Use HR Analytics to Improve Productivity, Profitability

Interest in people analytics is growing, but implementation remains a challenge.
jenel-white

Analytics is a hot topic across many areas of distribution – from inventory management to sales alignment. But for many companies, application in human resources remains a mystery.

That may be changing, according to a report from Deloitte. While there have been some easy, early applications, such as engagement and retention, senior leaders are looking for more "actionable information and insights," Deloitte notes in the 2017 Global Human Capital Trends report.

Seventy-one percent of companies surveyed by Deloitte for the report noted that people analytics is a priority for their businesses, but only 8 percent say they have usable data right now.

While engagement and retention remain critical elements, the tools available can now help track and predict patterns of fraud, analyze overtime patterns to reduce payroll leakage and improve productivity flow by assessing employee time management. Artificial intelligence programs can review video interviews and job applications for honesty and personality to ensure a cultural fit.

"A big trend in 2017 is that these new solutions are business driven, not internally HR focused, challenging HR departments to move beyond their own internal view of data and leveraging people data for a broad range of business problems," the report says.

For example, one sales organization partnered with its HR department to develop a new model around sales productivity to help predict and diagnose problems and determine solutions to those problems, including an improved hiring process.

As with other areas of analytics application, the quality of data is also a core challenge for HR analytics. "Clients tell us the problem requires a systemic solution," a recent Deloitte CFO Insights on this topic notes. Of particular concern is how to develop a system that has appropriate privacy and anonymity policies in place without sacrificing the usability of the data collected.

But as with other areas of analytics, doing it correctly up front and focusing on ensuring clean, usable data in the analyses can pay significant dividends in improved productivity and profitability.

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