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Big data: trying to build better workers

Steve Lohr (via NYT/ AFR) | April 22, 2013
Big data adds 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.

Companies view work-force data mainly as a valuable asset. Last December, for example, IBM completed its $US1.3 billion acquisition of Kenexa, a recruiting, hiring and training company. Kenexa's corps of more than 100 industrial organisational 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 IBM, 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.

 

ANALYSING TALENT

Tim Geisert, chief marketing officer for IBM'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 behavioural 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 CEO.

Google, not surprisingly, is committed to applying data-driven decision-making to human resource management. For years, candidates were screened according to SAT scores and college grade-point averages, metrics favored by its founders. But numbers and grades alone did not prove to spell success at Google and are no longer used as important hiring criteria, says Prasad Setty, vice president for people analytics.

Since 2007, the company has conducted extensive surveys of its work force. Google has found that the most innovative workers; also the "happiest," by its definition; are those who have a strong sense of mission about their work and who also feel that they have much personal autonomy. "Our people decisions are no less important than our product decisions," Mr Setty says. "And we're trying to apply the same rigor to the people side as to the engineering side."

Evolv, a San Francisco start-up, uses data science to advise companies on hiring and managing hourly workers. Evolv is sharing its data from clients; data that are stripped of personally identifying information and demographics like race and sex; with researchers at Wharton, Yale and Stanford. (This column's first two examples came from Evolv's data and analysis.)

 

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