In Hiring, Algorithms Beat Instinct

You know your company inside out. You know the requirements of the position you need to fill. And now that HR has finished its interviews and simulations, you know the applicants, too–maybe even better than their friends do. Your wise and experienced brain is ready to synthesize the data and choose the best candidate for the job.

Instead, you should step back from the process. If you simply crunch the applicants’ data and apply the resulting analysis to the job criteria, you’ll probably end up with a better hire.

Humans are very good at specifying what’s needed for a position and eliciting information from candidates–but they’re very bad at weighing the results. Our analysis of 17 studies of applicant evaluations shows that a simple equation outperforms human decisions by at least 25%. The effect holds in any situation with a large number of candidates, regardless of whether the job is on the front line, in middle management, or (yes) in the C-suite.

by Nathan R. Kuncel, David M. Klieger, and Deniz S. Ones

Full Story: http://hbr.org/2014/05/in-hiring-algorithms-beat-instinct/ar/1

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