But some of the world’s biggest companies are turning to predictive analytics to systematize their hiring practices.
The field of predictive analytics — which forecasts behavior and trends based on large quantities of historical information, or ‘big data’ — has in many ways already become an ordinary part of our personal and professional lives. Predictive algorithms underpin Amazon’s recommendation engine, Twitter’s ‘trending’ hashtags, and the ads served daily to a billion Facebook users.
And so it makes sense that the latest industry to be disrupted by predictive analytics is HR, with its clear interest in entrenching good behavioral practices. Proponents of predictive analytics in HR are betting that just as big data can tell a supermarket manager the optimal place for the candy rack, it can also reveal useful insights about hiring, retention, and workplace management. In its Global Human Capital Trends 2015report, Deloitte was bullish, noting that “as people analytics takes hold, data-driven decisions will become a common theme across all parts of HR.”
Companies from Wells Fargo to Foot Locker have put these tools to work with considerable success. The unimpeachable productivity gains flowing from predictive analytics led Deloitte’s report to a very strong conclusion:
“Organizations should invest aggressively in this new discipline, link it to the rest of the business, and reskill their teams to bring data to work in every major people-related decision.” — Deloitte
Big data meets healthcare recruitment
Healthcare and hospitals are often slow in adopting new technology. But DocDelta, a startup out of NYC, is looking to bring the predictive analytics revolution to clinician recruitment and retention. “Right now, healthcare systems spend billions on staffing practices that are neither scientific nor efficient,” says DocDelta CEO John Dymond. On average every hospital has 15% positions vacant, costing $200,000 per month in lost patient revenue, not to mention the considerable cost of physician recruiters and temp wages while the positions remain unfilled.
“Right now, healthcare systems spend billions on staffing practices that are neither scientific nor efficient.”
DocDelta’s solution is to use predictive analytics to understand the job embeddedness of clinicians: how engaged are they at work, how are they tied to their city, what are their professional aspirations? Assembling dozens of data points, DocDelta says they can predict which clinicians are interested in moving jobs — before anyone else knows about it, even before the clinician signals her interest to the market.
The analytical insights DocDelta offers are extremely valuable to recruiters, who could cut their talent sourcing time (and cost) down dramatically. And not a moment too soon: physician recruitment is an incredibly hot market at present. In its Talent Acquisition Factbook 2015, Bersin reports that in 2015 healthcare firms boosted their recruiting budgets by double-digits in response to an escalating war for talent.
“It’s bloodsport out there,” John Dymond concurred. “The fact is that hospitals and recruiters need data-driven insights to find and retain the best people, and an outdated ATS [applicant tracking system] is not nearly enough to remain competitive.” DocDelta’s clients, which include staffing firms and hospitals, believe that predictive analytics helps them get in front of recruitment problems, and avoid them altogether. Brad Weinberg, an early investor in DocDelta says that “if a hospital could know that their top cardiologist is looking to make a move, they can take action — maybe make the doctor a better offer to stay, or at least start the succession recruitment process early to minimize losses.”