Tool: Leadership Opportunity Selection Template

A woman comparing an apple and an orange

Leadership Opportunity Selection Template

Research in Management Science shows that bias is significantly reduced when employees are evaluated jointly rather than separately regarding their future performance.

This technique can be applied to many HR processes—including job interviews, promotions, bonuses, and even leadership development opportunities— to ensure fairness and accountability.

For example, when working with clients to improve equity in leadership representation, we often find that promoted employees have successfully completed a stretch assignment. That's because stretch assignments are vital to gaining the skills and visibility necessary for a promotion. But stretch assignments are usually assigned informally and unevenly, based solely on manager discretion.

To change that, we recommend implementing a formal process for stretch assignments.

A bias-busting process

In collaboration with managers, articulate the criteria for being assigned a stretch opportunity (for example, all good performers that receive an average performance review score of 3.5 out of 5 should receive a stretch assignment in the next quarter). Then, during the performance review process, ask managers to indicate whether each eligible report was assigned a stretch assignment. HRBPs can be trained to support manager adoption of this new process.

Such a comparison process can ensure that stretch assignments are fairly assigned company-wide, which in turn can bring you closer to your equity goals.

Click here to access the stretch assignment comparison template, and find out more about how Peoplism helps organizations adopt more fair processes and behaviors to improve DEIB.

"Evaluators are more likely to base their decisions on individual performance in joint than in separate evaluation and on group stereotypes in separate than in joint evaluation, making joint evaluation the profit-maximizing evaluation procedure."

Bohnet et al. Management Science, 2017

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