If I Were Running A Company…Face Value

There are two terms HR and recruiting uses a lot these days: big data and “Moneyball.” They both relate using analytics to get an advantage against the competition. The Moneyballization of the workplace with all this data could help in recruiting more quality candidates and HR to build an effective workplace. What big data does is find high-achieving performers and how quickly they learned…but it is more one-sided than you think.

Herminia Ibarra of HBR wrote that recruiters rely on massive open online courses (MOOCs) and gaming to find their talent. What the research found was that test scores were high…but most of them were men. Why the discrepancy?

In both MOOCs and gaming, it is male-dominated with little to no presence of women and minorities. The reason being men have the resources and activities they want to be involve that recruiters “coveted.” Online courses and gaming are basically in the male wheelhouse and it is easy to get data from because the recruiters can see the activities of how each person learns from experience. This does not benefit women because since MOOCs and gaming are male-dominated, why even participate when don’t have one of their ilk? For minorities, it is about access that it hard because the lack of internet connection and broadband in their homes, libraries, and other locations, it makes it hard for them to take classes.

The problem with recruiters who are relying on big data is that most look it at face value. They use big data to forward to the hiring managers and their bosses of the performance scores. It is a recruiter’s safe haven if they are doing their job right. What the bosses and hiring managers won’t see is the lack of participation for women and minorities, and frankly, they don’t care. What these people want is results and if the results are good, why try to change it?

This bring back to what Moneyball truly was: people looking data at face value. Sure, Billy Beane, his scouts, and his sabrmetricians looked at on-base percentage and slugging percentage, but they were they only people, at that time, who looked at that. Now, almost every team looks at on-base and slugging percentage, plus fielding f/x, and WAR (Wins Above Replacement) to go deeper into the stats. Although the Oakland As won the division title in 2002, they did not win their divisional series against Minnesota. Could it be that Oakland was too analytical, like why Peyton Manning has won only one Super Bowl? Pressure? we would never know.

Big data can be a plus for an organization because you have information that could benefit your organization. However, you have to ask the right questions and have the right setup to get to answers that you need. This is why in big data, like in mathematics:

Big data can be manipulative, it is up to us what makes sense.

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Big data can be manipulative, it is up to us what makes sense.

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