Josh Bersin on HR Analytics 2016: Moneyball Meets the Workplace

predictive analyticsAnalytics, as popularized by the best-selling book and baseball movie Moneyball, is the art of trying to make better decisions based on data. Talent management expert and Forbes contributor Josh Bersin calls analytics one of the most significant trends affecting employers in 2016.

The newest XpertHR podcast features Bersin, the principal at Bersin by Deloitte, Deloitte Consulting LLP, and his many insights on how employers can use data to their advantage in the workplace.

“Most hiring managers will hire somebody like them,” says Bersin. “But if you analyze by data, you may find those who went to the best colleges and have the best GPAs are not the best candidates.” He explains that data can ferret out the unconscious biases implicit in our nature and really improve a company’s business performance.

“Every company on the planet has to do a few basic things,” notes Bersin:

  • Hire people;
  • Decide who to promote;
  • Decide who gets more money each year; and
  • Make decisions about compliance issues.

All of those decisions, he adds, are in many cases being made by managers solely by gut feel. Bersin points out that most employers already use analytics to a great extent with customers, such as showing why they leave or return. But he says they still don’t do it enough with their employees. Nonetheless, Bersin observes that HR departments are getting increasingly serious about analytics.

According to Bersin, that’s because there are big ‘easy wins’ in analytics for employers. As an example, he recommends background analysis of people who stayed the longest at the company and were the most successful.

Retention

Another big win is with retention. For instance, he notes that some employers have built data models to analyze why people leave, most notably showing that those who had a commute of one hour or more were the most likely to depart.

Unplanned absences

Analytics also can help a company in other ways, such as predicting unplanned absences, says Bersin. Speaking of one large automobile plant, he asserts that statistical analysis revealed the following tidbit: “People who had performance appraisals the week before, many of them didn’t show up the following week.” With the data in hand, he points out that large employers can ensure they have extra staffing at certain points during the year to avoid getting caught shorthanded. But that’s not all.

Theft Prevention

Bersin says effective use of analytics can also predict theft. He cites a financial services company in Canada that found it could forecast how likely theft was to occur by the distance between a branch and a branch manager. “If the manager didn’t visit the branch on a regular basis, there would be more theft,” notes Bersin.

No Quick Fix

All of these observations make it sound like it’s an absolute no-brainer to rely on analytics. But the biggest misconception in this area is that data alone is enough. “It takes time and money to get good at this,” says Bersin, adding that companies that are serious need to hire a statistician. “This does not happen overnight.”

The California talent management expert concludes that you cannot just build a big database and see what it says. “You can’t let HR systems have poor data in them.” Instead, Bersin advises, “Start small. Pick a problem that’s easy to understand” where you know there’s likely a high return on investment which in turn will make the case for further investment.

For a complete rundown of Bersin’s analytics tips, tune into our latest podcast. And for more from Bersin and his team on what’s trending in HR, not only in analytics but beyond, Deloitte’s Global Human Capital Trends 2016 survey is not to be missed.

Are there other ways your company is using analytics to help the bottom line? Let us know by leaving a comment below.

 

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