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Traditional hiring practices have long relied on intuition and subjective judgment to identify the right candidates. However, forward-thinking organizations are discovering that applying rigorous data-driven methods to talent acquisition can improve both the quality and predictability of hiring decisions.
Start with a clear competency framework
“Thin-slice judgments,” according to Deloitte researchers—like those based on a handshake and brief intro—have historically influenced final interview evaluations. In most cases, the rest of the interview simply confirmed that initial judgment. The problem? Those first impressions do a poor job of predicting actual job performance.
Mark Linnville, head of talent at Garner Health—a platform to help employees find the doctors they need—uses a proactive and systematic method for measuring and refining hiring practices. “There is standard performance data that you are able to track through review cycles, but that is largely too lagging to make a difference quickly enough,” Linnville explains.
Instead, his team focuses on early indicators that provide faster feedback loops. At Garner, they track metrics tied to onboarding processes, particularly “time to productivity,” which allows them to generate quality assessments much sooner and make adjustments to their hiring process in real time.
Mark Linnville, head of talent at Garner Health
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