Don’t flaunt your body. Don’t be shrill. Don’t dye your hair “bottle blonde.”
There’s an astonishing list of don’ts for women that appeared in a recent news story about a prominent professional services firm offering misguided advice for aspiring women leaders. Immediately, the story sparked jokes among my colleagues: “Is this shapeless burlap sack too short for work? Should I try to imitate James Earl Jones when I talk to be less shrill? Is blonde hair OK if it’s from a box, but not a bottle?”
While the jokes help alleviate the frustration and disbelief, the real question is how these types of things continue to occur.
A big part of the problem is where we choose to use data to support women in leadership efforts. The good news is that there’s plenty of research to support the business case for women in leadership on the front end. For example, hot-off-the-presses research (paywall) by the Wall Street Journal found that the 20 most-diverse companies in the S&P 500 returned significantly higher share value than their low-diversity peers. Lange Avondjurken
But while companies are using data to support women in leadership at the strategy level, many are failing at the execution level. Once they get buy-in to do the program, they aren’t sure how to build a science-backed program that will actually help women. Thus, they rely on outmoded methods and assumptions in the belief that doing something is better than doing nothing. In the best cases, the program is simply ineffective. In the worst cases, it reinforces negative stereotypes.