Gender parity initiatives are not working.”
That’s the finding of a survey conducted by Bain and Co. in association with the Harvard Business Review (HBR) that has just landed on my desk. It’s interesting that one of the authors of the study is the redoubtable Orit Gadiesh, one of the finest management thinkers of our times and chairman of Bain and Co.—one of the few women to rise to the top of a multinational consulting firm.
The study has lots of interesting details—Mint will carry a detailed charticle on it next week—but there are a few findings that stand out: Women disappear as they “climb rungs up the corporate ladder”; “only 3% of Fortune 500 companies had a female CEO in 2009”; women make up only 12% “of the boards of FTSE 100 companies” in Europe; and that a full fourth of these companies still had “all-male boards”.
Illustration: Jayachandran / Mint
There is one finding that I will mention here, one that is very disturbing: “A 5% decrease in female retention, after 10 years, results in the equivalent of wiping out the benefits of increasing female recruitment from 30% to 50%.”
I know the number in this case is nowhere close to 5%, but for some reason I thought of ICICI Bank where several high-profile senior women executives had left around the same time.
I do think companies are missing a trick by not making it possible for enough women to rise to the top. Since we all know that rising to the top of an organization is equal parts skill and chance, let’s look at this mathematically. Given that there are as many women as men in the world, and assuming there is an equal probability (say 0.33%) of finding a smart woman (in any universe of women) as there is of finding a smart man, then a company that discriminates against women, actively or passively, either at the hiring stage, or at a subsequent stage, is lowering the probability of staffing itself with smart people.
Let me explain this with numbers.
A company has a universe of 10 women and 10 men to hire/promote.
In any group of 10 men, there will be three smart ones (continuing with our assumed probability).
And in any group of 10 women there will be three smart ones.
So, if the company ends up hiring or promoting five people out of this group, four men and a woman, it would have made two mistakes: one of the men hired isn’t smart; and two smart women have been overlooked. (I am aware that there is one basic error in using probabilities thus, but treat the example as illustrative, not mathematically perfect).
If Bain and HBR were to conduct a similar exercise in India, they are likely to find the situation in India far worse than in the US or Europe (despite the surfeit of “Power Women” listings that this writer helped start in a previous avatar). Even a casual perusal of these listings for the past few years will show that there are few new names. And the worst offenders are companies in areas such as software (despite the large number of women engineers the country churns out every year), pharmaceuticals and services—not because their sex ratios are any lower than those of, say, car makers or petroleum refiners, but because they have more of an opportunity to hire and promote women and haven’t really done so.
Just for the record, Mint is an equal opportunity employer and has roughly as many men working for it (in the newsroom), as it does women. There are also three women in Mint’s 11-member editorial leadership team. The interesting thing is that we didn’t achieve these numbers by consciously hiring women; we did so by simply focusing on hiring smart people. Which means there is some practical benefit to the math I described earlier in this column.