Could screening algorithms lead to better hiring choices?
Is that person a good fit for the job? The decision often hangs on a gut feeling. But that’s changing. Using people analytics, organisations can apply statistical techniques to large datasets about their employees to make more informed recruiting, management and business decisions. The technology can automatically screen CVs to find qualified candidates, identify high-performing workers or pinpoint those most likely to leave.
Results can be counterintuitive. A restaurant chain analysed by McKinsey found staff personality traits influenced branch performance, but friendliness was irrelevant; what mattered was a worker’s ability to focus. Traditional company hiring practices, such as recruiting only from top universities, may be overturned if the data says they don’t work. Automating some recruitment decisions may improve diversity by reducing bias: one company found a CV-screening algorithm approved 15% more women than HR professionals.
The tech saves time and money, though some applications, such as scanning staff emails to track their emotional reactions to new hires or promotions, can be intrusive. And data can only take you so far. Google may have pioneered data-driven hiring, but their director of staffing, Jeff Moore, describes recruiting as “both an art and a science”. So, there’s room for your gut too.
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Image credit: Piero Zagami and Michela Nicchiotti.