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Technology | Unboxed

Big Data, Trying to Build Better Workers

By STEVE LOHRAPRIL 20, 2013

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BOSSES, as it turns out, really do matter — perhaps far more than even they realize.

In telephone call centers, for example, where hourly workers handle a steady stream of calls under demanding conditions, the communication skills and personal warmth of an employee’s supervisor are often crucial in determining the employee’s tenure and performance. In fact, recent research shows that the quality of the supervisor may be more important than the experience and individual attributes of the workers themselves.

New research calls into question other beliefs. Employers often avoid hiring candidates with a history of job-hopping or those who have been unemployed for a while. The past is prologue, companies assume. There’s one problem, though: the data show that it isn’t so. An applicant’s work history is not a good predictor of future results.

These are some of the startling findings of an emerging field called work-force science. It adds a large dose of data analysis, a k a Big Data, to the field of human resource management, which has traditionally relied heavily on gut feel and established practice to guide hiring, promotion and career planning.

Work-force science, in short, is what happens when Big Data meets H.R.

The new discipline has its champions. “This is absolutely the way forward,” says Peter Cappelli, director of the Center for Human Resources at the Wharton School of the University of Pennsylvania. “Most companies have been flying completely blind.”

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Today, every e-mail, instant message, phone call, line of written code and mouse-click leaves a digital signal. These patterns can now be inexpensively collected and mined for insights into how people work and communicate, potentially opening doors to more efficiency and innovation within companies.

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