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Only 4% of Companies Successfully Apply Predictive Analytics to Human Resources

HiringApplying data analytics to HR functions generates big returns. According to Forbes, the small percentage of companies who are successfully applying data analytics to the problem of workforce management see stock market returns that are 30% higher than the S&P 500. That’s in addition to other benefits which these companies are receiving as a result of their successful data launches.

However, the same article reports that only 4% of the companies out there have successfully launched and used such programs. Obviously, this disparity represents an enormous opportunity for companies who are still positioned among the other 96%.

Forbes correctly reported that the specific tools that these companies use to evaluate their data has little to do with these successes.

The research shows that while tools are important, the leading companies have invested in other things: sound data management which delivers quality data, business consulting capabilities to focus on the right problems, strong relationships with finance and operational analytics teams, and visual design and communication skills. These are all critical skills, in addition to statistics, data, and math.

In fact, most HR teams tell us they can find statisticians fairly easily (I/O psychologists study statistics) but have a hard time finding project managers, people who can combine “data” and “business,” and people who can translate a “finding” into a program or solution that drives business change.

In this struggle, HR managers are not alone. This is the struggle in every organization and in every business corner. Yet just look at what can be accomplished if this challenge is solved successfully!

If you’re ready to step into the 4% then make sure that you and others in your organization can become the coveted people that businesses need to make the most of data analytics. Start with TMA’s data analytics courses and free webinar, and get the mindset shift that you need to combine “data” and “business” effectively.

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