Last week, the BBC reported that it’s easier to get a job if you're called Adam rather than Mohamed. Their mini-study replicated findings published in academic journals, by sending out fictitious CVs which were all identical, except for the names. In the original U.S. study, researchers sent around 5,000 CVs in response to job adverts, each randomly assigned with a stereotypical African-American or White-sounding name. Those with white-sounding names received 50% more callbacks for interviews. This bias persisted regardless of occupation, industry, or employer size.1 It has also been found against immigrant applicants, with recruiters justifying their decisions with language concerns, despite CVs listing language fluency, multinational firm experience, and education from top schools.2
Stereotypes, it seems, are alive and well in occupational selection. Evidence suggests that these implicit and subconscious biases are still contributing to workplace discrimination today.
Subconscious biases are also rife in promotion decisions. Ingroup (“like me”) bias describes managers' tendency to be more generous in their evaluations of employees who are similar to them, whether it be in terms of race, gender, or other obvious demographic characteristics. They tend to attribute the success of those similar to themselves, to internal, dispositional characteristics (“they succeeded because they’re good”). In contrast, achievements of ‘outgroup’ employees are more often attributed to external factors such as chance or fluke (“they were lucky”).3 Unfortunately, many promotion decisions tend to be highly subjective, based on vague or nonexistent criteria, and thereby open to significant bias. In the 1990s, a review of 64 promotions in three Fortune 500 companies revealed that “formally collected data didn’t enter into the promotion decision.”4 Is the situation any better today? In my experience, it’s a very mixed picture.
Without a robust development and assessment process, promotion decisions are likely to be based on subjective, personal knowledge of the candidate; with decision-makers relying on perceived similarity to themselves, or the extent to which they feel ‘comfortable’ with an individual. Such biases may contribute to the greater likelihood of men receiving promotions than women.5
Unfortunately, unconscious biases are not only in the ‘eye of the beholder’, they can also directly impact an individual’s performance through stereotype threat. This occurs when individuals within minority groups are reminded of the ways in which they might be negatively judged by the majority group and subsequently experience a decline in personal performance.6 For instance, imagine a woman applying for the ‘future leaders’ programme within her engineering firm. As she waits for her panel interview, she sits in the lobby surrounded by portraits of the company’s current and previous CEOs, dating back since the company was founded. As she glances down the long line of portraits, she notices that they are all men. Doubt of her own suitability is planted in her mind, as she questions whether a woman could ever run this firm. This “threat in the air” causes additional anxiety and distraction, which impairs her performance in the interview.6
There’s growing recognition that discrimination in society today is largely implicit and so has become “invisible, deep, and pervasive”.7 This might explain why, despite the documented benefits of workplace diversity, progress in achieving it has been slow.8 It’s important that we recognise this because a different approach is needed to address discrimination caused by subconscious biases. These subtle, deep-rooted forms of discrimination require more subtle and deeply rooted interventions.
Instead of attempting to ‘outlaw’ implicit biases, their motivational underpinnings must be addressed, along with the cultural factors which may trigger or maintain the beliefs and attitudes underpinning them. Greater attention also needs to be paid to the decision-making process itself, to unearth the subtle (and job irrelevant) factors that can influence talent management, potentially leading to discrimination. Whatever happens, stick to your data, resist the temptation to throw the criteria out of the window and go with a lower scoring candidate just because you feel they have a better “fit”. The vague concept of “fit” can hide many sins. Anyway, are you trying to create a workforce of replicas?
1Bertrand, M., & Mullainathan, S. (2004). Are Emily and Greg More Employable Than Lakisha and Jamal? A Field Experiment on Labor Market Discrimination. American Economic Review, 94, 991-1013.
2Oreopoulos, P. (2011). Why Do Skilled Immigrants Struggle in the Labor Market? A Field Experiment with Six Thousand Resumes. American Economic Journal: Economic Policy, 3, 148–171.
3Hung-Ng, S. (1981). Equity theory and the allocation of rewards between groups. European Journal of Social Psychology, 11, 439–443; Tsui, A., & O'Reilly, C. (1989). Beyond Simple Demographic Effects: The Importance of Relational Demography in Superior-Subordinate Dyads. The Academy of Management Journal, 32(2), 402-423.
4Ruderman M. N., & Ohlott P. J. (1994). The realities of management promotion. Greensboro, NC: Center for Creative Leadership.
5Ruderman M. N., Ohlott P. J., & Kram K. E. (1995). Promotion decisions as a diversity practice. Journal of Management Development, 14(2), 6–23.
6Schmader, T. (2010). Stereotype threat deconstructed. Current Directions in Psychological Science, 19, 14-18.
7Bartlett, K. (2009). Making Good on Good Intentions: The Critical Role of Motivation in Reducing Implicit Workplace Discrimination. 95 Virginia Law Review 1893-1972. Available at: http://www.jstor.org/stable/27759975?seq=1#page_scan_tab_contents
8Dobbin, F., & Kalev, A. (2016). Why Diversity Programs Fail. Harvard Business Review, 94(7), 14-20.