December 21, 2016 - Susan Rojo | Storytelling with Data

Data Win: Moneyball Your Hiring for Competitive Edge

Businesses using big data to win a competitive edge over their competition is nothing new. Rarely are there functions within organizations that don’t have a data component to them. Easily-quantifiable areas of business like sales, marketing, and operations have long used customized analytical systems to tweak business processes, planning, and procedures with the goal of increasing profits. As each new business function discovers, adopts, and implements big data analytics and visualization, data-savvy business leaders look for the next area that can potentially be boosted.  Moneyball

Over the last decade, with the example of Billy Beane’s Moneyball hiring “wins” as inspiration, heads of human resources departments have joined the quest for big data insights to guide their businesses. With hundreds of millions of workers in the US alone, payroll is often the biggest expense a company incurs. Hiring, firing, and promoting well can have a big impact on the bottom line. Even focusing just on hiring, the potential benefits are huge. Finding and hiring the right candidate for an open position has traditionally been done through posting a job description, sorting through an avalanche of resumes, conducting phone and in-person job interviews, tests, reference calls, and negotiations. Imagine having data to help streamline and improve the success rate of identifying the best candidates at the best time for them to be successfully recruited and hired at the optimal salary for a win-win position.

The idea behind Moneyball and the Oakland Athletic’s successful use of their players was to find new insights about the candidate pool and make data-informed decisions about who to hire and where to play them. The use of data analytics wasn’t new to baseball. People had been collecting stats on baseball for over a hundred years. The secret to the “Moneyball” approach wasn’t just running stats. It was about discovering the hidden value in employees that no one else (read “deep pocket” MLB teams) was going to pay big bucks for and taking advantage of that. The important point was to use data to maximize the human potential at their organization.  

While some companies like Google and Starbucks have embraced the use of analytics in human resources with varying degrees of success, most organizations still rely primarily on gut feelings (whether they admit it or not) to hire, fire, and promote their employees. When it comes down to it, people fear that the “human” in human resources is being taken away when data analytic are introduced.

Evan Sinar knows a thing or two about the crossroad of human resources and data analytics. He’s the chief scientist and vice president of Development Dimensions International, a company focused on developing, growing, selecting, and identifying leaders. In the latest edition of our Hadooponomics podcast, he discusses the many issues inherent in bringing data analytics to human resources departments. One of the more interesting aspects of bringing data analytics to human resources is the pull between the data and gut instinct of an expert.

“There’s been an immense amount of research into showing the inputs to decisions. And then if you track the effectiveness of those decisions, what’s the role that an algorithm or a formula can play versus expert judgment sitting on top of that.  And the main finding that you come up with is that, over time, the algorithmically driven decision will almost always be more effective.  But that doesn’t mean in every case it will be because there’s always a role for expert judgment.”

It might sound harsh to replace gut instincts with data-backed decisions, but the ability to make our conclusions better by having data to support them makes good business sense. At the same time, data is worthless without asking the right questions. Finding the right questions to ask takes expertise and creativity. Interpreting the data and communicating those insights in a way that makes sense to the organization also takes creativity that can’t yet be found in an algorithm.

To hear more of Evan Sinar’s commentary, check out: Hadooponomics Episode 17 – Data and Decision Makers: The Human “Resources” for Big Data in HR. The Hadooponomics Podcast series is produced by Blue Hill Research in partnership with Arcadia Data. You can listen to prior episodes here.


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