The Future of HR Analytics: Q&A with Workday’s Adeyemi Ajao

From predicting which high-performing employees are at risk of leaving to helping recruiters source the right talent, analytics are revolutionizing how HR operates.

We sat down with Adeyemi Ajao, VP of technology product strategy at Workday during the annual HR Technology Conference & Expo, shortly after he participated in a panel discussion on the future of HR analytics. Ajao shared his thoughts on what business analytics can learn from the consumer web, the importance of developing people-friendly analytics, and whether HR robots are in the future.

Why is HR analytics such a hot topic?

Ajao: Analytics are much more prevalent today than they were even a few years ago. As consumers, we use analytics five to 10 times in the first hour we’re awake—things like weather forecasts, Google Now scheduling our day, reading what’s recommended by Facebook, and following driving directions from Waze. We are now at the point where people expect this same level of analytics in the workplace.

We also have more data today, and the more data there is to analyze the better the results will generally be. We can do things today with these volumes of data that weren’t previously possible.

Data bias is something that has been discussed recently when it comes to analytics. What needs to be done in order to remove or limit data bias?

Ajao: In order for any analytics technology to answer a question, the question itself—the algorithms—and the data used to answer it both need to be solid. As data scientists we can build very sophisticated algorithms, but if the data going into the algorithms itself has a bias, then the best analytics engine in the world can’t help.

People who are preparing data for analysis need to make sure there isn’t a bias inherent in the data. As a simple example, if I’m trying to predict what the most popular song will be this month, and I omit all the rap songs simply because I don’t like rap, then the analytics engine can’t really make a good prediction. Preventing data bias is about ensuring that the broadest, most correct data set is available for analysis.

On the HR Tech panel, there was some discussion about there being two sides to the HR analytics coin. Can you expand on that idea?

Ajao: In order for analytics to provide actionable insights or recommendations, there needs to be an “answer” from the technology. That answer then needs to be communicated in a way that a human being can use to achieve a business outcome.

It’s great to spend all this time crunching the data and writing the algorithms, but if we forget about the person or lose the human element, then we’ve forgotten the goal of analytics: making someone’s life easier. Or put another way, we need to put the person back in personalization.

The HR Tech panel moderator asked if robots are going to take over HR. Are we approaching a point where technology can replace the judgment of HR professionals?

Ajao: HR robots aren’t coming to take anyone’s job. The science behind some of these data models is pretty sophisticated, and HR professionals sometimes can be a bit taken aback. Think of it this way: If recruiting recommendations keeps a recruiter from having to sort through 10,000 resumes and instead allows her to focus in on the 50 that are most likely to be a great fit for the job and culture, that’s really powerful. Analytics allow that recruiter to hone in on the most important and strategic aspects of the job.

I like to say that the result of analytics is the beginning of the conversation. That’s where human intuition comes in and makes judgments. Does this make sense? What is it telling me that I didn’t know before? What are the next steps?

Analytics are a tool to drive better business outcomes, with HR at the core of those decisions. Analytics augment human judgment and intuition—they don’t replace it.