Executive summary
This report on diversity in UK tech seeks to collate, deepen and examine the evidence base on diversity and inclusion that has been built up in the UK over the last decade, but most acutely, over the last eighteen months.
As well as presenting high level trends, at a national level, this report seeks to dive deep into the regional data on diversity and inclusion. This will enable new information to be used in decision making to support more inclusive practice around diversity, and a clear set of actions to be formulated at the geographical levels where they can be most effectively implemented.
In addition we have commentary from expert Diversity and Inclusion (D&I) leaders on steps people can take to improve D&I within their organisations.
Use this alongside Tech Nation's Diversity and inclusion Toolkit, which provides actionable insights and guidance to help founders build diverse and inclusive companies.
What has the pandemic meant for diversity and inclusion in the UK, what has the impact been on hiring trajectory, and what should we expect to see in UK tech with regard to diversity and inclusion over the next 12 to 24 months? This report develops our understanding, and provides an evidence base to start to answer these important questions.
Key statistics
- 50% of workers in the labour market as a whole are women, in tech, it’s half that, at 26%.
- In tech, there is an overrepresentation of people under 35 years of age, at 42% compared to 40% for the labour market as a whole.
- Tech has a marginally higher proportion of BAME people than the labour market as a whole, 11.8% for all occupations, and 15.2% for tech. However, this does not represent the UK population, where, according to the 2011 Census, 20% of people living in the UK are BAME.
- London (30.1%) and the West Midlands (17.4%) are leading for BAME representation in digital jobs
- Wales has the highest proportion of tech employees under 35 years of age, at 51%, followed by London at 48.7%, and the North East at 46.1%.
- London has the highest proportion of females working in tech, at 28.4%, just over half the proportion of the workforce more broadly. London is followed by the South East of England, with 27.7%.
- Wolverhampton and Walsall (41%), Blackpool (37%), Cambridge (35%), Milton Keynes (35%) and Merthyr Tydfil (39%) are leading for the representation of females in digital roles
- Portsmouth (11%) and Bristol (13%) are lagging in the proportion of females working in digital roles.
- Birmingham (28%), Leicester (32%) and Coventry (30%) have the highest proportion of BAME employees in digital tech roles, though data across UK clusters is patchy.
- 24% of organisations say they increased flexible work arrangements as a result of Covid-19.
- 43% of working women and 53% of working women from a non-white ethnicity worried about their jobs and promotions during the pandemic.
- 9% (206) of C-Suite leaders in tech companies analysed were female and 91% (2065) male.
- Only 3% of Chief Technology Officers (CTO’s) or Technical Director roles are held by women.
- 0.6% of Chief Operating and 0.4% of Chief Financial Officer roles are held by women.
- According to a report by Extend Ventures, within the past decade (2009 - 2019) female entrepreneurs faced barriers accessing VC investment, as shown below. Only 3% of VC funding (seed, early- and late-stage) went to all female teams. On the other hand, all male teams received 68% of VC funding.
Foreword
The report sheds new light on the composition of the diversity of employees in the tech sector across UK nations and regions, and diversity among tech leaders in C-suite roles. The findings add to the body of evidence showing that the problems exist at the top - and may well be trickling down into the workforce, alongside data from Extend Ventures on diversity and investment beyond gender. Of the tech companies for which leadership data was available we found that just 9% (206) of C-Suite leaders in tech companies were female and 81% (2065) male. Only 3% of Chief Technology Officers (CTO’s) or Technical Director roles are held by women, and just 0.6% of Chief Operating Officer and 0.4% of Chief Financial Officer roles are held by women.
This, clearly, is not good enough. The report draws on insights and advice from leaders in the field of D&I, including the Tech Talent Charter and Playfair Capital, but should also be seen alongside Tech Nation's D&I Toolkit. At Harmonic, we put purpose above profit, and work only with start-ups and scale-ups who are committed to delivering a diverse and values driven working culture. We’re subsequently delighted that this evidence provides a first step in developing a true understanding of diversity in tech, albeit it must be taken forward to create real change. We are pleased to be at the forefront of helping to understand and underpin that change alongside Tech Nation.
What is the state of diversity in UK tech?
There is a growing demand for tech roles in the UK. The tech labour market in the UK has rebounded from Covid-19. Demand for tech jobs was 42% higher in June 2021 than at the same time in 2019.
However, there is still a diversity and inclusion gap within tech companies when it comes to employees and leaders, and, a well documented lack of investment being made into underrepresented founders.
Many of the problems in addressing the diversity gap in UK tech stem from a dearth of data, and lack of robust evidence, which could lead to better placed interventions.
How does diversity vary across UK nations and regions?
These statistics, presented at a national level, can obscure important differences within UK regions and nations, and overlook nuances between groups of jobs, both within and outside of tech.
This section presents fine grained regional and city based data to allow for an exploration of the detailed data on diversity of people working in tech by age, gender and ethnicity - cutting the high level evidence down to size for informing targeted local interventions.
- London (30.1%) and the West Midlands (17.4%) are leading for BAME representation in digital jobs
- Wales has the highest proportion of tech employees under 35 years of age, at 51%, followed by London at 48.7%, and the North East at 46.1%.
- London has the highest proportion of females working in tech, at 28.4%, just over half the proportion of the workforce more broadly. London is followed by the South East of England, with 27.7%.
| Region | All jobs - Female | All jobs - BAME | All jobs - Under 35 | Digital jobs - Female | Digital jobs - BAME | Digital jobs - Under 35 |
| North East | 51.0% | . | 38.5% | 21.0% | . | 46.1% |
| North West | 49.9% | 8.1% | 39.6% | 25.0% | 9.5% | 39.4% |
| Yorkshire | 49.0% | 8.3% | 39.8% | 19.3% | 10.8% | 39.5% |
| East Midlands | 49.3% | 10.9% | 38.6% | 25.4% | 16.3% | 38.6% |
| West Midlands | 49.0% | 15.5% | 39.4% | 22.9% | 17.4% | 39.8% |
| East of England | 50.1% | 8.9% | 37.4% | 24.7% | 12.8% | 42.0% |
| London | 48.7% | 34.3% | 44.3% | 28.4% | 30.1% | 48.7% |
| South East | 49.9% | 9.7% | 37.4% | 27.7% | 11.5% | 34.0% |
| South West | 50.6% | 5.0% | 38.9% | 20.3% | 5.3% | 40.7% |
| Wales | 51.8% | . | 40.6% | 25.4% | . | 51.0% |
| Scotland | 50.7% | 3.8% | 39.5% | 26.5% | 7.0% | 42.9% |
| Northern Ireland | 50.4% | 4.9% | 38.7% | 27.0% | 4.2% | 45.7% |
| UK | 49.8% | 11.8% | 39.5% | 25.5% | 15.2% | 41.7% |
(Source: Tech Nation, ONS, 2019)
When we look at the breakdown of the tech workforce for UK cities, it is clear that some are more diverse than others - this information could be used as a starting point to explore the inclusiveness and diversity of tech companies in these cities, and form the basis for local interventions from respective tech communities, as well as learning from good practice that exists across the UK and in leading tech firms:
- Wolverhampton and Walsall (41%), Blackpool (37%), Cambridge (35%), Milton Keynes (35%) and Merthyr Tydfil (39%) are leading for the representation of females in digital roles
- Portsmouth (11%) and Bristol (13%) are lagging in the proportion of females working in digital roles.
- Birmingham (28%), Leicester (32%) and Coventry (30%) have the highest proportion of BAME employees in digital tech roles, though data across UK clusters is patchy. However, Leicester is the only UK cluster representative of the ethnic composition of the UK workforce more broadly, and this is likely a local underrepresentation, based on the working population of that city.
| City | Digital jobs - Female | Digital jobs - BAME | Digital jobs - Under 35 | All jobs - Female | All jobs - BAME | All jobs - Under 35 |
| London | 29% | 25% | 48% | 52% | 32% | 44% |
| Manchester | 21% | 14% | 44% | 51% | 13% | 41% |
| Glasgow | 28% | . | 48% | 52% | . | 45% |
| Slough and Heathrow | 22% | 52% | 41% | 50% | 38% | 36% |
| Newcastle | 20% | . | 48% | 54% | . | 39% |
| Reading | 25% | 16% | 33% | 53% | 12% | 38% |
| Birmingham | 21% | 28% | 36% | 51% | 26% | 41% |
| Warrington and Wigan | 29% | . | 29% | 52% | . | 36% |
| Cardiff | 28% | . | 50% | 51% | . | 40% |
| Liverpool | 27% | . | 46% | 53% | . | 40% |
| Bristol | 13% | . | 44% | 52% | . | 47% |
| Middlesbrough and Stockton | 24% | . | 49% | 52% | . | 38% |
| Newport | 20% | . | 36% | 53% | . | 39% |
| Edinburgh | 19% | 12% | 48% | 50% | 6% | 43% |
| Luton | 19% | 15% | 58% | 51% | 18% | 36% |
| Southend | 22% | 14% | 40% | 53% | 5% | 41% |
| Wolverhampton and Walsall | 41% | 15% | 36% | 52% | 17% | 39% |
| Nottingham | 26% | 15% | 48% | 52% | 14% | 42% |
| Falkirk and Stirling | 28% | . | 36% | 54% | . | 43% |
| Swansea | 29% | . | 62% | 50% | . | 38% |
| Southampton | 18% | . | 23% | 48% | . | 39% |
| Leicester | 22% | 32% | 46% | 51% | 23% | 39% |
| Sheffield | 23% | . | 54% | 49% | . | 42% |
| Merthyr Tydfil | 39% | . | 56% | 50% | . | 39% |
| Coventry | 18% | 30% | 47% | 51% | 21% | 46% |
| Swindon | 20% | 19% | 26% | 51% | 9% | 36% |
| Dundee | 18% | . | 63% | 49% | . | 44% |
| Dudley | 19% | . | 53% | 48% | . | 40% |
| Blackburn | 22% | . | 41% | 51% | . | 40% |
| Hull | 22% | . | 35% | 53% | . | 41% |
| Leeds | 27% | 9% | 33% | 51% | 12% | 43% |
| Peterborough | 25% | . | 30% | 50% | . | 40% |
| Blackpool | 37% | . | 31% | 55% | . | 33% |
| Stoke-on-Trent | . | . | 65% | . | . | 38% |
| Portsmouth | 11% | . | 48% | 53% | . | 41% |
| Derby | 22% | . | 35% | 47% | . | 41% |
| Bangor and Holyhead | . | . | . | . | . | . |
| York | 21% | . | 27% | 52% | . | 38% |
| Bournemouth | 25% | . | 42% | 52% | . | 39% |
| Milton Keynes | 35% | 19% | 25% | 50% | 12% | 38% |
| Sunderland | . | . | 36% | . | . | 38% |
| Aberdeen | 32% | . | 36% | 52% | . | 44% |
| Cambridge | 35% | 18% | 36% | 54% | 10% | 38% |
(Source: Tech Nation, ONS, 2019)
How has the pandemic impacted Diversity and Inclusion?
Research carried out by Fawcett in their ‘Equal Pay Day Report’ shows that inequalities increased during the pandemic.
43% of working women and 53% of working women from a non-white ethnicity worried about their jobs and promotions during the pandemic.
1 in 3 mothers lost their jobs or number of hours due to childcare responsibilities.
However, as working from home was introduced on a national scale and more flexibility was allowed, this catered to the 91% of women who prefer flexible working. Moreover, research carried out by BIT found that when job advertisements included flexible working options, 16% more women applied for the job.
(Source: Tech Talent Charter, 2021)
Analysis carried out by Tech Talent Charter details actions organisations have taken as a result of the pandemic. The top three responses were increased flexibility (24%), no action (20%), and mental health/wellbeing support (18%).
How has the growth of the tech sector impacted diversity and inclusion?
9% of the UK workforce are employed in digital tech, according to data from the ONS.
Employer demand for tech jobs was at a record high, as of June 2021. As of February 2021, there have been over 100,000 advertised tech jobs. All IT related job vacancies now account for 13% of all UK open job vacancies.
Careful attention should be made in terms of the type of people companies are attracting and recruiting for such roles, by ensuring they use a variety of talent pools and job boards for recruitment.
Multiverse, formally known as WhiteHat, has approximately two fifths of apprentices on tech apprenticeships.
- 58% identify as BAME (Black, Asian, Mixed ethnicity).
- ⅓ are from a disadvantaged background
- ⅓ had free school meals
Apprenticeship schemes are available to help those wanting to gain some digital skills, and forge a career in the tech world. It offers the flexibility of learning whilst on the job and gaining a qualification, developing practical experience.
The diversity of leaders in UK tech scaleups
We analysed over 2,200 UK based tech scale ups to assess the diversity within these companies, by understanding the gender split of founders and C-suite.
The percentage of primary C-suite execs in tech scale ups and high growth tech companies, where gender is known, was skewed heavily towards men, in some roles, the proportion of females was less than 1%.
(Source: Tech Nation, Beauhurst, 2021)
Tech C-Suite summary:
- 9% (206) female and 91% (2065) male.
- Taking the primary C-suite as a subset, of the 206 females that made up the 9%, of these 137 were founders.
- 8% of Chief Executive Officers/Managing Directors/Owners are held by women.
- Only 3% of Chief Technology Officers (CTO’s) or Technical Director roles are held by women.
- 0.6% of Chief Operating and 0.4% of Chief Financial Officer roles are held by women.
Inclusive job advertisements
Data from LinkedIn’s ‘Gender Insight Report’ shows that the numbers are very similar for both men and women looking for jobs and researching a company on LinkedIn before applying. 41% women vs 42% men. However, this does not translate into jobs applied for, women were 16% less likely than men to apply for the job. Overall, women apply to 20% fewer jobs than men.
Research shows that when reading through job descriptions, women tend to feel they have to meet all requirements of a job, before they can apply. Whilst, men meeting about 60% of requirements of a job feel that it is sufficient.
Advertised job roles with a ‘check’ lists of demands and requirements can deter women from applying, whereas describing the performance objectives of a role is more inclusive.
Transparency and fairness of a company is often inferred from a job advert when the salary bracket is included. Both women and men feel that the salary range and benefits are the most important information to be included in a job description at 68% and 58% respectively. With a clear 10% difference between the two, this is followed by the qualifications needed.
(Source: Linkedin ‘Gender Insight Report’, 2018)
It is important for companies to understand how they can work to improve inclusion, which should in hand attract people from all backgrounds. In order to provide some key action points which organisations can take away, and apply, we spoke to industry experts who lead in the D&I space to answer some key questions.
However, once women apply, they are 16% more likely than men to get hired for the role. This increases to 18% for more senior roles than their current position. Therefore, we can assume the hurdles are earlier on in the process
Expert insight
Improve the application process
Bridget Gildea
Consultant: Behavioural Insights; policy, innovation and digital learning
Studies have increasingly shown that interventions focused on e.g. unconscious bias training not only have a negligible effect on diversifying the hiring process, but can actually backfire, leading to worse outcomes in terms of diversity, equity and inclusion in organisations’ hiring. Some firms have incorporated findings from behavioural science to look instead at taking an evidence-based approach to de-biasing systems, including areas of framing, candidate selection and the provision of biographic data in the application and hiring process. This has included areas like removing the “noise” of biographical data including with classical musician auditions – when the hiring committee could see the musicians playing, only 5% of the finalist pool were women; after putting up screens between the musicians and committee so the committee could not see the musicians, this went up to 50% purely through this one intervention.
What is the state of diversity among UK tech founders and investment?
According to a report by Extend Ventures, within the past decade (2009 - 2019) female entrepreneurs faced barriers accessing VC investment, as shown below. Only 3% of VC funding (seed, early- and late-stage) went to all female teams. On the other hand, all male teams received 68% of VC funding.
Comment
Supporting diversity in tech
Jeevan Sunner
Playfair Capital
Only 3% of VC funding went to all-female teams; the Covid-19 pandemic has only exacerbated this. At Playfair, we want to help redress that imbalance. In collaboration with Tech Nation, Google for Startups and 90 leading European VCs, we will give 250+ women founders the opportunity to meet investors to ask for advice, pitch for investment or find a mentor. In doing so, we hope more women from remote areas of Europe are getting equal opportunity and access to investors. Find out more here.
Entrepreneurs from Black, South Asian, East Asian and Middle Eastern backgrounds received in total 1.7% of VC investment. Given that ethnic minorities make up 14% of the UK population, this shows the disproportionate underinvestment in these communities. On the other hand, 76% of VC investment went to all white founding teams.
Only 0.24% of the 1.7% invested in ethnic minority founders went to black entrepreneurs. Black female entrepreneurs are at an even greater disadvantage, receiving the lowest amount of funding this decade, at 0.02%. This equates to just one black female founder – believed to be Sharmedean Reid of BeautyStack.
Overall, 43% of VC funding went to teams where at least one founding member was from an elite university, defined as the University of Cambridge, the University of Oxford, Harvard University or Stanford University including their business schools. This also shows a skew towards those with educational and economic privileges.
Investment by growth stage also shows that white founders get the lion share of investment, and this proportion grows as the stage increases.
It is estimated that only 3% of VC’s in the UK are black, with only a few at partner level or in the position to make investment decisions. Higher representation of black people within VC firms could help alleviate investment gaps.
Expert insight
The importance of role models
Isabel
Independent Consultant, D&I
- This is important in relation to role models within the young person's workplace, and understanding their sphere of influence outside of work, (this may be positive, negative, or indifferent). Who are the role models in the young person's life - we must understand this and their connection to the young person's understanding/expectations of work, a career and personal development.
- Mentoring is about an ongoing relationship between two people. Young people can have more than one mentor, and these relationships can be formal and informal, often we tell young people they need one mentor who will solve all their issues - this is untrue.
- Mentors must understand the key point that 'success' is individual to each young person and not try to solve all the young person's problems, or over-promise and not deliver. The main outcome or aims of mentoring should be: to challenge, develop confidence, celebrate success, encourage the young person to reflect and be critical/honest about mistakes when needed, develop problem-solving skills, and work with the young person to overcome their own challenges.
There are initiatives created to ensure fundings goes to diverse founders and to make VC more representative of society, such as Diversity VC, Included VC and the Newton Venture Program.
Methodology
Adzuna
Over 17million rows of job advertisement data were analysed using data from Adzuna to understand and evaluate the current health of tech, by looking at employer demand for tech jobs. But also how employer demand for tech jobs were affected by the pandemic.
There were 29 categories of job advertisements from construction jobs to healthcare to legal. Data from the years 2020 and 2021 (January to June) were analysed. The median salary was used to ensure figures presented in the report were not heavily skewed towards more senior higher paying tech roles.
Office for National Statistics (jobs)
To measure the total number of tech and tech-enabled jobs across the economy, we used data from the Office for National Statistics (ONS) Annual Population Survey (APS). This is a survey-based sample of the UK population – on individual people rather than businesses. To get UK-wide data on people working in tech jobs from the survey, we have to make sure that the sample of people reflects the broader UK population – so we have to use multipliers from the ONS.
But this kind of analysis does not measure the number of direct jobs created by digital tech companies. To understand the impact and benefits of digital tech we need to have reliable data not only on the number of tech jobs across the economy but also performance and productivity indicators for the sector itself.
To do this, we use official data from the ONS Business Structure Database (BSD), which we also use to look at the performance of tech companies. This methodology allows us to have refined data that can be relied upon as the most accurate count of direct jobs created by the digital tech companies across the country.
The numbers are quite different in some cases. This is because one analysis looks exclusively at people working for digital tech companies, while the other looks at people working in tech jobs across the economy.
This report presents two different sets of stats on employment. This means that the economy-wide numbers should not be compared to the sector-wide ones. But we have used this year’s method to look back over time. If you want to compare employment in your local area, all the data you need is in the 2018 Tech Nation report.
The new 2019 analysis is based on a comprehensive look at all UK businesses that are PAYE or VAT registered.This means that using BDS data will provide us not only with the number of direct jobs created by tech companies but also helps us understand the performance of these companies. Viewed together, the two sets of data will help us understand all people working in digital tech.
The data on digital tech companies also contains financial information, as well as employment. This means that we can have reliable data on productivity. To get a true picture of jobs in digital tech, we need to look at performance, as well as quantity of jobs – this cannot be obtained from the APS alone.
Digital tech jobs – includes all people working in digital tech occupations, irrespective of the industry. For example, a software developer working in a retail company. (Source: ONS Annual Population Survey, Sept-Sept 2018-2019)
Digital tech jobs in digital tech – includes only people working in digital tech occupations in the digital tech industries. For example, a software developer working in a web development firm. (Source: ONS Annual Population Survey, Sept-Sept 2018-2019)
Jobs in digital tech – includes all people working in digital tech industries, including non-digital jobs. For example, an accountant working in a web development firm. (Source: ONS Business Structure Database Sept-Sept 2018-2019)
Beauhurst
Over 2,200 UK Scale ups were analysed using Beauhurst data to determine the proportion of male and female split within tech companies, as founders and C-suite.
Secondary data sources and reports such as Extend VC, LinkedIn, and The Tech Talent Charter and were also used within the report.
Expert insight
How to create inclusive job advertisements
Lexie Papaspyrou, Project Lead
Tech Talent Charter
There is a lot of guidance coming out in the D&I space but much of it is based on untested hypotheses that are yet to be shown to be accurate. In general the D&I space has a dearth of rigorous research and this makes it hard to identify what is helpful and what is ineffective, or worse, counterproductive.
However, there are a small number of organizations which are now producing high quality data-driven research conducted via randomised controlled trials. This is leading to a much needed and growing number of insights that can be relied upon to genuinely improve the inclusivity of recruitment if executed properly.