The benefits of a diverse workforce are well-recognised, e.g. size of talent pool, return on investment in training, enhanced creativity and problem solving. Yet, in many professions and businesses the workforce is dominated by one gender or ethnic group. Two scientists of Wagenigen University and an Australian and Dutch colleague, now show that much like the poverty trap, such a lack of diversity represents a lock-in situation. But they also present a way out, in their publication of 27 July in PLoS-One.
"The reason that workforce diversity turns out to be very hard to improve, is that it is driven by a plethora of mechanisms" says lead author Kate O'Brien from the University of Queensland. "There are social stereotypes, unconscious bias, family responsibilities, workplace culture and educational disadvantage of marginalised groups. These factors interact and can be contentious, making it very difficult to identify and address simple barriers to change."
Using mathematical modelling, the authors tackle the issue in a completely new way, and develop a practical framework for identifying barriers and opportunities for change.
"We demonstrate that a relatively small amount of bias towards appointing and retaining employees from the existing dominant group has the potential to keep workforce diversity low, creating a trap," says Marten Scheffer, one of the co-authors from Wageningen University. "We see the situation in our own organization where the staff is dominated by white males like myself. We want to change that, but realizing it in practice turns out to be really challenging."
Appointment and departure
O'Brien, who has a background in modelling complex systems takes a pragmatic approach. "Ultimately the composition of the workforce depends on the rate at which people are appointed to and depart from the organisation, the diversity of applicants, and whether there is any bias in appointment and departure." The simple 'employee budget approach' developed by the authors focuses on three key factors: appointment bias, departure bias and applicant diversity. They demonstrate how these indicators can be used to diagnose the bottle necks, and solve them in practice.
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