How to Use Data to Drive Inclusive Recruitment with Rubie Clarke

Amberjack helps future focused organisations bridge the gap between today and tomorrow.


Amberjack and Fearless Futures at the 2023 Institute of Student Employers EDI Conference  

Understanding the uses and importance of intersectional data analysis and best practice in ED&I data management, as well as current industry EDI trends, is a necessary part of achieving a robust recruitment process that encourages diversity and embodies inclusion. This is why Amberjack hosted a session at the most recent ISE EDI Conference with Fearless Futures, deep diving into this topic and providing practical examples and suggested actions for employers. 


Creating inclusion through the recruitment process requires innovation. Amberjack partnered with DEI experts, Fearless Futures in 2023 in an exciting partnership to unlock robust insights in Amberjack’s candidate recruitment data from over 300,000 applicants and 36 sectors. Using Fearless Futures’ intersectional analysis modeling, the result is an insightful and revealing report for 2023 which shows the joint effects of demographics like Ethnicity, Race and Gender on the outcome of an application, producing critical insights for employers and a compelling case for intersectional approaches to DEI tactics and solutions. 

So, what is intersectionality? 

When organisations gather diversity data, it’s traditionally done in isolated categories like Race or Gender. Collecting data in this way limits the depth with which we can understand DEI trends in recruitment – and indeed beyond –  because looking at categories of identity separately fails to consider or account for the fact that people can be both Black and a Woman, or Asian and a Disabled Man – and the specific experiences and needs of such communities. 

The risk of taking a “siloed” approach is firstly inaccuracy. Data that says “women receive higher offer rates than men ” may invisibilise the fact that for South Asian Women, the opposite might be true. Working on the basis of incomplete or inaccurate data has risk implications – if all seems to be going well for Women in an organisations recruitment cycle, you might consider your approaches to inclusive recruitment very effective for Women and turn your attention elsewhere – meaning South Asian Women are not only invisible in the data, but invisible, unaccounted for and underserved in your DEI solutions too… 

The risk of this approach is not just inaccuracy, but inefficacy, in the decisions made based on the data insights. Data that shows “women receive higher offer rates than men” may disregard that for Black Women, this isn’t quite right. If all seems to be going well for Women in your recruitment processes, Black Women, like South Asian Women in our examples, are not only also invisible in the data, but lacking consideration in your DEI solutions. This results is often less diverse teams, whereby the vast majority of Women hired are White, and the Black folks hired are men, and so on: in other words, folks who experience multiple forms of inequity are rarely served by siloed approaches to inclusive recruitment. 

Systems of inequity, like racism and sexism, don’t operate as ‘stand alone’ systems, they intersect to produce unique inclusion barriers. Look at the pay gap for example, Fawcett Society’s intersectional analysis of the most recent pay gap data shows there is a 14.7% pay gap between women of Bangladeshi and Pakistani heritage and white British women. Compared with white British men, the figure is 28.4%. For Mixed White and Black Caribbean heritage women there is a 10.6% gap between them and White Women. Compared with white British men, the gap is 25%. The Fawcett report identifies systemic inequity* as a key cause for the Ethnicity and Gender pay gap: 75% of Women of Colour have experienced racism at work and 42% report being passed over for promotion despite good feedback. The figure for white women is 27%. 

In order to design DEI solutions that are effective and sustainable in removing intersection barriers, we need to identify the specific trends at the intersection of Race and Gender, and other categories. We need an intersectional approach that analyses these categories together. By unlocking these important trends, organistions can not only improve the accuracy of insights but, crucially, can use this data to evaluate where hidden barriers to inclusion may be present in existing processes, policies and approaches to recruitment.

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