Siri Chilazi is a research fellow at the Women and Public Policy Program at the Harvard Kennedy School. Iris Bohnet is the Albert Pratt Professor of Business and Government, co-director of the Women and Public Policy Program, and the Academic Dean at Harvard Kennedy School.
In 2014, several large tech companies including Apple, Facebook, Google, and Microsoft started releasing annual diversity reports detailing their workforce composition.
The data themselves were not cause for celebration. However, the move was hailed as a win for transparency and as a harbinger for more progress to come on diversifying the industry.
As we now know, our hopes for increased diversity, equity, and inclusion (DEI) in tech have not come to fruition. The industry remains overwhelmingly white, Asian, and male-dominated, especially in technical jobs. Is there something unique about diversity data such that their disclosure does not drive behavior in the same way as data in other domains? Or might we be able to leverage further insights from behavioral science to help organizations use diversity data as an engine for progress on DEI?
Our findings in a recent white paper and several real-world examples show that when done right, the collection, analysis, and disclosure of diversity data indeed holds the promise of being a powerful lever for progress.
From Harvard Business Review
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