Job Interviews, Like Dating, Are an Exercise in Irrationality
The solution is from time to time to hire people you don’t think would work out.
Dan Ariely is the James B Duke Professor of Psychology and Behavioral Economics at Duke University. He is the founder of The Center for Advanced Hindsight and co-founder of BEworks, which helps business leaders apply scientific thinking to their marketing and operational challenges. His books include Predictably Irrational and The Upside of Irrationality, both of which became New York Times best-sellers. as well as The Honest Truth about Dishonesty and his latest, Irrationally Yours.
Ariely publishes widely in the leading scholarly journals in economics, psychology, and business. His work has been featured in a variety of media including The New York Times, Wall Street Journal, Washington Post, Boston Globe, Business 2.0, Scientific American, Science and CNN.
There’s lots and lots of research showing that interviews don’t add to the ability to predict how good somebody will be at work. In fact, they subtract from it. And it turns out that if you have a simple statistical model that looks at GPA and SAT and all kinds of other things and you just create that, this would predict some performance, how well will people do on the job.
But if you take that model and then you add an interview to it, you actually do worse. Now why do you do worse? Because you interview somebody that went to the same university than you and say, "Oh, those statistics are not important, what’s important is that he has gone to this good university." And you interview somebody that has the same religion as you and you say, "Oh these things are unimportant, what’s important is he has the right moral fibre, like people from my religion." And you interview somebody else and they are blonde and you say, "They are so attractive, other things don’t matter."
So what happens is that when we have an interview and rely on that interview, we shift our criteria for every person trying to have this flexibility and that first eliminates our ability to be accurate, to have any accuracy, and the second thing, it hinders our ability to learn from experience about what works and what doesn’t work.
The other really interesting thing about interviewing is that we rarely, rarely try to actively test whether our models are correct or not correct. And this is true for both job interviews and romantic dating. Imagine you are interviewing somebody and you don’t like them. Now, you think they’re not going to work out, how would you know? Usually you would throw them out and you will never see how they would work. Right? So you would only take the people that you think will work out, and the people you don’t think will work out, you’ll never see. Under those conditions, you have no way to learn whether, for example, the people you think are worse will actually be better than people you think are good.
Now, what’s the solution for that? The solution is from time to time to hire people you don’t think would work out. Now I know it sounds strange, it sounds crazy and it sounds expensive. And it is expensive. But the idea is, you interview somebody and you say, "I don’t think the person will work out. I don’t think they’re the absolute bottom, but I don’t think they’re that good. But you know what? I’ll hire them. And I will give them a chance and in a year I’ll see whether I was right or wrong." And if you were right and your gut intuition was true from the interview, you wasted salary on somebody for a year, but if you got it wrong, now you might go and say, "You know what, maybe my intuition about who is right and who is wrong are not so good. And let me revisit my whole interviewing process and apply this new learning principle for everybody I meet from now on."
And this is basically what scientists do when they do experiments. We take our intuitions and we put it to a test. And we test the condition that we think will work and we test a condition we think will not work. And it’s expensive and it’s difficult and it’s time-consuming, but without that, we can never really learn what works and what doesn’t work.
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