Michael Housman, an economist and managing director of analytics at Evolv, says he thinks work-force science will increasingly be applied across the spectrum of jobs and professions, building profits, productivity, innovation and worker satisfaction.
Evolv, he says, has focused initially on hourly workers and call centers, which capture masses of data on every call and online exchange. Jobs at these centers are often difficult and have very high rates of attrition, routinely as high as 100 percent a year. "We wanted to start where there was a huge opportunity" to make improvements, he says.
Transcom, a global operator of customer-service call centers, conducted a pilot project in the second half of 2012, using Evolv's data analysis technology. To look for a trait like honesty, candidates might be asked how comfortable they are working on a personal computer and whether they know simple keyboard shortcuts for a cut-and-paste task. If they answer yes, the applicants will later be asked to perform that task.
Those who score high on honesty typically stay in their jobs 20 to 30 percent longer than those who don't, Evolv says.
Neil Rae, an executive vice president of Transcom, was impressed with the project's results and plans to use Evolv in the call centres he runs, which employ 12,500 workers.
In the call-center world, Mr Rae says, 5 per cent attrition a month; 60 per cent a year; is stellar performance. Dropout rates are calculated at 30-day intervals, and it takes four to six weeks to train a worker. The cost of attrition; for hiring and training a replacement; is about $US1,500 a worker, he says.
In the project with Evolv, Mr Rae says, Transcom was able to hire fewer people — about 800 instead of a more typical 1000 hires; to get 500 workers who were still on the job at least three months later. The big payoff, he says, should come in cost savings and better customer service with less worker churn in call centres.
"This makes hiring more a science and less subjective," Mr Rae says.
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