Google's Research on Interviewing Technical Candidates

Yesterday's New York Times has a good article on Google's analysis of what works and what does not work when interviewing candidates for technical jobs. This paragraph closely matches my experience:

Behavioral interviewing also works — where you’re not giving someone a hypothetical, but you’re starting with a question like, “Give me an example of a time when you solved an analytically difficult problem.” The interesting thing about the behavioral interview is that when you ask somebody to speak to their own experience, and you drill into that, you get two kinds of information. One is you get to see how they actually interacted in a real-world situation, and the valuable “meta” information you get about the candidate is a sense of what they consider to be difficult.

I have interviewed candidates this way for years, and I can't recall ever being wrong in my assessment of a developer's general intelligence and technical skills. However, I have made mistakes! In particular, this method doesn't necessarily give you a good indication of how well the candidate will get along with other members of the team, and whether or not they will behave professionally. I'm not as good at assessing that as I am at assessing technical skill.

Unsurprisingly, Google also found

[...] that brainteasers are a complete waste of time. How many golf balls can you fit into an airplane? How many gas stations in Manhattan? A complete waste of time. They don’t predict anything. They serve primarily to make the interviewer feel smart.

The article doesn't mention anything about whiteboard coding, but I also find that useful in technical interviews.

I have to disagree with the headline, however. While big data might not be able to tell you who to hire, it clearly told Google that they were doing it incorrectly!