TTC Methodology Notes

1. Overview

We conducted an annual survey targeting organisations (Signatories) to collect qualitative and quantitative data on Diversity and Inclusion (D&I) in UK tech. The survey was distributed to Senior Signatories, Principal contacts, or designated Data contacts and we received responses from 708 organisations.

2. Survey preparation

Participants were provided with questions and guidance notes one month before the submission window.

Webinars were conducted to offer support and clarify any queries about the survey and questions.

3. Data Collection Period

Data collection took place between July and September 2023 and was required to be a snapshot of any point between March 1, 2023, and September 28, 2023.

4. Participation Requirement

To maintain Signatory status, organisations had to respond to at least the mandatory sections of the survey. Signatories who failed to submit mandatory data were removed from the Tech Talent Charter (TTC).

5. Data Representation

The collected data represented 229,781 UK tech roles, which, based on a CompTIA 2023 report on the ‘State of the Tech workforce UK ’, allows us to estimate a representation of between 11% and 12% of the UK tech workforce.

The CompTIA’s report “draws upon many data sources, including EMSI Burning Glass, UK Office for National Statistics (ONS), Eurostat, OECD, CompTIA and more."

6. Tech employee sample sizes

In addition to the robust sample sizes captured across gender and ethnicity, the sample sizes of tech employees for disability, neurodiversity and socioeconomic status are as follows:

Disability - 113,262

Neurodiversity - 59,647

Socioeconomic disadvantaged backgrounds - 30,472

7. Data Accuracy

The inclusion of unusual/outlying data was considered on a case-by-case basis to ensure the analysis was accurate and trustworthy. For example, we contacted Signatories for clarification/correction of numbers that failed data checks.

8. Dataset Reliability for Benchmarking

Data excluded instances where Signatories did not request diversity data from employees or if employees did not disclose their diversity data.

Nonetheless, the dataset features a robust sample size, ensuring its reliability and utility.

9. Categorisation Criteria

Industry, location, and company size were standardised for anonymity and analysis purposes.

For example, employee counts were split into the following categories:

• 1-9: Micro
• 10-49: Small
• 50-249: Medium
• 250-1,000: Large
• 1,001+: Super large

10. Gender

Signatories were asked to report on the number of tech roles held by people who are: 

Men; Women; Non-binary and/or Trans; accounting for preferences not to disclose. 

When the term ‘gender minority’ is used we are totalling the number of employees who identified as women or non-binary. We define the term “gender minority” in the context of the UK tech economy, where women and non-binary people are minority groups. We recognise that in wider demographic samples these groups are not necessarily minority groups.

Note: the proportion of gender minorities captured in our survey has risen slightly each year, but it’s important to contextualise that although our datasets are large samples, they are not longitudinal; new Signatories join TTC each year and some are removed each year for failing to meet their commitment to share their D&I data. Therefore our data is a snapshot each year of what is happening in the companies that are committed to improving D&I in tech. Our non-binary data is only 0.09% and therefore this number mainly refers to women.

11. Ethnicity

Signatories were asked to report on the number of tech roles held by people who are: 

Asian or Asian British; Black African, Caribbean or Black British; Mixed or multiple ethnic groups; White or Any other ethnicity; accounting for preferences not to disclose. 

When the term ‘ethnic minority’ is used we are totalling the number of employees reported to be Asian or Asian British; Black, African, Caribbean, or Black British; or Mixed or multiple ethnic groups.

12. Other Diversity Lenses

Signatories were asked to share if they measure other employee characteristics, including Disability, Neurodivergence and Socioeconomic diversity.

In addition to this, Signatories were asked about their D&I strategy for the following lenses:

Age, Disability, LGBTQ+, Neurodiversity, Religion, Socioeconomic diversity.

13. Reporting and Exclusions 

Percentages have been rounded up to the nearest whole unless otherwise noted.

To ensure a consistent and representative position, Signatories without tech employees have been omitted from the average industry calculations.

14. Additional Data

In addition to the annual D&I survey, data was used from a nationally representative consumer research survey on Neurodiversity, conducted on our behalf by Attest.

References:

Taylor, L.(2023), ‘Investors must avoid tokenism to improve VC diversity’, UKTN. Available at https://www.uktech.news/guest-posts/improving-diversity-vc-venture-capital-20230705 (accessed 14 February 2024)

Wood, A.(2023), ‘Only 2% of VC funding goes to female and ethnic minority founded businesses’, Startups Magazine. Available at https://startupsmagazine.co.uk/article-only-2-vc-funding-goes-female-and-ethnic-minority-founded-businesses (accessed 14 February 2024)

Morgan Stanley (2023), ‘How founders and investors can work together to build a more inclusive ecosystem’, Sifted. Available at https://sifted.eu/articles/founders-investors-inclusive-ecosystem-brnd (accessed 15 February 2024)

15. Contact Information

For further inquiries about the annual report, data, or methodology, contact TTC at hello@techtalentcharter.co.uk