The Science of Smart Hiring: Find Great New Workers

Are you finding it difficult to find great new workers for your staff employment? Nobody told you it will be easy. Hiring is hard, as told by The Atlantic.

Every year, millions of Americans are being hired and if they thought getting hired is easy, they're mistaken. Finding great new workers is difficult and The New York Times has it that a little bit of empiricism can help. For example, ten years ago, Google was known for its complex application process and brain-teasers. The reason behind this was because Google was still ironing its hiring process. Ultimately, the company realized that GPA wasn't the answer. The single best predictor, they found out, was absolutely nothing.

That's the main difficulty in hiring - identifying the metrics that predict the employee success rate. So how does one measure effectiveness? Meanwhile, basic credentials like graduate degrees and certifications are valued in applications, but they "have little or no power to explain variation in performance across," one report from NBER details.

So recruiters focus on interview scores instead. But they may be biased in one direction or another - leaning towards the younger or the older, etc. Then some applicants end up with bad interviews. The hiring decision ultimately boils down to the 30 minute interaction.

There is no magic behind hiring, and Google recognizes this. It will always be difficult to predict the performance of an employee.

Hiring is hard, and nobody is very good at doing it alone, whether you're a Google boss, a high-school principal, or a sports general manager. They need help-sometimes in the form of standardized tests, and sometimes in the form of aggregated interview reports. When it comes to identifying the best future talent, groups are better than individuals, data-plus-groups is better than groups alone, and nearly anything is better than brainteasers.

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