Yes, I don't think their process is magic. Google gets a good workforce because they are generous and prestigious, which means a lot of good people apply there. And Google is willing to say no to a lot of people in their search for good people. They reject a lot of candidates who would probably have worked out just fine.
> Or, put another way, they choose to accept a high rate of false negatives to avoid false positives.
Which is how it is typically presented because it sounds much better than "reject a lot of candidates who would probably have worked out just fine". It is useful to perceive both the potential value in an approach like this and the shortcomings. Google can absorb the massive expense in man hours, lost opportunity, etc. that comes with trying to craft genuinely predictive interview processes, but a lot of the companies trying to emulate them can't. Too often, interviewees don't realize a process of this sort is stacked against them, and interviewers don't appreciate the negatives of adopting a still-nascent approach that sounds more reliable simply because it is quantitative - and assuming since Google does it it must work.
Interviewing is hard. I wonder if a number of great candidates just refuse to interview with Google because it's too cumbersome? I know a couple of great folks who just dropped half way because they couldn't be bothered with Google's lack of organization and their lengthy process.
Its not like Google pays the best or still has the best workplace. It's a large company with large company politics and red tape.
I'm not sure I believe that, actually. As elaborate as the process is, there are still plenty of false positives. I'm not convinced a simpler process would have produced a materially different outcome.
The trouble with that is it probably makes false positives more likely to slip through because they have to interview more people to fill a position...
Which is unfortunately wrong (unsafe), as it assumes the noise is random.
That seems to be an unproven assumption, and quite likely to be a wrong assumption. For example if good people turn out to be less interested in "honing their interview skills", adding parasitic noise to the signal.
It's more than they're optimizing on a very specific set of skills/experience - the ability to answer a particular type of problem (eg. from "Crack the Coding Interview") on a whiteboard in under 45 minutes.
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