When HR leaders look back at 2022, there is a good chance that it will be called “The Year that People Data Analytics Took Off.” Many organizations are increasingly recognizing that scouring data on their employees’ motivations, engagement levels and aspirations is endlessly helpful, given the tight labor market and increased employee expectations. And the organizations that have not yet amped up their analytics are realizing that they had better start—and fast. The people analytic trend that picked up speed in 2022 is expected to continue into next year, as HR continues to face significant recruitment and retention challenges in the new world of work.
HRExecutive spoke with Hallie Bregman, Ph.D, the owner of data analytics consultancy The Bregman Group and a former diversity and data analytics leader for Wayfair, for her take on how people data analytics will be used in the coming year, how it can drive innovation and why certain social media platform owners may wish they had used it for their recent layoffs.
This interview was edited for brevity and clarity.
HRE: What’s the state of people analytics as we close out 2022?
Hallie Bregman: First and foremost, we can’t get enough of the data in an easy, clean and manageable way to draw the insights that would have the most impact. That’s what the majority of people analytics folks are focused on—just the fundamentals.
HRE: I assume larger corporations have a chief data officer who gathers all the data.
Bregman:That’s a big assumption. Corporation size almost doesn’t matter. I think it’s how long they’ve been doing people analytics, and a lot of big corporations have only started in the last year or two.
When folks are starting out, it’s often a manual process and limited in what they can achieve. They spend a lot of time reporting on the basics without demonstrating the major value of people analytics, which is far beyond reporting. Eventually, you may have a head of people analytics who has a few people under them but most teams are not bigger than a few people. It’s rare when you see a team bigger than 10 unless you’re talking about Meta, which just laid off part of its people analytics team because they had 250 people working on their people analytics. That’s absurd. We provide value, but not that much.
HRE: What will 2023 look like in terms of people data analytics from an HR perspective?
Bregman: I don’t think you need bigger teams to have more impact. More resources are always better but if people have the time and space to engage with this work, there’s a lot of value. I think that adoption will continue to increase. I don’t know that it’s a one-year journey. It might be a three-year journey before folks are feeling much more comfortable with people analytics.
HRE: How can people data analytics help when tech companies such Twitter and Meta are laying off tens of thousands of employees at a clip?
Bregman: Hopefully, people analytics was involved from the beginning. As in, where you could say these are people you can’t get rid of because they’re single points of communication. They’re the people everybody comes to ask the question. If you let them go, who will have the answers to those questions?
(These topics also will be explored during HRE‘s upcoming HR Tech Virtual Conference, taking place online from Feb. 28 to March 2. Learn more and register for the free event here.)
There are analytics that can show if two people never communicated before and now you can put them on the same team. Does that lead to knowledge sharing or does that lead to different ways of communicating and becomes a huge challenge? Are you letting go of managers who have high retention? People analytics can show that.
HRE: Speaking of technology layoffs, is this a good opportunity for data scientists to find their next job?
Bregman: I don’t think that firms without analytics teams are hiring them for the first time right now. They’re lean and they have to keep budgets flat. Everybody’s being conservative but [those organizations that have analytics teams] aren’t laying off those people. They’re not the first team to go. Those teams are valuable for figuring out models to maximize people in their business in this particular time. [The can ask] how should we organize and enable teams to work together, how collaborations happen and how remote work is working. These are important, high-level questions that are top of mind for the entire business, especially during a layoff or a shift to remote work.
HRE: Can you give us an example of an organization that does people data analytics right?
Bregman: I was talking to Anheuser-Busch and their people analytics is aimed at building products for the organization. They’re not building insights, they’re building recommendations. Johnson & Johnson is doing impressive work with skills as well.
Uber has done innovative stuff by leveraging these tools and technologies to measure the effectiveness of hybrid work and how it changes work relationships? What does onboarding look like for new hires? What happens when people go into the office; are they by themselves and still on Zoom meetings? Or are they engaging with people face to face? They can get answers for lots of questions because that’s an organization that is thoughtful.
HRE: What specifically do HR leaders need to analyze next year that they’re not analyzing now? Is it still employee engagement?
Bregman: It’s always engagement. Are there different ways to analyze it? Yes, and in more meaningful ways. I don’t think DEI measurement is nearly as mature as it needs to be, for example. Companies have invested a lot in DEI programs and not a lot in DEI measurement other than headcount. If it were up to me, that’s where I would move the needle.
HRE: When you performed data analytics at Wayfair, what was the most surprising thing you discovered?
Bregman: So many things. The difference in performance management language for women versus men, as in how often women were told that they were not confident in opportunity areas, occurred 10 times more often than men. A lot of intervention has been done to remedy that. There was a huge amount of response and reaction but that’s a cool insight. It’s actually quantifiable and we could say that there’s a bias here. It wasn’t surprising but it was validating.
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