Under pressure to cut costs and boost productivity, HR is now looking towards big data and analytics to ensure a job well done. Xerox Corp. has cut its attrition rate at one of its call centres by a fifth through analysis of big data (a collection of large and complex data sets spanning four dimensions – volume, velocity, variety and veracity) to sieve through job applications for all its 48,700 call-centre jobs, reports the Wall Street Journal (WSJ).
Applicants for the job take a 30-minute test that screens them for personality traits and puts them through scenarios they might encounter on the job. Then the program spits out a score: red for low potential, yellow for medium potential or green for high potential. Xerox accepts some yellows if it thinks it can train them, but mostly hires greens.
Using algorithms and sophisticated software makes it possible to evaluate more candidates, amass more data and peer more deeply into applicants’ personal lives and interests.
Globally, spending on talent-management software rose to $3.8 billion in 2011, up 15% from 2010, according to research firm Gartner.
Laszlo Bock, a senior vice president at Google Inc. and director at Evolv (a solutions provider that helps companies optimise the performance of global hourly workforces by utilising big data predictive analytics and machine learning), told WSJ that software will supplement, if not supplant, many of the personnel decisions long made by instinct and intuition.
“The initial thing companies like Evolv are looking at is people as they get hired, but over the years this can help companies pick who to advance, who to promote,” he said. “Even at the best companies there’s still a lot of guessing.”