Radical Respect by Kim Scott

Author:Kim Scott
Language: eng
Format: epub
Publisher: St. Martin's Publishing Group

LOOK FOR BIAS IN FIRING DECISIONS

Analyze the data about who you are firing. Are you firing a disproportionate number of employees from systemically disadvantaged groups? If so, take the time to ask yourself honestly if bias or prejudice are skewing your decisions. If they are, figure out what you can do about it.

TRACK WHY PEOPLE QUIT

When you have regretted attrition, you should do everything you can to get them to tell you why. Categorize the reasons why. When trends emerge, figure out what you can do to address them. Track these trends over time. Are you succeeding in addressing the key issues? Reassure the people who left that the truth will not burn bridges, and while you’d love to convince them to stay, that is not the purpose of the meeting. You are there to learn about mistakes that you or your organization made so that they aren’t made again.

If you really want to know why that valued employee has quit, get as senior a leader as possible to do the interview. People usually leave managers, not companies. That manager might be the last person who’ll hear the unvarnished truth. But the manager’s boss? Then the employee might be eager to talk.

This is good management hygiene for all regretted attrition, but it’s especially important when it’s people from historically marginalized groups who are quitting. Investigate why the people you’ve worked hard to recruit and retain don’t want to work for you any longer—whether it’s mistakes you’ve made, mistakes others in your organization have made, or problems endemic to your workplace culture. Quantify it. What percentage of people from historically marginalized groups quit because they have experienced harassment or discrimination at your company? How many left because they’ve experienced bias, prejudice, or bullying? Ask this explicitly in the exit interview. How does this compare to people from historically advantaged groups who leave the company? The data doesn’t necessarily point to a problem; but it does point to the need to investigate. If the investigation reveals a problem, figure out how to fix it!

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