Here's my take on this Frankensteined assemblage of disjointed data sets they are trying to use (badly) to study the drivers of the gender gap:<p>It’s interesting to consider how different career paths and total time worked can affect compensation - for both men AND women. The topic certainly warrants further analysis.<p>That said, McKinsey’s narrative about their approach glosses over serious data challenges. While it’s clear their analysts made significant efforts (and leaps of logic) to transform suboptimal inputs into a grand, authoritative finding—it’s not clear WHY.<p>Knowing that errors compound with each step of a multi-stage analysis, and without additional visibility into the quality and utility of their source data and assumptions, I'm calling BS on McKinsey’s "calculations". You can read more about the problems a few of us have identified in the comments at <a href="https://www.linkedin.com/posts/sarahjacksonweaver_mckinsey-analysis-of-gender-pay-gap-data-activity-7301227865084231682-iz65" rel="nofollow">https://www.linkedin.com/posts/sarahjacksonweaver_mckinsey-a...</a>
The world would be better off without McKinsey[0].<p>0 = <a href="https://en.wikipedia.org/wiki/McKinsey_%26_Company#Controversies" rel="nofollow">https://en.wikipedia.org/wiki/McKinsey_%26_Company#Controver...</a>