People Analytics: Where Data Science Meets HR

For all its buzzword status, it’s difficult to hype up data science.

90% of the world’s data–taking into account our entire timeline, billions of years back–was amassed over the past few years. The evidence is right in front of us: we can spend our entire lives clicking on every webpage, and we’ll never get to the end.

New content is being created every second. The smallest things we do–our purchases from a certain shop, how many seconds we’re late to work–get measured and tracked.

The emergence of data science

This huge, overwhelming mass of data that we’re swimming in could have been treated as a mere side effect of technology, but human beings decided to turn it into an opportunity: wrangle insights out of these data so we can make better decisions. From there, data science was born.

Data science is a notoriously lucrative industry. Aside from how demanding it is to learn–it’s a fusion of programming, math, and deep business knowledge–it also provides significant leverage for companies that invest in it.

Its traditional domain has been fields that naturally generate a lot of numbers, such as banking and sales, but it’s already being used by companies to optimize as many of their processes as possible. This includes HR.

Unconventional partners: data science meets HR

The intersection of data science and HR is interesting because of the subject matter: people.

Human behavior can defy logic, and there seems to be a vast disconnect between numbers, graphs, spreadsheets and real, flesh-and-blood people. HR demands a huge amount of emotional intelligence, empathy, intuition; data science is more comfortable with clean, precise logic.

Because of this difference in approach, the combination is especially powerful: you get a well-rounded perspective of the people in your organization.

Moreover, human capital is always behind a company’s success: figure out how to improve employee engagement or recruitment, and you drastically up the entire company’s performance.

However, people analytics isn’t as mainstream yet. HR is practically a minefield of data, from employee profiles to long-term retention rates, but for data to be analyzed, it has to be “clean.” Most companies don’t have reliable data (or you’d have to sift through lots of paper to extract them), although automated systems are helping with this.

71% of companies want to prioritize people analytics, but this doesn’t carry over to actual practice. It’s a chance, then, for competitive advantage. Mike West goes as far as  to say that companies not taking advantage of people analytics will get crushed by companies that do.

People analytics in action

Google is a great example of a company that leverages people analytics.

For one, their entire hiring process is data-driven. They already have an algorithm that assesses hirability based on various test scores, they’ve figured out the best way to interview, and they even collect feedback from new employees to improve onboarding.

They also conduct initiatives such as Project Oxygen and Project Aristotle, which are based on intensive study of their own teams.

Project Oxygen determined the eight characteristics of great leaders, and Project Aristotle analyzed what makes a great team. Both projects came up with surprising insights that informed companies all over the world.

Conclusion

The potential of data science for your organization is unlimited–and still untapped, as of the present. This is especially true with people analytics, which can answer relevant problems such as “Why are these employees quitting?” and “What’s the best way to form teams?” By making the most out of your people, you can give your company’s performance a significant boost.

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