Post by Sylvia Apostolidis
Principal DEI Consultant & Founder, The Jasmar Group
Creating a diverse, equitable and inclusive (DEI) workplace has never been as important and urgent as it is today. Having worked in the field for nearly 20 years, I am encouraged by today’s increased senior level commitment, budgets, and intentions to break down barriers and ensure equitable treatment for all. Yet, despite best intentions, very little progress has been made.[1] Overall inclusion scores[2] and representation levels of women and non-majority group members at executive levels have stagnated.[3]
Companies continue to throw time and resources
at traditional approaches that yield little.
Your culture is what people do, not what they know or think. Current approaches to DEI appeal to our rationality, aiming to change beliefs in hopes of more inclusive actions. “Of course, bias awareness training and leadership programs for women will be beneficial”, they say, not realizing that awareness and fix-it programs geared towards under-represented groups have little, if any, positive impact (and can actually backfire).[4] Imagine how much time and money is being spent on something that simply is not working. We approach other business problems with evidence-based rigour – why are we not doing the same in the DEI realm?
Let’s re-think diversity statements
Visit any FP500 company’s website and you’re likely to see a statement committing to building a diverse, equitable and inclusive workplace. But do these statements actually increase diversity in hiring? Not so, according to recent evidence.[5] In fact, they may lead to less hiring of people from under-represented groups!
We need to move beyond assumption to evidence.
Behavioural science makes diversity work better.
We are, after all, trying to change behaviour. Isn’t it time to use what we know about human behaviour, decision-making and motivation to make real and sustainable change towards inclusion? Let’s move beyond assumptions and “best” practice and, instead, focus on influencing behavioural change through an evidence-based and measured approach. It not only gets to better outcomes, but it also focuses our effort, time, money and overall limited resources on the things that are going to work best.
There’s a strong business case for
applying Behavioural Insights to DEI.
Achieving a diverse and inclusive workplace is a “wicked” problem – defined as a social or cultural challenge that is difficult to solve, deeply interconnected with other complex social issues, and wrought with systemic and individual biases. Over the past five years, there’s been an explosion of BI teams (40 to 400!) around the world solving similarly complex issues.
The opportunity is enormous for organizations to embrace BI and (finally!) make real, sustainable change to advance diverse, equitable and inclusive cultures. The applications of BI to DEI challenges are endless - whether it’s improving talent processes, motivating leaders, creating more effective learning solutions or increasing uptake rates for various initiatives, for example. And we can choose which BI method suits us best: A behavioural lens approach (applying what we know from the BI literature) or a behavioural trial (using experimentation to determine what works best in our specific organization). While a BI trial yields more confidence in our solutions, a behavioural lens approach offers a good first step for many organizations.
Interrupting Bias in Recruitment and Talent Processes
“I’m not biased.” It’s a statement that I’ve heard more times than I can count. The reality is that we all hold cognitive biases and stereotypes that impact our intentions to be fair and inclusive. They’re unconscious, so we can’t see them at the moment of making that important recruitment or promotion decision. Many companies provide training for employees, but a better way to interrupt biases is to simply re-design the process and nudge decision-makers out of them. As examples:
The Challenge: Despite the high number of women applicants, women were not being selected for an interview.
BI Nudge: Compare CVs side-by-side. This has been shown to eliminate gender bias in evaluation!
Why it Works: Comparing side-by-side engages our slow-thinking brain and takes the stereotype out of the equation. We are also less likely to favour the most recent resume we see (recency bias).[6]
The Challenge: Evaluators are more likely to give 10/10 to high-performing men than high-performing women.
BI Nudge: Changing the rating scale from 10 (or 100) to an arbitrary number (let’s say 6) closes the gender gap on perfect scores.
Why it Works: It might seem trivial, but these numbers have cultural associations that “brilliance” is most associated with (white) men, and not people of other genders or racial groups.[7]
Motivating Leaders
Another common challenge I hear is, “My leaders don’t see the importance of investing in DEI. They believe the company is a meritocracy, despite the numbers showing otherwise. How can I get them to commit their time and resources?” Some evidence-based nudges to consider include:
The Challenge: Leaders do not understand the importance of investing in DEI.
BI Nudge: Usually the business case for DEI is presented in terms of what the organization will gain. Instead, communicate the risk. What will the organization lose by not building an inclusive culture?
Why it Works: The message may be felt more strongly as we feel losses at least 2X more than gains.[8]
Images from https://inclusion-nudges.org/
The Challenge: Leaders believe their company is a meritocracy.
BI Nudge: Humanize the demographic data to get them to an “aha” moment. First, present all employees ready for a promotion. Ask leaders, “who do you know”?
Then take away all promotion-ready employees other than white, cis-gender men. The likelihood is that leaders know less (if any!) women and minority group members.
Why it Works: We respond to emotion. Faces register differently in our mind than numbers.[9]
Small changes make a big difference!
Through firsthand experience in applying a behavioural lens to strengthen talent systems and approaching DEI strategies from a behavioural perspective, I have seen the clear results. Applying behavioural insights to DEI challenges works. It’s time to question status-quo approaches that fall short and, instead, embrace a BI approach rooted in human behaviour, evidence and experimentation.
Sylvia Apostolidis is a Diversity, Equity and Inclusion strategist, speaker and thought leader. Committed to finding real solutions to a complex issue, Sylvia works with leading companies across Canada as an advisor and consultant, sharing “next” practice DEI strategies. She brings an evidence and human-centred approach to workplace inclusion, leveraging behavioural insights to design more inclusive systems, processes and behaviours. Contact Sylvia at sylvia@thejasmargroup.com.
[1] Newkirk, P. (2019). Diversity, Inc.: The failed promise of a billion-dollar business. Public Affairs.
[2] https://www.mckinsey.com/capabilities/people-and-organizational-performance/our-insights/understanding-organizational-barriers-to-a-more-inclusive-workplace
[3] Catalyst. (2020, August 19). Women in the workforce: Canada (Quick Take). https://www.catalyst.org/research/women-in-the-workforce-canada/; Catalyst. (2020, October 20). People of colour in Canada (Quick Take). https://www.catalyst.org/research/people-of-colour-in-canada/; and Canadian Centre for Policy Alternatives. (2019, December 9). Canada’s colour-coded income inequality. https://policyalternatives.ca/publications/reports/canadas-colour-coded-income-inequality
[4] Dobbin, F., & Kalev, A. (2016, July). Why diversity programs fail. Harvard Business Review. https://hbr.org/2016/07/why-diversity-programs-fail
[5] Kang, S. K., DeCelles, K. A., Tilcsik, A., & Jun, S. (2016). Whitened résumés: Race and self-presentation in the labor market. Administrative Science Quarterly, 61(3), 469–502. https://doi.org/10.1177/0001839216639577
[6] Bohnet, Il, Van Geen, Al, & Bazerman, M (2016). When performance trumps gender bias: Joint vs separate evaluation. Management Science, 62(5), 1225-34. https://doi.org/10.1287/mnsc.2015.2186
[7] Rivera, L.A., & Tilcsik, A. (2019). Scaling down inequality: Rating scales, gender bias, and the architecture of evaluation. American Sociological Review, 84 (2), 248-74. https://doi.org/10.1177/0003122419833601
[8] Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263-292. https://doi.org/10.2307/1914185
[9] Nielsen, T. C., & Kepinski, L. (2020). Inclusion nudges guidebook: Practical techniques for changing behaviour, culture, & systems to mitigate unconscious bias and create inclusive organizations (3rd ed., pp. 172.176).