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

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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
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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

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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


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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
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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
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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,
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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.
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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
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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
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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.


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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
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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."


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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


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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
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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.
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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
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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
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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

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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.
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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
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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


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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.
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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
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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
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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
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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
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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


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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
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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
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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
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• South West;
• Wales;
• West Midlands; and
• Yorkshire and The Humber.
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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