Every company’s online application form includes a selection box asking candidates how they found out about the job—from LinkedIn, the company’s website, an employee referral, and so on. Part of the reason for the question is so human resources departments can gather data and optimize the best way to source candidates. At least that’s the idea.
But it doesn’t always work out that way. Candidates overwhelmingly select the first option in the drop-down menu regardless of what it is, says L. J. Brock, chief people officer at the digital currency exchange Coinbase. Brock conducted an experiment at his previous job where he rotated the first choice in the selection box every week—one week it would be Google, the next an email job list, etc.—and every week the first choice ended up being the biggest referral source.
The simple conclusion is that candidates weren’t taking the choice seriously. They were just clicking a box to move on in the application process. But for Brock, the results underscored one of the biggest issues that human resources leaders face in using data to generate insights. “If you don’t have the right systems and processes in place to capture the right data the right way every time, whatever insights you have won’t be real,” he says.
To be sure, the shift toward data-driven decision making in HR, underpinned by algorithms and machine learning, is uncharted territory for most organizations. Organizations collect education, experience, and performance data for employees, of course. But they have little to show in terms of how HR can help drive business strategy from that data.
“The problem lies in the fact that HR functions have tons of data but no real expertise in how to manage and analyze it to create actionable outcomes,” says Deepali Vyas, senior client partner and global co- head of Korn Ferry’s fintech practice.
Vyas says that increasingly, organizations—particularly those in the Fortune 500—are trying to solve the problem by creating an “HR data scientist” role. In its ideal form, the HR data scientist combines employee performance data with personal, environmental, social, and other external facts to create strategies to improve employee experience, cross-company collaboration, productivity, and employee well-being.
Moving past simply analyzing survey results is the next data frontier for HR leaders, says Brock. A dedicated HR data scientist can help generate insights to “direct the actions of leaders and employees,” he says.