4 minute read
How can we evaluate potential?
How can we evaluate potential?
Yale School of Management Finance Professor Kelly Shue studied almost 30,000 management track employees at a large North American retail chain. Her study of the chain's evaluation and promotion data found that women consistently got higher performance ratings than men, but consistently received lower potential ratings as well. Why was this?
Shue worked with colleagues Danielle Li (MIT) and Alan Benson (University of Minnesota). They described the evaluation process of the company as follows: "Managers use a “nine-box” grid—a commonly used tool at large organizations—to evaluate their employees, giving them a low, medium, or high score on their performance over the prior year and a low, medium, or high score on their potential for growth and development. The employees with high scores for both performance and potential—those in the upper right quadrant of the grid—are most likely to be promoted."
Their paper noted that while real-world metrics contributed to the performance rating, the potential rating was more abstract, and therefore at risk of bias from the evaluator. They expressed concern that characteristics such as assertiveness, charisma and ambition were commonly associated with leadership potential, while also being highly subjective and stereotypically associated with male leaders.
They also considered the possibility that evaluators were correct in their assessment that women were high-level performers but lacked the skills to be successful in different roles in the future (what the 'potential' rating implies). However, they found the opposite. They identified men and women with similar performance and potential ratings for one period, then looked forward to see how they diddid their potential ratings come true? They found that for the same potential rating, women tended to receive a higher performance rating in the next period as well (whether or not they had been promoted). And the cycle continued - women continued to receive lower potential scores even after they demonstrated through their performance that the previous period's potential score was inaccurate.
The authors also checked whether female evaluators would be less susceptible to this trend, but they did not find significant differences in the evaluation practices of male and female managers. It is possible that female evaluators fear being seen as 'unfairly' favouring other women, so are peer pressured into mimicking the sex ratios of their promotion cohorts as the wider organisation.
Overall, Shue describes a system where women get progressively lower potential scores relative to their actual future performance the higher up the organisation you go. The key takeaway of the research is that managers were consistently underestimating women's ability to perform in the future, resulting in a 'promotion gap'.
So, what can organisations do to close this gap? One solution would be to remove potential ratings from the evaluation system and promote based on proven performance. The advantage of this step is simplicity, but it could have other consequences. Shue's earlier research has shown that those performing best in their current role do not always perform as highly in the next role, especially when those roles have different responsibilities. As an intermediate step,
organisations could adjust the weighting they place on performance and potential, to rely more heavily on performance rather than 50:50. In an ideal world, organisations would employ data scientists to look for systematic gaps between performance and potential ratings like those in the study. They could also continue to identify other metrics that predict leadership talent, beyond manager evaluations. As investment in Diversity & Inclusion grows, organisations should consider using that spend on data scientists and specialists in organisational behaviour. With better insights, management should be able to make better decisions, which should give a better return on investment than motivational speakers.
