On data and the gender gap

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Sheryl Sandberg's new book has, as expected, ignited a debate over women in the workplace. Sandberg contends that many women don't negotiate very well, and this inability is largely responsible for "the gender gap." 

Dice recently reported that the gap has largely disappeared. Yes, salary differences remain between the sexes, but they can be explained by "legitimate" factors like experience.

Looking at the (Hypothetical) Data

Before I became a proper techie, I used to work in corporate HR. I learned a long time ago that everyone's dispassionate about other people's compensation. Once they talk about their own, though, emotions run high. 

So, are men paid more than women? And are there mitigating factors?

Note that, in this post, I use hypothetical data to make a point.

Looking at the average salaries for programmers, there is in fact a legitimate difference between men and women of about eight percent:

df1

But macro-level statistics may mask perfectly valid reasons for this difference. Perhaps the generic title of programmer obscures differences in skills. In 2013, knowing how to code in COBOL isn't necessarily as valuable as knowing PHP, right? Or what about experience? All else equal, programmers with more experience might make more than those new to the field, irrespective of gender.

Throwing in years of experience, you see that the gender differences are much smaller, even non-existent in some cases:.

df2

Looking at the data above, you'll notice a clear outlier here. The guy with seven years of experience makes the most money out of everyone. Perhaps he has a unique programming skill? A good recruiter? Maybe he knows something about the VP's extracurricular activities and gets a little extra to keep his mouth quiet.

Regardless of why, this outlier can throw off the numbers for everyone if the sample size is small. So, is it?

df3

In short, yes. If we were talking about 11 hundred or thousand, then one outlier would have a negligible impact. But with 11, each data point has a disproportionate impact.

Simon Says

I'm not saying that some level of gender discrimination doesn't exist today. (This post used simple, hypothetical data). However, before making any controversial statements about any issue, make sure that you've looked at some data first.

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About Author

Phil Simon

Author, Speaker, and Professor

Phil Simon is a keynote speaker and recognized technology expert. He is the award-winning author of eight management books, most recently Analytics: The Agile Way. His ninth will be Slack For Dummies (April, 2020, Wiley) He consults organizations on matters related to strategy, data, analytics, and technology. His contributions have appeared in The Harvard Business Review, CNN, Wired, The New York Times, and many other sites. He teaches information systems and analytics at Arizona State University's W. P. Carey School of Business.

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