Harvard Business Review Full Article
https://hbr.org/2021/02/research-men-get-more-actionable-feedback-than-women
Research: Men Managers Get More Actionable Feedback Than Do Women
Elena Doldor, Madeleine Wyatt, and Jo Silvester
February 10, 2021
Audrey Shtecinjo/Stocksy
Summary.
One of the most important ways managers can support aspiring leaders is though developmental feedback; that is, feedback focused on growth opportunities. However, not all developmental feedback is created equal. New research based on a computerized analysis of more than 1,000 pieces of written feedback identified four key ways in which feedback given to women tends to be less actionable and less effective than that given to men: Developmental feedback for female employees tends to focus on delivery rather than vision, coping with politics rather than leveraging politics, and collaboration rather than assertiveness. It also tends to present a lack of confidence as a fundamental shortcoming, rather than a specific skill that can be developed. Based on these disparities, the authors offer several strategies for managers to overcome their own (often unconscious) gender biases and help both their male and female reports achieve their leadership potential.
Although businesses now employ more female managers than ever before, women’s advancement into senior leadership roles remains much slower than for men. While there are a variety of structural causes driving gender inequity in the workplace, one important factor is the disparity in how men and women are given developmental feedback. Identifying and reducing bias in feedback on past performance is somewhat more straightforward, since this sort of feedback tends to be more quantitative — but feedback focused on how employees should change and grow as leaders in the future is fundamentally qualitative, making it much harder to analyze.
However, with computerized text analysis, it’s possible to quantify differences in feedback between men and women, as well as how these differences can drive employees down different leadership paths. In our recent study, we used a form of machine learning known as “topic modeling” (which has recently become popular as a tool for analyzing political Tweets — see the Methodology Corner below for more details) as well as comprehensive qualitative analysis to investigate a large, complex dataset of developmental feedback.
Specifically, we explored gender differences in a dataset of open-ended written feedback for 146 mid-career leaders, provided anonymously by more than 1,000 of their peers and leaders while taking part in a leadership development program. We also asked participants to rate their leaders’ performance numerically, giving us a quantitative baseline for comparison that enabled us to control for objective differences in leaders’ performance.
Извор: WUNRN – 01.04.2021
