Advocates of Big Data analytics often cite their craft as the antidote to gut decisions, arguing more rational, data-driven reasoning is now within the reach of businesses. At Johnson & Johnson ($JNJ) they are putting the idea to the test, notably by digging into their employment data to support the hiring of fresh college graduates over industry veterans.
The events, which were outlined in a Wall Street Journal feature, are a textbook example of how data are butting up against accepted wisdom. External recruiters provided the accepted wisdom, telling J&J to favor experienced industry staffers over new college graduates because they deliver better value over the long term. In the 2012-2013 school year, J&J managers, with the words of recruiters ringing in their ears, slashed their hiring of recent graduates by 10%. The move led Doug Grant, head of J&J's people analytics team, to question whether data supported the decision.
In the past, companies lacked both the raw data and the number crunching capabilities to answer such questions. But Grant was able to round up data on 47,000 J&J employees, divide them up into new graduates and experienced hires and analyze whether one group outperformed the other. What Grant found torpedoed the recruiters' assumptions. Performance levels were similar across both groups. And new graduates stayed at J&J longer and were more likely to win promotion. "[The data] dispelled a myth in our organization," Grant said.
Having dispelled the myth, J&J has set about revising its hiring practices. Recruitment of fresh graduates jumped 20% last year, giving J&J the makings of a workforce that--if the data prove to be reliable--will stay at the company for a substantial period of time. J&J attributes its ability to keep young people at the company to its two-year leadership program, in which it aims to steep new hires in its corporate culture and give them connections to peers and mentors.
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