Why Hasn’t HR Embraced People Analytics?

The backbone of any successful business is its employees. In fact, according to a global IBM survey, 71% of CEOs say human capital is a key source of competitive advantage. So, it should be no surprise that managing HR-related data is a critical aspect of any business. Why then, has HR analytics progress been so slow?

There’s been plenty of reasons why HR analytics should be more popular:

  • Decades of research
  • Years of practical tool building
  • An exponential increase in available HR data
  • Plenty of evidence indicating that improved HR and employee management leads to stronger companies

Yet, only 15% of execs surveyed by Harvard Business Review (HBR) say they use predictive analytics based on HR data, and only 5% of big-data investments have been in HR analytics, according to a study from Tata Consultancy Services.

That doesn’t mean there isn’t any interest. Of the same execs surveyed by HBR, 48% predicted they’d be using HR-driven analytics within two years.

Researchers Wayne Cascio and John Boudreau recently considered how HR analytics can become more user friendly, and hopefully become more popular. They identified several “push” and “pull” factors that could impact how HR uses big data to manage talent.

‘Push’ for Impact

Cascio and Boudreau identified four elements they believe would “push” HR analytics to audiences in an impactful way. They advise HR leaders to present HR data with the following factors, which they’ve dubbed the “LAMP elements,” in mind:

  • Logic. HR leaders should highlight the connection between talent and organizational success. This could involve using data to link demographic diversity to innovation, or showing how bottlenecks in the talent pipeline could be affecting employees’ career paths.
  • Analytics. It’s not enough to present raw data. Relevant techniques and tools must be used to transform data into interesting and actionable insights.
  • Measures. Analytics are only as good as the raw data being put in – put “garbage data” in, and you’ll get bad insights out. HR leaders must create accurate and verifiable numbers and indices that’ll turn out actionable results.
  • Process. Once the analysis is complete, HR leaders must find the best way to present their findings to interest and motivate decision makers. That means considering communication channels, timing and presentation techniques.

‘Pull’ of Well-Presented Analytics

Cascio and Boudreau went on to identify five “pull” factors HR leaders will need to consider once they’re able to use HR analytics.

For decision makers to view insights from HR analytics in the right light, they must be:

  • Timely. The results must be delivered at the right time and be in the right context – which should be made clear.
  • Valuable. What will decision makers do with the analysis? Its inherent value and usability must be made apparent.
  • Credible. The decision makers will want information from HR analytics that represents the “real world.”
  • Impactful. The analysis must be worth decision makers’ time and attention, which means its impact should be large.
  • Ongoing. The decision makers need to understand how this information will affect their decisions and actions moving forward.

Better Analytics, Better Performance

One of the major aims of HR analytics is to educate execs about how their human capital-related decisions affect the business.

A survey conducted by Boudreau and another colleague, Ed Lawler, asked companies to rate a number of positive outcomes of adopting an HR analytics system. The companies that rated educating decision makers on the impacts of their HR decisions highly were consistently associated with:

  • A stronger HR role in strategy
  • Greater HR functional effectiveness
  • Higher organizational performance

In other words, those who put HR data and analytics to effective use were able to see multiple payoffs, including higher overall company performance.

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