People Analytics Can Transform Companies the Way Sabermetrics Transformed Baseball

I pored over Michael Lewis’ “Moneyball: The Art of Winning an Unfair Game” back in 2008. The use of an analytical, numbers-based approach to winning in baseball (called “sabermetrics”) appealed directly to the data geek in me .

This approach also drew a sharp contrast to some of the economic models I was studying at the time, which often made broad generalizations about how people and companies behave in a rational world. So outside of the baseball diamond, how do we understand the real world and the way individuals behave within it? Is it possible to reconcile both the “rational” and “irrational” behaviors that make up each individual, and use an understanding of those behaviors to predict how companies could work more effectively?

During my time as a human capital consultant (read: someone who consults on how to get the right people in your organization, improve their performance, and keep them happy), I saw how much data exists about people in the workplace. And the analysis of that data — called People Analytics — can help us achieve a holistic view of employees, both as a group and as individuals, so we can understand their behaviors and the result of those behaviors. In doing so, People Analytics can help individuals and companies hit professional home runs.

Billy Beane Had Some Advantages That HR Doesn’t

As our data gathering and analytical techniques grow more sophisticated, so does our ability to use those results to transform how we work (or play the game). Then why are only 8% of companies capable of developing predictive models in 2016?

To be fair, HR departments have been using data for decades — looking at metrics dashboards and benchmarking how they are doing compared to others companies. We have 7% annual turnover vs. an industry standard of 8% so that must be good, right? Sure. But it forced HR teams only to look backwards and did not give them enough insight to tell them what to do in the future. It’s like knowing that you keeping striking out, but not having enough information to know how to hit a home run next time.

And HR does want to hit a home run, but they’ve had some disadvantages:

  • Unclear contribution to the bottom line. This is key. HR has traditionally been considered a cost center and until you can prove the return on investment of People Analytics, it’s hard to get approval from your senior leaders. Billy Beane, on the other hand, was able to see wins and losses pretty quickly.
  • HR is hard to quantify by nature. People and their behavior are comprised of a lot of intangibles. Especially when they are not in highly quantifiable roles, like sales. Billy had tons of statistics at his fingertips that had been measured over the years. And a very clear, quantifiable outcome — runs scored per game.
  • People-related data is housed all over the place. With information on performance in one place, and compensation in another, it’s been hard to gather all this data into one place to do meaningful analysis. Baseball stats have been tracked and compiled carefully for years.
  • Lack of resources. Not to beat a dead horse, but again, HR is seen as a cost center. So it may not be the first place for investment in the tools and people needed to gather, clean, and analyze the data to make evidence-based decisions on how we work. Billy, as the senior leader, smartly made the investment in analytics (with some convincing from Jonah Hill’s character).

Once senior leaders understand the huge potential benefits of analyzing “people data,” HR can stop looking to the past, and can start planning how to help individuals and teams win at work.

Focus On the Inputs, Understand the Outcomes

Once the investment is made, the key will be to increase the meaningful data points collected and to organize that data in actionable ways. We can transform organizations by using analysis to predict the future of our workforce — predictive analytics. And then understand today what immediate actions we could take to improve the likelihood of positive outcomes occurring — prescriptive analytics.

Ultimately, it’s ‘garbage-in, garbage-out.’ So we focus on gathering the most meaningful inputs and iterating on those inputs as we learn more. This leads to increasingly accurate predictive insights: which hires are most at risk of leaving the company and why? What are the highest impact ways to motivate your managers and teams? As Jonah Hill’s character said, “what I see is an imperfect understanding of where runs come from.” People Analytics will give us a better understanding of where an organization’s “runs” or “wins” come from. Like Billy Beane of the Oakland A’s, we can use the right data to get the right people on our teams and make sure they are empowered to do what they do best.

We’re not simply looking backward to measure progress anymore — we’re looking forward to activate, enhance, and enable the workforce, one person at a time. Google has been the classic example of a company blazing this trail, but there are many examples to support the presence of an emerging data revolution.

As Michael Lewis said, “if you challenge the conventional wisdom, you will find ways to do things much better than they are currently done.” Better use of data will allow HR and organizations to “do things much better” — meaning data driven decision-making and improved chances of success on the professional field.

Tom Slade is a Product & Data Strategist at Yoi, a new employee success platform built to maximize employee productivity, engagement, and retention. Yoi influences employee outcomes by utilizing predictive and prescriptive data analytics within a workflow automation framework to facilitate the most critical workplace conversations and activities. For more information, click here.