Time to say “out with the old and in with the new,” not just to last season’s styles, but to your approach to people analytics, too.
People analytics are good for more than just “creating facts”—they can help inform strategies and drive innovation, according to Cole Napper, VP of research at labor market research firm Lightcast and author of People Analytics: Using Data-Driven HR and Gen AI as a Business Asset.
“I’d say 80% to 90% of what is people analytics today is just creating facts. ‘How many people do we have? How many people left? How many people did we hire? What are the demographic characteristics?’ and not much beyond that,” Napper said. “We’ve invested in a space as an HR function to be more data-driven for 10, 15, 20 years, and they don’t have much to show for it.”
Napper chatted with HR Brew about how to get the most out of people analytics, especially in the age of AI.
This interview has been edited for length and clarity.
What will HR pros learn from your book?
I really tried to focus on, “What are the challenges that I’ve had? What are the ways to do HR and people analytics, specifically in HR, effectively, and cutting through all the BS?” Because there’s a lot of talking points where I’ll hear, “People are your greatest asset,” and then companies don’t operate any differently…What does it really mean to treat people as an asset? What does it really mean to use AI effectively in 2025?...What is HR even going to look like in five or 10 years if AI truly proliferates the way we think?
What are examples of shortcomings with people analytics?
Let’s take the hardest one first, and that’s data-driven decision making. I think very few people are making data-driven decisions at all. Now, I think that there are data-informed decisions that get made…A lot of what has been called people analytics, up until this point, was actually what I call “creating a shared set of facts.” So analytics, in my opinion, is focused on the future, focused on diagnosis, focused on prediction, focus on prescription.
There’s a generational shifting of the guard in HR that’s going on right now…You have more of the folks who are digitally-native, and eventually going to be AI-native professionals, in the HR space that are eventually going to be holding chief people officer/CHRO roles, and that’s not really the case today, and it hasn’t really been the case, historically speaking…I think it’s time for fields like people analytics to step up to be the thing that’s driving the future…Being a thermostat, rather than a thermometer that just goes up and down with the temperature.
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What else should HR pros know about people analytics in the future with AI?
There’s a whole section in the book I call, “Is people analytics a luxury? Is it just a phenomenon?” Like I chose some charts that show the relationship between the growth of people analytics and low interest rates…From roughly 2012-ish to roughly 2021-ish, where there was a period of functionally zero interest rates for corporate borrowing…What you see is the second interest rates started to go up, people analytics headcount started to go down, and so the question you have to ask yourself is: “Is this just the new designer purse for HR, that everybody wanted to do it because everybody else was doing it?”...If you only talk about it theoretically, you don’t put it into practice, what does that mean for an organization? What it means is it was a luxury item, and they were treating it as such. When times got tight, they were going to cut back.
People analytics needs to be focused on helping businesses understand their cost structure. If you go to any CEO right now, they’re trying to say, “How do we take costs out of the business? How do we be more efficient? How do we be more productive? How do we be more innovative?” And, people analytics historically has not focused much of their effort in that space, and so one of the ways that AI helps is, you can produce people analytics at a lower cost structure by having AI be that leap frog or be that force multiplier for a people analytics function. So, maybe historically, you needed 50 people and a $15 million budget to do people analytics effectively. Maybe now you could do it with AI technology and five people what 50 people used to do.