Unboxed: Big Data, Trying to Build Better Workers

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.”

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.

Digital technology also makes it possible to conduct and aggregate personality-based assessments, often using online quizzes or games, in far greater detail and numbers than ever before.

In the past, studies of worker behavior were typically based on observing a few hundred people at most. Today, studies can include thousands or hundreds of thousands of workers, an exponential leap ahead.

“The heart of science is measurement,” says Erik Brynjolfsson, director of the Center for Digital Business at the Sloan School of Management at M.I.T. “We’re seeing a revolution in measurement, and it will revolutionize organizational economics and personnel economics.”

The data-gathering technology, to be sure, raises questions about the limits of worker surveillance. “The larger problem here is that all these workplace metrics are being collected when you as a worker are essentially behind a one-way mirror,” says Marc Rotenberg, executive director of the Electronic Privacy Information Center, an advocacy group. “You don’t know what data is being collected and how it is used.”

Companies view work-force data mainly as a valuable asset. Last December, for example, I.B.M. completed its $1.3 billion acquisition of Kenexa, a recruiting, hiring and training company. Kenexa’s corps of more than 100 industrial organizational psychologists and researchers was one attraction, but so was its data: Kenexa surveys and assesses 40 million job applicants, workers and managers a year.

Big companies like I.B.M., Oracle and SAP are pursuing the business opportunity. So is eHarmony, the online matchmaking service. It announced in January that it would retool its algorithm for romance so it could examine employee-employer relationships, and enter the talent search business later this year.

THE penchant for digital measurement and monitoring seems most suited to hourly employment, where jobs often involve routine tasks. But will this technology also be useful in identifying and nurturing successful workers in less-regimented jobs? Many companies think so, and can point to some encouraging evidence.

Tim Geisert, chief marketing officer for I.B.M.’s Kenexa unit, observed that an outgoing personality has traditionally been assumed to be the defining trait of successful sales people. But its research, based on millions of worker surveys and tests, as well as manager assessments, has found that the most important characteristic for sales success is a kind of emotional courage, a persistence to keep going even after initially being told no.

The team of behavioral and data scientists at Knack, a Silicon Valley start-up firm, uses computer games and constant measurement to test emotional intelligence, cognitive skills, working memory and propensity for risk-taking. Early pilot testers include the NYU Langone Medical Center, Bain Company and a unit of Shell, says Guy Halfteck, Knack’s C.E.O.

Article source: http://www.nytimes.com/2013/04/21/technology/big-data-trying-to-build-better-workers.html?partner=rss&emc=rss