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Your assumptions fall apart of you consider that it's not all skill, part of it is random. You're falling into the same trap. You think someone is better when

Your assumptions fall apart of you consider that it's not all skill, part of it is random. You're falling into the same trap. You think someone is better when in all probability they got luckier. And you think that picking someone you think is better will statistically get you a better person when that's not true if credentials are highly luck based. It's like buying lotto tickets from a gas station that's produced more winners in the past. I'm saying your measurements aren't going to be any better than whatever percent of "skill" is randomness. CEO candidate 2 went to a better school but you don't know that it was his grandpa's alma matter who pulled some strings. Candidate 3 might be a multimillionaire but it's because he got a settlement from a malfunctioning ski lift when he was 10. A lot of the "signals" companies use to determine if somebody would be a good leader or employee are 100% luck based. You could statistically pick a worse candidate every time that looks betters if you're looking at the wrong signals.

wegs 6y ago
They don't fall apart. You need to look at it as expected values. Most signals are not 100% noise, but e.g. 90% noise and 10% signal. If you have a candidate from Harvard, it's a mixture of ALDCs and really smart people with some bias for policies like affirmative action. You might not know what you're getting, but there are odds of scoring that genius. Ditto with most other low-quality signals. And statistically, you do get someone better than a random schmuck off the street. I mean, the processes are noisy, and perhaps 10% of your workforce might make a better CEO, but you have no way of finding those 10%. (And the noisy signals problem in hiring isn't specific to CEOs).