HR by the numbers

A fascinating post on Slate about how Google HR applies engineering principles to its job:

After crunching the data, Carlisle found that the optimal interview rate—the number of interviews after which the candidate’s average score would converge on his final score—was four. "After four interviews," Carlisle says, "you get diminishing returns." Presented with this data, Google's army of engineers was convinced. Interview times shrunk, and Google's hiring sped up.

That rings true with me. The banks in particular are notable for grilling candidates with ten or more interviews, often back-to-back in a single day. The implication from these findings - and remember, Google has engineering offices all over the globe, so it's not just confined to the West Coast hippies - is that the only benefit of this interviewing approach is as a rite of passage or test of endurance, because it sure doesn't seem to be optimised for finding people whom interviewers agree are suitable. You'd think that a bank would value the time of its interviewers more.

Google have something called PiLab ("people and innovation lab") that seems to be dedicated to running HR experiments on Google engineers and interviewees. They seem to be ruthlessly data-driven, and I'm reminded of the maxim "Talk is cheap, show me the code". I wonder how many HR organisations that I've encountered would handle that kind of demand for proposals backed by (relatively) hard data and stats. I suspect most of the would be curled up weeping under their desks by the time the engineers were dissecting the ludicrously unfounded stats in the second paragraph of their report.

They even determined that good managers, defined by those getting good 360-degree rankings, make a measurable difference to their teams:

When analysts compared the highest- and lowest-performing managers, they found a stark difference—the best managers had lower attrition rates (meaning fewer people left their teams), and their teams were much more productive across a range of criteria.

Of course, with that knowledge, the trick is finding and hiring or promoting people who are going to be those good managers; there's always the risk that a whiff of power might make an otherwise engaging and competent recruit go psycho.

The more mischievous part of me wonders how many of the facts put out by Google in this article are true, and how many are false (or, more likely, "true but misleading") to get Facebook, Cisco, Apple, IBM et al to run down blind alleys in their own recruiting/HR practices...