3: Investment and Business Environment 2.13 This domain recognises that many firms often need factors external to the business to help them and achieve and maintain their optimum growth. This includes the access that businesses have to knowledge and expertise (to help with strategic and operational development), finance and investment capital (to help drive investment, scaling, and growth), and access to networks of peers (where experiences can be shared, business relationships built, and collaborations taken forward). Enabling Domain 4: Ideas and Innovation 2.14 The fourth enabling domain recognises that, increasingly, UK businesses must compete on the basis of content and quality, not simply price alone where lower cost locations will always have the ‘whip hand’. Accordingly, this domain recognises the critical necessity of the generation, commercialisation, and spinning-out of new ideas, approaches, and knowledge (from both academia and/or established larger businesses), which firms in the ecosystem can embrace and deploy to improve the innovation and content of their own products. A strong flow of ideas and innovation is critical to the performance of any competitive ecosystem. Finally, Enabling Domain 5: People, Skills, and Inclusion 2.15 This final domain recognises the importance of talents, skills, and opportunity in the functioning of a resilient and high-performance ecosystem. Without workers with the right qualifications, talents and mindsets, business cannot grow and expand. By the same token, without economic growth and expansion, people and their communities cannot benefit from the employment and learning opportunities that inclusive growth can deliver into the ecosystem. 3. Defining metrics for NUTS1 regions’ digital economy ecosystems 2.16 Following the Rapid Evidence Review and collective agreement on the resulting five enabling domains driving the digital ecosystem, work was undertaken to agree metrics and indicators for the domains in the framework. These indicators could then be used to drive assessment dashboards of the digital ecosystems presenting in each of the 12 UK NUTS1 regions. 2.17 The principles used to select for metrics for the five enabling domains were as follows: • Data sources should be public where possible, giving the greatest transparency and the optimum flexibility for future updates; • Data sources should be sufficiently recent to give meaningful results, ideally updated within the last two-to-three years, and with historic data available for trend analysis; • Full UK geographic coverage at the NUTS1, NUTS2 and NUTS3 levels was sought where possible, so that data analyses could be built up and disaggregated, although inevitably there were some coverage gaps; and • In general, metrics were sought which permitted comparison between regions of different sizes – therefore, percentages or ratios were preferred over absolute numbers, although the latter also needed to be included to some Department for Digital, Culture, Media & Sport: Assessing the UK’s Regional Digital Ecosystems | A Final Report 16 September 2021 | 10 extent because of their importance for identifying ‘threshold effects’ and measurements of ‘critical mass’. 2.18 In progressing this activity: • Steer-ED Undertook a detailed review of relevant publicly available data sets from sources such as ONS, NOMIS, Ofcom, HESA, and similar; • For each dataset, data availability, frequency of update, level of sector disaggregation and geographical coverage were probed to ensure indicators were meeting the principles above. The frequency of update meant that many of the indicators in the national Census could not be shortlisted; and • Where publicly available data were limited or lacking, for example numbers and locations of high-growth companies, and details of occupation types being advertised, Steer-ED worked to access databases provided by used Beauhurst, Tech Nation and Geek Talent (the latter being a subcontractor to the Steer-ED team for this purpose). 2.19 The metrics were grouped by the appropriate enabling domain they help to characterise, and are set out in Table 2-1. These are the metrics which drive the UK NUTS1 Summary Dashboards presented at Section 4. Table 2-1: Final list of metrics used to characterise enabling domains of regional digital ecosystems Enabling Domain Metric Digital Tech Businesses, Employment & GVA • Digital sector % share of total enterprises • Digital sector % share of employees • Digital occupations % share of employment • Digital sector % share of enterprise births • Average annual growth in digital sector employees (% p.a.) • Average growth in digital occupations over 5 years (% p.a.) • Digital sector % share of GVA • Average real growth in digital sector GVA - 5 years (% p.a.) • Digital sector GVA per hour worked (£/hour) • Balance of international trade in digital sector services as % of GVA Place, Infrastructure & Assets • Earnings p.a. as % of house prices • Average business floorspace per £1k rateable value (sq. m) • Superfast broadband coverage (% of premises) • Full fibre coverage (% of premises) • Gigabit-capable coverage (% of premises) Investment & Business Environment • 3yr survival rate of digital sector firms (%) • % of digital sector firms identified as 'high growth' • Digital sector firms raising Angel Network funds • VC investment in digital sector firms per capita (£) Ideas & Innovation • Computer Science FTEs in REF2014 • Average % Computer Science research rated 4* in REF2014 • Digital sector R&D tax credit expenditure per enterprise (£k pa) • Innovate UK grants in "AI & Data Economy" sector (£m) • Digital sector university spin-outs per 1m pop • HE postgrad computing students per 1k pop Department for Digital, Culture, Media & Sport: Assessing the UK’s Regional Digital Ecosystems | A Final Report 16 September 2021 | 11 Enabling Domain Metric People, Skills & Inclusion • Digital sector median gross annual pay (£k) • Median gross annual pay for IT and telecoms professionals (£k) • Proportion of people aged 16-64 with NVQ4+ (%) • Proportion of people aged 16+ using the internet (%) • Proportion of households with internet access (%) • Proportion of internet users finding info online for work/study (%) • % of first degree graduates that remain in the region • Higher Education computing students per 1k pop Source: Steer-ED, 2021 Department for Digital, Culture, Media & Sport: Assessing the UK’s Regional Digital Ecosystems | A Final Report 16 September 2021 | 12 4. Visualisation Approach for Comparing Areas 2.20 Under this activity, the metrics presented in Table 2-1 were collated in a single Excel workbook containing information at the NUTS1, 2 and 3 levels. The spreadsheet tool enables rapid comparison between NUTS1, 2 and 3 regions on a standardised scale, so that variations between regions can easily be identified and investigated further. 2.21 The tool produced a series of ‘box plot’ style outputs positioning the selected NUTS area relative to all other UK NUTS geographies at that level. Figure 2-3 provides a snapshot of how the box-plot was visualised. Figure 2-3: Example of the visualisation of the metrics provided by the Indicator Tool Spreadsheet Source: Steer-ED, 2021 2.22 Figure 2-3 shows where a chosen area within the NUTS1, 2 or 3 area sits relative to all the other areas in its NUTS’ category. The scales are normalised across the indicators, so that it is easier to understand a place’s relative performance against other areas in the NUTS geographies. 2.23 The median score for each indicator is represented by the red line and is shown consistently in the middle of the chart. The horizontal bars display data in quartiles; the first quartile of scores (light blue), the second quartile (dark blue to the left of the median), third quartile (dark blue to the right of the median), and fourth quartile (light blue). Lastly, the black dot indicates where the chosen area within a particular NUTS geography sits in relation to all the other UK areas at that level of geography. This helps to give a perspective on an area’s performance with metrics where there may be extreme outliers. 2.24 For ease of interpretation, the metrics were organised such that the lowest performing geography is consistently on the left of the chart, with highest performance to the right. Department for Digital, Culture, Media & Sport: Assessing the UK’s Regional Digital Ecosystems | A Final Report 16 September 2021 | 13 2.25 Additional graphical representations of data are used throughout this report to highlight movements, trends, and geographical distributions, where appropriate. 5. Stakeholder Roundtable Discussions 2.26 To complement the data analysis and gather qualitative insights, a series of NUTS1 region roundtable discussions were held with stakeholders. In total, 12 stakeholder roundtable discussions were held with the three nations of Northern Ireland, Scotland, and Wales, and the nine English regions. 2.27 Drawing on DCMS’, TechNation’s, and Steer-ED’s national/regional contacts, these took in a total of more than 160 people, with stakeholders drawn from the following broad groups: • Accelerators; • Businesses; • Local government authorities; • Skills providers; and • Universities; 2.28 The roundtable discussions were delivered virtually, using MS Teams, with each session led by a pair of Steer-ED consultants. These roundtable discussions had a broad mix of stakeholders, and provided very helpful qualitative insights into the local digital ecosystems. It should be noted, though, that it was not feasible for every relevant stakeholder organisation to be represented, so there will inevitably be some aspects of the local digital ecosystems which will not have been covered in the discussions. 2.29 It was not possible, given the number of variables in play, for roundtable discussions to be structured as robust and statistically representative samples of the stakeholder populations of their nation or region. As such, the sampling approach was purposive and pragmatic; given the numbers involved, formal allowance for bias arising from non-response to the invitation to participate in the roundtable discussion could not be undertaken. 2.30 The main purpose of the roundtable discussions was to explore the study’s emerging data set, and share quantitative insight on the performance of the digital ecosystem in the NUTS1 region in view. The roundtable discussions focused on the following areas of discussion: • ‘The Past’ - The digital economy’s success stories, challenges and supporting factors relating to the NUTS1 region, up until this point; • ‘The Present’- a discussion of what the current factors enabling the digital ecosystem in the relative NUTS1 region; and • ‘Future Opportunities’ – what is needed to spur future growth of the digital ecosystem and economy across the NUTS1 region, and how this might be advanced for the future. 2.31 Findings from the roundtable discussions were collated and synthesised, and were then used to supplement the metrics data captured at the level of the five enabling domains of the ecosystem, providing a comprehensive assessment of Department for Digital, Culture, Media & Sport: Assessing the UK’s Regional Digital Ecosystems | A Final Report 16 September 2021 | 14 each NUTS1 region’s strengths, weaknesses, opportunities, and challenges. These are presented as Summary Assessments at Section 4. Assembly of database of accelerators, incubators, and wider assets 2.32 The penultimate activity involved assembling a database of accelerators, incubators, and wider assets in support of the digital economy, grouped by NUTS1 region. These data were drawn from a range of sources, including the following: • Business incubators and accelerators: the national picture22 • The Beauhurst Data Platform23; • 153 Business incubators for UK for start-ups and entrepreneurs24; • The Complete List of Unicorn Companies25; • The Higher Education Statistics Agency26, drawing-down data on all UK universities delivering Computer Studies courses; • References made to accelerators, incubators or wider assets made in the stakeholder roundtable discussions (at activity ‘5’ above) • Steer-ED’s wider professional knowledge of science and technology assets at regional level. 2.33 Following assembly, these data were screened and de-duplicated. These data were subsequently used to provide insights into the provision of accelerators, incubators, and wider enabling assets at the level of each of the UK’s NUTS1 regions. Indicative projections of future growth for NUTS1 regions 2.34 Detailed modelling of future growth in the digital economy’s GVA and employment was beyond the scope of this study. However, Steer-ED did provide indicative estimates of the extent to which each NUTS1 region’s digital sector could increase by 2025, and these are included in the ‘Achieving Prosperity’ section for each of the NUTS1 Summary Dashboards in Section 4. 2.35 Steer-ED’s indicative estimates were derived as follows: • The focus of estimation was on the two sub-sectors which have shown a clear pattern of growth in GVA over the last few years (both at the UK level and at the regional level): ‘Computer programming and consultancy’ (SIC division 62) 22 Business incubators and accelerators: the national picture - GOV.UK (www.gov.uk) 23 Beauhurst 24 153 Business incubators for UK for startups & entrepreneurs, 2021, Entrepreneur Handbook 25 The Complete List Of Unicorn Companies, CB Insights 26 HESA Department for Digital, Culture, Media & Sport: Assessing the UK’s Regional Digital Ecosystems | A Final Report 16 September 2021 | 15 and ‘Information service activities’ (SIC division 63). For the purposes of indicative estimates, it was assumed that these software- and data-intensive sub-sectors will be the primary drivers of regional growth in the digital sector27; • Combining ONS’ regional GVA data for these sub-sectors up to the year 2019, growth rates were assumed for 2020 in line with the region’s annual average for the period 2014 to 2019 (these varied from 5.1% p.a. in the South West to 13.9% p.a. in Northern Ireland). It was then assumed that each region’s annual growth in these combined sub-sectors’ GVA could converge to 8.5% p.a. by 2025 (this being the UK average for the period 2014 to 2019), with a linear interpolation being used to calculate annual GVA growth rates for the years between 2020 and 2025; and • The associated employment uplifts by 2025 were estimated by dividing the region’s GVA uplift by the region’s GVA per employee for these combined sub-sectors (averaged over the period 2015 to 2019). Limitations 2.36 Data availability was a key limitation for this study. Overall, data were collated at NUTS3 level wherever possible. Where different geographic boundaries were used in a dataset (for example, for data which is released by local authority or postcodes), these were aggregated and organised appropriately to the NUTS3 level. NUTS2 and NUTS1 data were also collected where possible, or where NUTS3 data was not available for the metric or geography. The availability of like-for-like data on school-level qualifications was also limited due differences in the education systems across the four nations. 2.37 Some metrics had more extensive time-series coverage than others (both in frequency of measurement and overall time covered), which makes comparison between some metrics challenging. 2.38 SIC Code classifications have limitations, because they are rigid and may only partially account for emerging sectors, such as Fintech, EdTech etc. To account for this, Steer-ED used additional sources, such as Beauhurst’s tracked growth business database and data from Geek Talent, which classifies sectors and occupations in ways which fit more closely to emerging sectors and roles. However, these data were not available for all metrics. 2.39 Overall, the metrics give good insight into national/regional digital ecosystems in the UK, but the data availability and time period limitations must be considered when assessing the Summary Assessments in Section 4. 27 In London, the GVA of the ‘Motion picture, video and TV programme production’ (SIC division 59) sub- sector has also been growing strongly, but this pattern is not common across the regions. Department for Digital, Culture, Media & Sport: Assessing the UK’s Regional Digital Ecosystems | A Final Report 16 September 2021 | 16 Purpose 3.1 This Section presents a brief contextual summary of the UK’s digital economy to illustrate its importance to the UK’s long-term growth and competitiveness. The Digital Sector 3.2 The digital sector28 represents a substantial share of the UK economy. It employed around 1.66 million people in 2020, accounting for 4.9% of all employment. In terms of Gross Value Added (GVA), the sector contributed £151 billion to the UK economy in 201929, which was 7.6% of the UK total. In its economic contribution, the digital sector is therefore larger than, for example, the construction sector (£130 billion) or the financial services sector (£126 billion)30. 3.3 Furthermore, the digital sector is rapidly growing, as shown in Figure 3-1. Since 2010, its GVA has grown by 26.5% in real terms, compared to total UK GVA growth of 17.7%. 3.4 The primary driver of this growth, especially over the last five years, has been ‘Computer programming, consultancy and related activities’, which is also the largest sub-sector, as shown in Figure 3-2. 3.5 In terms of the spatial distribution of digital sector activity, Figure 3-3 illustrates the digital sector’s share of total employees by NUTS3 area. The sector’s average share of employees ranges from 2.1% in Wales to 8.4% in London, and its share of GVA ranges from 3.4% in Wales to 12.3% in London (see the Summary Dashboards in Section 3 for further information on these metrics). 28 The ‘digital sector’ refers to those businesses in digital industries, based on Standard Industrial Classification definitions. ‘Digital occupations’ refers to digital job roles, in whatever industry, based on Standard Occupational Classification definitions. See Figure 2-1 for further information on the definitions of the ‘digital sector’ and ‘digital occupations’ used for this report. 29 DCMS Sectors Economic Estimates 2019 (provisional): Gross Value Added 30 Regional Gross Value Added (balanced) by industry (ONS), 2021 3 The Digital Economy in a UK Context Department for Digital, Culture, Media & Sport: Assessing the UK’s Regional Digital Ecosystems | A Final Report 16 September 2021 | 17 Figure 3-1: Indexed GVA for the digital sector, and for the UK Source: DCMS Sectors Economic Estimates31 Figure 3-2: Digital sector GVA by sub-sector, since 2010 Source: DCMS Sectors Economic Estimates 31 2019 GVA figures here and throughout the report are provisional 90 95 100 105 110 115 120 125 130 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Indexed GVA in constant prices (2010=100)Digital Sector UK 0 10 20 30 40 50 60 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 GVA (£bn, 2018 prices)Manufacturing of electronics and computers Wholesale of computers and electronics Publishing (excluding translation and interpretation activities) Software publishing Film, TV, video, radio and music Telecoms Computer programming, consultancy and related activities Information service activities Repair of computers and communication equipment Department for Digital, Culture, Media & Sport: Assessing the UK’s Regional Digital Ecosystems | A Final Report 16 September 2021 | 18 Figure 3-3: Digital sector share of employees by NUTS3 region, 2019 Sources: ONS Business Register and Employment Survey and Northern Ireland BRES Digital Occupations 3.6 There were 1.63 million people in digital occupations32 in the UK in 2019. Since 2010, employment in digital occupations has increased by 53%, far outstripping the overall UK employment growth of 12%. This shows how important the digital economy is to the prosperity and economic outlook of the UK. 32 Telecommunications engineers, IT engineers, IT Technicians, IT & telecommunications directors, and IT & Telecommunication Professionals Department for Digital, Culture, Media & Sport: Assessing the UK’s Regional Digital Ecosystems | A Final Report 16 September 2021 | 19 Figure 3-4: Indexed employment in digital occupations and all occupations, since 2010 Source: ONS Annual Population Survey 3.7 The vast majority (80%) of this growth has been in IT & telecommunications professional occupations, such as programmers, web designers and IT business analysts (Figure 3-5). Figure 3-5: Number of UK digital occupations, by occupation category since 2010 (legend includes the specific SOC codes) Source: ONS Annual Population Survey 90 100 110 120 130 140 150 160 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 Indexed number of people in employment (2010=100)Digital occupations All occupations 0 200,000 400,000 600,000 800,000 1,000,000 1,200,000 1,400,000 1,600,000 1,800,000 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 People in employment5245 IT engineers 5242 Telecommunications engineers 313 Information Technology Technicians 213 Information Technology and Telecommunications Professionals 1136 Information technology and telecommunications directors Department for Digital, Culture, Media & Sport: Assessing the UK’s Regional Digital Ecosystems | A Final Report 16 September 2021 | 20 3.8 The geographic distribution of digital occupations is more evenly spread than digital sector employment, ranging from 3.0% of all employment in Wales, to 7.2% in London. This more even distribution reflects the fact that all sectors of the economy require digitally-skilled people, and the UK’s geographic distribution of all economic activity is less skewed towards London and the South East than that of the digital sector. Over the last five years, the growth in digital occupations has been particularly strong in Northern Ireland (57%), and least rapid in the South East region (9%). Table 3-1: Total digital occupations and occupations growth by nation and region, 2020 NUTS1 region or nation Total digital occupations 2020 Digital occupations share of all employment Digital occupation growth 2015-2020 East of England 161,200 5.2% 21% East Midlands 98,600 4.2% 13% London 340,700 7.2% 34% North East 44,200 3.7% 36% North West 146,800 4.3% 22% Northern Ireland 33,200 3.9% 57% Scotland 111,100 4.2% 34% South East 295,900 6.4% 9% South West 129,700 4.7% 25% Wales 43,000 3.0% 29% West Midlands 123,400 4.5% 40% Yorkshire and The Humber 106,200 4.1% 38% Source: ONS Annual Population Survey Regional Digital Ecosystems 3.9 As seen above, there are currently wide disparities in the extent to which the digital economy is contributing to the prosperity of the UK’s nations and regions, and there are also considerable differences in growth rates. 3.10 The adoption of digital technologies across all industry sectors and markets is increasing, and will continue to transform the way people, businesses and places work in the UK, making a critical contribution to innovation and productivity growth33. 33 See, for example, Information and communication technology intensity and productivity, ONS, 2018 Department for Digital, Culture, Media & Sport: Assessing the UK’s Regional Digital Ecosystems | A Final Report 16 September 2021 | 21 3.11 Improving digital skills capability is a major focus for regional stakeholders. Key findings from a recent evaluation34 of the DCMS-funded Local Digital Skills Partnerships show that when there is greater collaboration, and joined-up activity between regional stakeholders, national organisations and central government, digital skills interventions are more impactful. 3.12 Furthermore, as a sector, digital is also one of our most promising growth areas, and it is one in which the UK has a competitive international position35. 3.13 If the UK is to maximise the benefits of the digital economy – both as a driver of productivity growth and as a substantial and fast-growing contributor to jobs and economic output in its own right - it is increasingly important that these benefits are extended more fully across the country. This requires concerted and ambitious development of the digital ecosystems in every part of the UK, building on existing strengths and addressing the key barriers to progress. 34 The Local Digital Skills Partnership evaluation report is due to be published in the Autumn 2021 35 For information on the UK’s international position see, for example, the UK Tech Competitiveness Study Department for Digital, Culture, Media & Sport: Assessing the UK’s Regional Digital Ecosystems | A Final Report 16 September 2021 | 22 4.1 With the study background, approach and methodology, and wider context established, this Section presents ‘Summary Dashboards’ characterising the present status of the digital economy ecosystem in each of the 12 UK NUTS1 regions. 4.2 To aid readability and consistency, each Dashboard is structured with six logical parts: • The first provides a positioning overview of the NUTS1 region in view, setting out headline statistics for the region, a summary of the economy overall (including GVA growth) and the size of the digital economy in particular, and a perspective on the demand for digital economy occupations. − Data driving this part of the dashboard are drawn from ONS’ Regional GVA tables, the Business Register and Employment Survey (BRES)36, the Annual Population Survey and specially-commissioned data from Geek Talent37; • The second part then provides information on how the region in view performs against the identified metrics for each of the five enabling domains being used to characterise the digital ecosystem (see Table 2-1). These data are presented in tabular form with a ‘box plot’ chart, with the latter enabling specialisms and weaknesses to be identified easily. − The data driving this section of the dashboard are drawn from an extensive list of sources, fully reported in Appendix B. • Part Three then focuses on the digital economy’s spatial distribution within and across the region in view. Maps present digital economy employment, digital sector assets (including incubators, accelerators and such), and digital 36 The totals for digital sector employment and digital occupations in the year 2019 have been sourced via NOMIS from the Business Register & Employment Survey and the Annual Population Survey respectively. In the absence of sufficiently detailed recent data on the overlap between these two, an assumption has been used that 42% of the digital sector employment is in digital occupations – drawn from an analysis of the detailed occupations by industry data available from the England & Wales Census 2011 37 Location quotients (LQ) have been used on some of this data to draw out regional differentiation more clearly (for example, on occupations data, the LQ is calculated by the following process: an occupation’s share of total ads in the region divided by this occupation’s share of total ads in the UK). The UK average is, therefore 1.0. Only the top 10 occupations by job adverts are shown here, ranked by LQ. 4 Summary Dashboards Department for Digital, Culture, Media & Sport: Assessing the UK’s Regional Digital Ecosystems | A Final Report 16 September 2021 | 23 sector high-growth businesses to help identify clusters of activity and potential in the region. − Data driving this part of the dashboard are drawn from the BRES, Beauhurst’s Leading High-Growth Platform38, stakeholder roundtable discussions held with regional partners, and the database assembled by the study on digital economy relevant accelerators, incubators, and wider assets; • Part Four moves on to provide perspectives on sub-regional potential, disaggregating the overall NUTS1 position down to NUTS2 and 3 levels to show the relative output (GVA) of the digital sector. This material highlights where the region’s NUTS2 and NUTS3 regions are in relation to the top and bottom performers in the UK. Charts provided include the five-year (2014- 2019) growth rate for the digital sector’s GVA, Higher Education Computing Students per 100k population, and VC investment per capita. − The data driving this section of the dashboard are drawn from an extensive list of sources, which are fully reported in Appendix B. • Part Five focus on the area’s digital economy potential and high-growth business specialisms, providing an analysis of growth potential, looking at the annual GVA output (over the 2010-2019 period) produced by digital sector sub-sectors. This Part also includes two ‘Word Clouds’ drawn from an analysis of Beauhurst’s Leading High-Growth Platform dataset, setting out the frequency of sub-sectors to which high growth forms associate themselves, and the ‘buzzwords’ used to define their services; − Data driving this part of the dashboard are drawn from ONS’s Regional GVA tables and Beauhurst’s Leading High-Growth Platform. • Finally, Part Six draws the material into a short summary, focusing on the strengths of the digital ecosystem in the region, the opportunities/specialisms that present, the barriers to be faced, and how the ‘prosperity prize’ that the digital economy potentially presents can be best achieved for the region. 4.3 Summary Dashboards are presented for 12 UK NUTS1 regions in the following order. • East Midlands; • East of England; • London; • North East; • North West; • Northern Ireland; • Scotland; • South East; 38 10% or 20% year on year growth in headcount or turnover, over a three-year period – Beauhurst/OECD definition Department for Digital, Culture, Media & Sport: Assessing the UK’s Regional Digital Ecosystems | A Final Report 16 September 2021 | 24 • South West; • Wales; • West Midlands; and • Yorkshire and The Humber. Department for Digital, Culture, Media & Sport: Assessing the UK’s Regional Digital Ecosystems | A Final Report 16 September 2021 | 25 East Midlands – Summary Dashboard Region • Component NUTS2 regions: Derbyshire and Nottinghamshire, Leicestershire, Rutland and Northamptonshire and Lincolnshire. • Key Statistics: 15,627km2, 4.9m population, £110bn total GVA (2019), 1.5% total annual GVA growth (2014-2019) • The East Midlands’ economic activity is concentrated in Nottingham and Leicester, but it also has main population centres in Derby, Mansfield, Lincoln, and Northampton. • This region continues to perform strongly relative to the UK in manufacturing, particularly in Food, Textiles, Leather Products, Manufacture of other Non-Metallic Mineral Products, and Wearing Apparel. • The digital sector is relatively small as a percentage of total output for the region (3.6%), but it is showing strong growth in economic output (5.7%, 2014-2019), marginally faster than the UK’s Digital Sector, and much faster than the East Midlands’ economy as a whole. • Total digital employment (estimated at 125k in 2019) is weighted towards digital occupations in businesses not traditionally in the Digital Sector; this is indicative of the high demand for digital skills in non-digital sector industries, such as Transport and Storage (which link to the region’s transport infrastructure). • Demand for digital occupations is dominated by both Derbyshire and Nottinghamshire and Leicestershire, Rutland and Northamptonshire, with 52% and 40% of the area’s digital occupation online job postings in 2019-2020, respectively. This is followed by Lincolnshire, which has a small proportion at 8%. • There is relatively high demand for Web Developers, Field Service Engineers and IT Support Analyst (location quotient above 1.0, the UK average) although the largest absolute demand for occupations is Software Developers, accounting for 25% of digital occupation job adverts in the 2019-2020 period, indicating increasing demand for innovative software and accelerating growth in technology. Digital Sector GVA growth 2010-2019 (indexed to 2010), East Midlands NUTS1 Region Source: Regional Gross Value Added, ONS Demand for Digital Occupations by NUTS2 region in the East Midlands (2019 – 2020) Digital Sector and Digital Occupation Employment (2019), East Midlands NUTS1 Region Source: Geek Talent, 2021 Source: Business Register and Employment Survey and Annual Population Survey, 2019 80 100 120 140 160 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 East Midlands digital sector East Midlands economy UK digital sector 52% 40% 8% Derbyshire and Nottinghamsh ire Leicestershire, Rutland and Northampton shire Lincolnshire Employment in digital sector: 64k Residents in digital occupations: 90k Total digital employment in East Midlands: c. 125k 16 September 2021 | 26 Concentration of demand for Digital Occupations (2019-2020), East Midlands NUTS1 Region • This table shows digital occupations by demand for the East Midlands. It displays the total number of adverts, percentage share of digital occupation adverts, and the concentration of demand against the UK average (known as the location quotient). Total demand is highest for Software Developers, Data Engineers, and IT Support Analyst, but comparative demand is highest for Web Developers, Field Service Engineers and IT Support Analysts. Broadly these in demand roles are digital occupations that are not necessarily in the digital sector. Occupation Total digital occupation adverts (2019-2020) Share of total digital occupation adverts (%) Location Quotient vs UK (1 = UK average) Web Developer 7,097 6.4% 1.46 Field Service Engineer 3,157 2.8% 1.40 IT Support Analyst 7,952 7.1% 1.39 Software Developer 27,342 24.5% 1.22 IT Service Manager 2,425 2.2% 1.21 Database Administrator 1,710 1.5% 1.20 Test Analyst 3,341 3.0% 1.11 IT Manager 5,347 4.8% 1.09 System Administrator 1,573 1.4% 1.07 Business Development Executive 1,556 1.4% 0.98 Source: Geek Talent, 2021 East Midlands - Digital Ecosystem metrics, relative to UK NUTS1 Regions • The table below presents a list of indicators arranged into the five components of a regional digital ecosystem. It shows the value for the East Midlands and how this compares to the lowest and highest NUTS1 region values, to enable assessment to be made of where the key strengths and opportunities for growth of the digital ecosystem are. The period at which the data is recorded is indicated for each indicator. • The box plot below the table indicates visually where the East Midlands (black dot) sits against the median (red line), interquartile range (deeper blue) and range (lighter blue) of the UK NUTS1 regions. Where the black dot is to the right of the median, the East Midlands is above the median value on this indicator. 16 September 2021 | 27 Indicator name Period EM Box plot comparison Lowest 25th centile Median 75th centile Highest Digital sector % share of total enterprises 2020 5.9 3.0 5.6 6.3 7.7 14.1 Digital sector % share of employees 2019 2.4 2.1 2.8 3.0 3.5 8.4 Digital occupations % share of employment 2020 4.2 3.0 4.0 4.3 4.9 7.2 Digital sector % share of enterprise births 2019 5.5 4.8 5.4 6.0 8.0 12.7 Average annual growth in digital sector employees (% p.a.) 2015-19 3.2 -2.0 0.9 2.8 6.9 8.2 Average growth in digital occupations over 5 years (% p.a.) 2015-20 2.4 1.8 4.0 5.6 6.4 9.4 Digital sector % share of GVA 2019 3.6 3.4 4.0 4.5 5.1 12.3 Average real growth in digital sector GVA - 5 years (% p.a.) 2014-19 5.7 1.8 3.3 5.6 6.6 7.6 Digital sector GVA per hour worked (£/hour) 2019 37.1 29.8 36.6 40.7 45.1 62.4 Balance of international trade in digital sector services as % of GVA 2018 0.1 0.0 0.2 0.3 1.3 3.5 Earnings p.a. as % of house prices 2020 13.8 9.3 10.1 14.6 16.9 20.3 Average business floorspace per £1k rateable value (sq. m) Mar-2020 19.2 4.1 13.4 16.8 17.9 19.2 Superfast broadband coverage (% of premises) Jan 2021 95.8 89.1 93.1 95.6 95.7 96.0 Full fibre coverage (% of premises) Jan 2021 15.1 10.5 15.8 19.5 22.3 60.7 Gigabit-capable coverage (% of premises) Jan 2021 15.1 10.5 20.6 33.0 45.0 74.8 3yr survival rate of digital sector firms (%) 2016-2019 62.7 58.2 59.9 61.8 62.4 64.9 % of digital sector firms identified as 'high growth' 2020 0.9 0.9 1.4 1.8 2.9 5.7 Digital sector firms raising Angel Network funds 2016-20 5.0 2.0 5.0 11.0 17.3 110.0 VC investment in digital sector firms per capita (£) 2016-20 5.8 5.8 18.5 44.4 132.8 1256.7 Computer Science FTEs in REF2014 2014 145.5 60.8 99.1 137.0 188.6 413.8 Average % Computer Science research rated 4* in REF2014 2014 17.1 10.0 20.7 25.1 28.2 33.4 Digital sector R&D tax credit expenditure per enterprise (£k pa) 2017/18 14.2 13.8 16.5 19.0 22.3 75.6 Innovate UK grants in "AI & Data Economy" sector (£m) 2011-20 9.0 2.3 8.7 14.5 31.2 232.7 Digital sector university spin-outs per 1m pop Apr 2021 1.2 1.1 2.7 3.8 5.2 7.3 HE postgrad computing students per 1k pop 2019/20 0.4 0.3 0.3 0.4 0.5 0.8 HE postgrad comp, eng & tech, and maths students per 1k pop 2019/20 1.2 0.7 0.9 1.2 1.4 1.7 Digital sector median gross annual pay (£k) 2020 30.2 30.2 32.6 34.9 38.8 47.4 Median gross annual pay for IT and telecoms professionals (£k) 2020 35.8 35.0 37.2 39.3 43.5 51.7 Proportion of people aged 16-64 with NVQ4+ (%) 2020 37.2 34.5 37.3 38.8 41.6 58.5 Proportion of people aged 16+ using the internet (%) 2020 91.4 88.2 90.6 91.2 92.6 95.1 Proportion of households with internet access (%) Q1 2021 92.0 89.0 92.8 94.0 95.0 97.0 Proportion of internet users finding info online for work/study (%) Q1 2020 50.0 23.0 36.8 42.5 52.3 67.0 % of first degree graduates that remain in the region 2016/17 56.9 51.7 61.1 69.9 75.7 87.8 HE computing students per 1k pop 2019/20 1.8 1.3 1.4 1.8 2.3 2.6 Source: Steer-ED and various datasets – See Appendix B 16 September 2021 | 28 East Midlands - Digital Sector’s spatial distribution Digital Sector Employment Total and, as a percentage of Total Employment by NUTS3 (2019) • The maps below show absolute digital employment and digital sector employment as a percentage of total employment by NUTS3 region. They highlight where employment is concentrated and where there are relatively large employment clusters. 16 September 2021 | 29 Digital Sector assets (2021), and density of digital sector high growth businesses (2020) • The map to the left shows the location of digital ecosystem assets in the East Midlands, including accelerators, incubators, universities with computer science courses, university spinouts, and additional research assets. It highlights the concentration of assets in urban centres with universities. • The map to the right shows the density of high growth businesses operating in the digital sector in the East Midlands. It highlights how high growth businesses are concentrated in larger urban areas. 30 of 199 East Midlands – Sub-Regional Potential Analysis of Key Metric Combinations at NUTS2 level • The charts below highlight key metrics at a NUTS2 and NUTS3 level and how they relate to the relative size of the digital sector in the East Midlands, highlighting where there is sub-NUTS1 potential for uplifting the digital sector and in turn boosting prosperity. • Each data point (blue) equates to one NUTS2 or NUTS3 region in the UK. The East Midlands are indicated in black. Key outliers outside the East Midlands are labelled to provide context. National trends are largely replicated as sub-NUTS1 regional trends in the East Midlands. Digital Sector GVA % plotted against Digital Sector GVA 5 year growth rate (2014-19) – All UK NUTS2 regions Source: Regional Gross Value Added (balanced) by industry (ONS), 2021 • The chart above shows that NUTS2 regions in London and the South East are outliers, with large relative digital sector output. Digital Sector GVA % plotted against Digital Sector GVA 5 year growth rate (2014-19) – East Midlands NUTS3 regions and UK NUTS3 outliers Source: Regional Gross Value Added (balanced) by industry (ONS), 2021 • The chart above shows how digital sector growth is corelated with the relative size of the digital sector in the East Midlands’ NUTS3 regions. It plots these against outlier NUTS3 regions from the rest of the UK. Tees Valley and Durham Cumbria Inner London - West Inner London - East Outer London - West and North West Berkshire, Buckinghamshire and Oxfordshire Eastern Scotland Derbyshire and Nottinghamshire Leicestershire, Rutland and Northamptonshire Lincolnshire 0 2 4 6 8 10 12 14 16 -4 -2 0 2 4 6 8 10 12 Digital Sector % share of GVAAverage real growth in Digital Sector GVA - 5 years (% p.a.) Derby East Derbyshire South and West Derbyshire Nottingham North Nottinghamshire South Nottinghamshire Leicester Leicestershire CC and Rutland West Northamptonshire North Northamptonshire Lincolnshire Solihull Hounslow and Richmond upon Thames Mid and East Antrim 0 5 10 15 20 25 30 -15 -10 -5 0 5 10 15 20 25 Digital Sector % share of GVAAverage real growth in Digital Sector GVA - 5 years (% p.a.) 31 of 199 Digital Sector GVA % plotted against HE Computing Students per 100k population (NUTS2 regions) Source: HESA, 2019 Regional gross value added (balanced) by industry (ONS), 2021 • The chart above shows there is a slight positive trend between the number of higher education computer students and the relative size of the digital sector. Digital Sector GVA % plotted against VC investment per capita (2016-2020). Inner London East and West excluded as large outliers (NUTS2 regions) Source: Beauhurst, 2021 and Regional Gross Value Added (balanced) by industry: all NUTS level regions, 2021 • The chart above shows there is a positive trend between the amount of VC investment per capita and the relative size of the digital sector at a NUTS2 level. Cumbria Inner London - West Derbyshire and Nottinghamshire Leicestershire, Rutland and Northamptonshire Lincolnshire 0 2 4 6 8 10 12 14 16 0 100 200 300 400 500 600 700 Digital Sector % share of GVAComputer Science per 100K population Cumbria Berkshire, Buckinghamshire and Oxfordshire Derbyshire and Nottinghamshire Leicestershire, Rutland and Northamptonshire Lincolnshire 0 2 4 6 8 10 12 14 16 0 50 100 150 200 250 300 350 400 Digital Sector % share of GVAValue of VC investment in digital sector firms (£ per capita 2016-20) 32 of 199 East Midlands – Potential and High Growth Business Specialisms Growth Potential • To understand the growth potential of the East Midlands, it is important to understand what is driving growth. The chart below plots the annual GVA output from six sub-sectors of the digital sector from 2010-2019. Annual GVA output from Digital Sector sub-sectors (2010-2019) Source: Regional Gross Value Added (balanced) by industry (ONS), 2021 • The chart above shows that there has been significant growth in Computer programming and consultancy (CAGR of 6.6%), it is also the largest sub-sector. Information service activities has grown steadily since 2010, and most recently, since 2017, at a fast pace. The sector grew at a CAGR of 8.09% between 2014-2019. These sub-sectors are where the growth potential for the East Midlands lies. High Growth businesses and specialisms • Activities of high growth digital sector businesses help to identify in more detail the specific market areas in which the East Midlands’ potential for further economic growth lie. There were 99 high growth businesses in the digital sector in the East Midlands as at 2021, equating to 0.9% of the total number of digital sector businesses in the NUTS1 region. • The specialisms which these high growth businesses operate in are tracked by Beauhurst. The word clouds below show the most common sub-sectors (as defined by Beauhurst) which East Midlands high growth firms operate in, and “buzzwords” that relate to their business operations. It shows significant expertise in providing software as a service, the development of mobile apps, internet platforms, analytics insight tools, with specialisms in Artificial Intelligence, eHealth, FinTech and Wearables. Word Cloud showing the frequency of high growth digital sector business sectors, as defined by Beauhurst World Cloud showing the frequency of high growth digital sector business buzzwords, as defined by Beauhurst Source: Beauhurst, 2021 0 500 1,000 1,500 2,000 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 GVA (£m, 2018 prices)Publishing activities Motion picture, video and TV programme production Programming and broadcasting activities Telecommunications Computer programming and consultancy Information service activities 33 of 199 East Midlands Digital Ecosystem in Summary Strengths • In recent years, the East Midlands has grown above the median in terms of both digital sector employees (3.2% per annum) and digital sector GVA (5.7% per annum). • These regional averages do not do justice, however, to the two East Midlands cities in which the digital sector is particularly strong. Nottingham features in the top quartile of UK NUTS3 areas for the digital sector share of employees (5.1%), recent growth in digital sector employees (5.7% per annum) and recent growth in digital sector GVA (8.7% per annum). Leicester is in the top quartile of NUTS3 areas for recent growth in digital sector employees (6.5% per annum) and recent growth in digital sector GVA (15.6% per annum). • Such growth has reflected the region’s success in recently attracting large employers (e.g. IBM’s Client Innovation Centre at Leicester), as well as the development of substantial home-grown digital businesses such as Experian, UNiDAYS (online student community), Lockwood Publishing (mobile games), and ENSEK (energy sector software). • Vibrant tech communities have been established over the last ten years, particularly in Nottingham (Tech Nottingham) and Leicester (Create Leicester and Leicester Tech Startups). Tech Nottingham is the largest of these, and now has around 3,000 members. By providing networking and collaboration opportunities these grassroots organisations have strengthened the connections within the East Midlands tech community, making it much easier to seek advice and support from peers. • Survival rates for digital sector businesses are relatively high in the East Midlands: 63% of such firms survive into their third year, which is in the top quartile of UK regions for this metric. • Although the region appears to have a relatively low average performance in REF2014 in terms of the proportion of computer science and informatics research judged to be world-class (at 17%), this regional average again hides a strong centre of excellence in the University of Nottingham, which had 37% of its submitted research in this area judged to be 4*. Through its Horizon Digital Economy Research Institute, the University has funded four cohorts (15 years) of PhDs and has helped position Nottingham and the East Midlands in digital research, particularly in data privacy and ethics. The Ingenuity Programme hosted by the University of Nottingham is an example of the University’s support for entrepreneurship and the creation of impact-led businesses. Opportunities/Specialisms • Amongst the region’s 99 digital sector companies identified as high growth, prominent sub-sectors include Software-as-a- Service (31% of firms), mobile apps (24% of firms), analytics, insight, tools (15%) and internet platform (14%). In the ‘buzzword’ analysis of these firms’ activities, the most common tagged specialisms are Artificial Intelligence (8% of firms), FinTech (6%), wearables (5%), and eHealth (5%). • The East Midlands has a diverse range of digital businesses. However, there are some cluster specialisms, for example in Health Tech in Nottingham (e.g. Imosphere, Pharmaseal, Boditrax), Agri-Tech in Lincolnshire (supported by the University of Lincoln’s Institute for Agri-food Technology), and Creative Tech in Leicester (e.g. Anicca, Bulb Studios, Herdl). • With the COVID-19 lockdowns, the East Midlands has seen a number of digital professionals re-locating to the region from London, while still working remotely for London-based firms – considering it to offer better housing affordability and a higher quality of life. This presents an opportunity to integrate these (often highly skilled) people into the East Midlands tech community, sharing contacts and expertise, and potentially creating a wider base of experienced digital professionals from which East Midlands tech businesses can recruit. Barriers to Growth • Access to talent is a pressing concern and is a critical constraint on the growth of the region’s digital ecosystem. • The East Midlands currently has the second lowest median gross annual pay in the digital sector of all UK regions (£30.2k), and also appears in the lowest quartile for median gross annual pay of IT and telecoms professionals (£35.8k). This is likely to be a contributory factor to the difficulties in attracting and retaining digital talent and reflects the fact that the digital sector as yet only accounts for a relatively modest – albeit growing – share of the region’s economy (3.6% of GVA). • More widely, the East Midlands is also in the lowest quartile for the proportion of working age people with any degree-level qualifications (37%). • The numbers of active East Midlands-based digital sector spinouts from universities currently appears to be low, according to the data tracked by Beauhurst: 1.2 per million population, which is in the lowest quartile of UK regions. Of more concern, however, is that the broader R&D intensity of digital sector firms in the East Midlands is relatively low: with an average digital sector R&D tax credit expenditure of £14.2k per annum per enterprise, this is in the bottom quartile of UK regions. • Looking at international trade data, the East Midlands’ balance of trade in digital sector services as a proportion of GVA is +0.1%, which is below the 25th percentile of +0.2% and well behind the West Midlands (+1.4%) and London (+3.5%). • Issues of digital poverty have been brought into sharp focus by the COVID-19 lockdowns, and where households lack access to sufficient devices and/or connectivity this constrains the extent to which children and adults can access education and training resources. This presents very practical barriers to people from more disadvantaged households acquiring new digital skills and developing an interest in the area (reported by programme managers to have been a 34 of 199 problem in some of the region’s European Structural Fund, ESF, funded skills-development programmes). The region currently appears in the bottom quartile for the proportion of households with internet access (92% having internet access). • Digital connectivity is also still a problem in some parts of the region. Though there is now a very high coverage of superfast broadband (96%), the East Midlands is currently in the lowest quartile for full fibre and gigabit-capable coverage. • Relatively little external capital is being invested in the region’s digital sector, and this presents a further barrier to maximising its growth potential. Normalised to the population size, the East Midlands has had the least venture capital funding into its digital sector of any UK region over recent years (in the period 2016 to 2020, funds raised by East Midlands digital companies amounted to just 0.2% of the UK total, according to Beauhurst data, compared to the region’s UK population share of 7%). Achieving Prosperity • On the basis of Steer-ED’s indicative modelling (see Section 2), the digital sector in the East Midlands has the potential to grow by at least £1.5 billion in annual GVA by 2025 (an increase of 38% on the 2019 value), creating an additional 36,500 jobs (an increase of 49% on the employment in 2019). • Recent growth in the region’s digital economy has largely been down to the software and data-intensive Computer Programming and Consultancy and Information Services segments. These are vital bedrock sectors for the region, going forward, work is needed to both consolidate the good progress made and accelerate and extend this. • In realising the ‘prosperity prize’, there are constraints on the availability of funding, especially around Angel and venture finance, which are both necessary to lubricate the virtuous circle of start-up and scaling. Availability of talent is also an issue, in terms of both volume and experience. These constraints must be tackled if the full economic potential of the region's digital economy is to be realised. • Whilst focusing on the above issues is key to enabling prosperity, the region can look already to the digital economies in Nottingham and Leicester to see what can be achieved in a relatively short space of time. 35 of 199 East of England – Summary Dashboard Region • Component NUTS2 regions: East Anglia (Norfolk, Suffolk & Cambridgeshire), Bedfordshire and Hertfordshire, and Essex. • Key Statistics: 19,120km2, 6.3m population, £165bn total GVA (2019), 2% total annual GVA growth (2014-2019). • The East of England is a region of low-lying counties featuring many rural and coastal towns, many of which have low population densities. The main population centre for the East of England is Essex. • This region performs strongly, relative to the UK, in Agriculture, Manufacturing, Construction, and Civil Engineering. • The Digital Sector accounts for a significant percentage of total output for the region (5.1%), and the regional sector is comparatively larger in terms of economic output than for the UK as a whole. The growth of economic output from the digital sector (3%, 2014-2019) is slower than the UK’s Digital Sector, but faster than the regional economy as a whole. • Digital employment (estimated at 235k in 2019) is weighted towards digital occupations in businesses not traditionally in the digital sector. This is indicative of the high demand for digital skills in non-digital sector industries such as Recruitment, Retail, Technology, Construction, Pharmaceuticals/Life Sciences. • Demand for digital occupations is highest in East Anglia, which includes Cambridgeshire (46% of digital occupation online job postings 2019-2020), followed by Bedfordshire and Hertfordshire (37%) and then Essex (17%). • There is relatively high demand for Software Engineers, Field Service Engineers and System Administrators (location quotient above 1.0, the UK average), although the largest absolute demand for occupations is Software Developers, making up 19% of digital occupation job adverts 2019-2020. Digital Sector GVA growth 2010-2019 (indexed to 2010), East of England NUTS1 Region Source: Regional Gross Value Added, ONS Demand for Digital Occupations by NUTS2 region in the East of England (2019 – 2020) Digital Sector and Digital Occupation Employment (2019), East of England NUTS1 Region Source: Geek Talent, 2021 Source: Business Register and Employment Survey and Annual Population Survey, 2019 80 100 120 140 160 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 East of England Digital Sector East of England Economy UK digital sector 46% 37% 17% East Anglia Bedfordshire and Hertfordshire Essex Employment in the Digital Sector: 130k Residents in Digital Occupations: 161k Total digital employment in the East of England: c. 235k 36 of 199 Concentration of demand for Digital Occupations (2019-2020), East of England NUTS1 Region • This table shows digital occupations by demand for the East of England. It displays the total number of adverts, percentage share of digital occupation adverts, and the concentration of demand against the UK average (known as the location quotient). Total demand is highest for Software Developers and Data Engineers, but comparative demand is highest for Embedded Software Engineers, Field Service Engineers and System Administrators. Broadly these in demand roles are digital occupations that are not necessarily in the digital sector. Occupation Total digital occupation adverts (2019-2020) Share of total digital occupation adverts (%) Location Quotient vs UK (1 = UK average) Embedded Software Engineer 13,390 7.5% 1.55 Field Service Engineer 5,421 3.0% 1.49 System Administrator 3,079 1.7% 1.30 IT Support Analyst 11,412 6.4% 1.25 Network Engineer 4,397 2.5% 1.14 IT Manager 8,728 4.9% 1.11 Test Automation Engineer 3,241 1.8% 1.11 Data Engineer 18,641 10.4% 1.07 IT Service Manager 3,380 1.9% 1.05 Web Developer 7,850 4.4% 1.01 Source: Geek Talent, 2021 East of England - Digital Ecosystem metrics, relative to UK NUTS1 Regions • The table below presents a list of indicators arranged into the five components of a regional digital ecosystem. It shows the value for the East of England and how this compares to the lowest and highest NUTS1 region values, to enable assessment to be made of where the key strengths and opportunities for growth of the digital ecosystem are. The period at which the data is recorded is indicated for each indicator. • The box plot below the table indicates visually where the East of England (black dot) sits against the median (red line), interquartile range (deeper blue) and range (lighter blue) of the UK NUTS1 regions. Where the black dot is to the right of the median, the East of England is above the median value on this indicator. 37 of 199 Indicator name Period EE Box plot comparison Lowest 25th centile Median 75th centile Highest Digital sector % share of total enterprises 2020 8.7 3.0 5.6 6.3 7.7 14.1 Digital sector % share of employees 2019 3.8 2.1 2.8 3.0 3.5 8.4 Digital occupations % share of employment 2020 5.2 3.0 4.0 4.3 4.9 7.2 Digital sector % share of enterprise births 2019 8.0 4.8 5.4 6.0 8.0 12.7 Average annual growth in digital sector employees (% p.a.) 2015-19 1.2 -2.0 0.9 2.8 6.9 8.2 Average growth in digital occupations over 5 years (% p.a.) 2015-20 3.9 1.8 4.0 5.6 6.4 9.4 Digital sector % share of GVA 2019 5.1 3.4 4.0 4.5 5.1 12.3 Average real growth in digital sector GVA - 5 years (% p.a.) 2014-19 3.0 1.8 3.3 5.6 6.6 7.6 Digital sector GVA per hour worked (£/hour) 2019 43.1 29.8 36.6 40.7 45.1 62.4 Balance of international trade in digital sector services as % of GVA 2018 0.7 0.0 0.2 0.3 1.3 3.5 Earnings p.a. as % of house prices 2020 9.8 9.3 10.1 14.6 16.9 20.3 Average business floorspace per £1k rateable value (sq. m) Mar-2020 13.2 4.1 13.4 16.8 17.9 19.2 Superfast broadband coverage (% of premises) Jan 2021 95.6 89.1 93.1 95.6 95.7 96.0 Full fibre coverage (% of premises) Jan 2021 14.6 10.5 15.8 19.5 22.3 60.7 Gigabit-capable coverage (% of premises) Jan 2021 15.9 10.5 20.6 33.0 45.0 74.8 3yr survival rate of digital sector firms (%) 2016-2019 63.8 58.2 59.9 61.8 62.4 64.9 % of digital sector firms identified as 'high growth' 2020 1.3 0.9 1.4 1.8 2.9 5.7 Digital sector firms raising Angel Network funds 2016-20 17.0 2.0 5.0 11.0 17.3 110.0 VC investment in digital sector firms per capita (£) 2016-20 131.0 5.8 18.5 44.4 132.8 1256.7 Computer Science FTEs in REF2014 2014 169.7 60.8 99.1 137.0 188.6 413.8 Average % Computer Science research rated 4* in REF2014 2014 25.3 10.0 20.7 25.1 28.2 33.4 Digital sector R&D tax credit expenditure per enterprise (£k pa) 2017/18 21.6 13.8 16.5 19.0 22.3 75.6 Innovate UK grants in "AI & Data Economy" sector (£m) 2011-20 60.4 2.3 8.7 14.5 31.2 232.7 Digital sector university spin-outs per 1m pop Apr 2021 4.7 1.1 2.7 3.8 5.2 7.3 HE postgrad computing students per 1k pop 2019/20 0.5 0.3 0.3 0.4 0.5 0.8 HE postgrad comp, eng & tech, and maths students per 1k pop 2019/20 1.2 0.7 0.9 1.2 1.4 1.7 Digital sector median gross annual pay (£k) 2020 39.6 30.2 32.6 34.9 38.8 47.4 Median gross annual pay for IT and telecoms professionals (£k) 2020 44.9 35.0 37.2 39.3 43.5 51.7 Proportion of people aged 16-64 with NVQ4+ (%) 2020 39.2 34.5 37.3 38.8 41.6 58.5 Proportion of people aged 16+ using the internet (%) 2020 92.3 88.2 90.6 91.2 92.6 95.1 Proportion of households with internet access (%) Q1 2021 95.0 89.0 92.8 94.0 95.0 97.0 Proportion of internet users finding info online for work/study (%) Q1 2020 52.0 23.0 36.8 42.5 52.3 67.0 % of first degree graduates that remain in the region 2016/17 51.7 51.7 61.1 69.9 75.7 87.8 Higher Education computing students per 1k pop 2019/20 1.3 1.3 1.4 1.8 2.3 2.6 Source: Steer-ED and various datasets – See Appendix B
