Thursday, September 1, 2022

Data-driven DEI

 From Fortune:

  • Understand disparities by controlling for differences in training and education.
  • Find the root causes of bias
    Preference bias is good old-fashioned bigotry (animus-based discrimination).  
    Information bias (statistical discrimination) arises when employers have imperfect information about workers’ potential productivity and use observable proxies, like gender or race, to make inferences (gender stereotypes are a classic example).  
    Structural bias occurs when companies institute practices, formally or informally, that have a disparate impact on particular groups, even when the underlying practices are themselves group blind. Employee referral programs can fall into this category.
  • Follow-up to find what works and what doesn't
    Solutions that yield measurable results can be substantiated into company policy, while those that don't should be discarded. In the case of the hospital network, once a small change was made to the structure of their scheduling, gender differences were reduced. Despite countless hours spent in training and seminars, their results were unchanged for years. The solution was hidden in plain data.

    Related:  Do Workplace Diversity Programs Work?

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