Workers can now be analysed like any other data thanks to some applications of big data AP
Bosses, as it turns out, really do matter; perhaps far more than even they realise.
In telephone call centres, 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, aka 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.
Workforce science, in short, is what happens when big data meets HR
A NEW DISCIPLINE
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 email, 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 behaviour 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 revolutionise organisational 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."
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