|February 23rd, 2012|
Interviewing programmers at work we ask technical questions that require knowledge of algorithms and data structures as well as coding on a whiteboard. It's the best way we know to evaluate candidates, but how good is it, really? It favors confident people who can think quickly on their feet, are comfortable showing their work verbally, are strong in an expressive language, and have done similar interviews before. It doesn't test ability to focus, conscientiousness, code reading skills, or patience. It's definitely useful, but could we be doing something better?
The real problem here is minimal feedback on whether we're testing the right things in an interview. If we decide not to hire someone we don't get any further indication of quality, while if we do decide to it's not for months later that we can tell how good they really are. With a tiny number of training examples for "chose to hire" and none for "chose not to hire", how do we get good at picking the right people? We need to start getting more feedback on how good the interview process is at predicting what candidates would be good.
Companies vary in their interview practices, and you expect the ones with the best methods to get better employees for their money. Those companies should have a competitive advantage so a randomly selected successful company is probably doing better interviewing. A company's interview ability is only one of many contributors to success, however, so this might not tell us much.
Companies with good people probably do better, so instead of hiring you could look for successful companies and buy them for their employees. This makes much more sense with tiny companies (startups) because there's much less noise. This is really expensive, though, so how can we tell if it's worth it? Really, this is just another hiring method we'd like to compare.
The simplest solution would be to start randomly hiring some of the people who failed the interview and then several months later see how well interview success correlates with performance. If you keep good notes you can check how well each of the different aspects of the interview and the candidate's background predict performance. The problem is that if our interview process is already working well we end up hiring a lot of bad programmers we wouldn't have otherwise. Sample size is also a problem.
More complicated, a pair of companies could cross-interview. Two companies that had similar ideas of what makes a good employee could each interview a bunch of the other company's people. Then they could see how well their interview rankings predicted the other company's performance reviews. You would need to be careful, though, because this might lead to lots of poaching. A big enough company might be able to do this internally.
I'm not very happy with any of these ideas, but I do think something along these lines would be very valuable. When you can measure results and test improvements it's possible to move quickly to a much better way.  Reliably identifying the employees who would help your company the most would be huge.
 We do this all the time with A/B testing.
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