Getting Real About Data-Driven HR

Claire Monroe

Welcome back, everyone, to The Science of Leading. I’m Claire Monroe, here with my favorite contrarian and wise mentor, Edwin Carrington. Edwin, how are you doing today?

Edwin Carrington

Doing well, Claire. Always glad to be here and—if you’ll forgive the cliché—help shine a little light through the fog of conventional wisdom.

Claire Monroe

That’s the good stuff! Because today we’re diving into a topic that always gets people talking—sometimes defensively, honestly. This shift from gut-feel HR to data-driven decision making... it’s wild how fast it’s moved. Edwin, can you just… set the scene for a sec? HR used to feel like this mix of folklore and vibes. Who seemed right, who felt like they were thriving.

Edwin Carrington

You’re not wrong. For a long time, HR was basically oral tradition—passed down manager to manager. Stories, instincts, “what’s worked before.” And that had its place. But organizations got bigger, messier. The complexity outgrew the playbook. That’s where people analytics changed the rules.

Claire Monroe

Yeah. And it’s not like intuition vanished overnight—I mean, I still catch myself wanting to trust a hunch. But now it’s like... what even is “data-driven HR”? I’ve told people, “It’s not just spreadsheets making decisions,” but I don’t know if that helps.

Edwin Carrington

Actually, that’s a good instinct. Data-driven HR starts with meaningful questions. Like, “Why are people leaving this department?” or “Which hires actually succeed?” Then you go find evidence that either confirms—or challenges—what you think you know. The goal isn’t more reports. It’s better judgment.

Claire Monroe

So like... using data to test whether your story about someone holds up. Or if you’re just stuck in an old script.

Edwin Carrington

Exactly. I’ll be honest—early in my career, I once hired someone who checked all the “right” boxes. On paper, in the interview, the vibe felt solid. My gut was all-in. But if I’d looked closer—benchmark data, peer performance, even past project feedback—I’d have seen the warning signs. I didn’t. And they struggled. Hard.

Claire Monroe

So, like… full-on regret?

Edwin Carrington

Yeah. And not because I used my gut. But because I only used my gut. Data wouldn’t have made the decision for me—it would’ve shown me where my blind spots were. That’s the shift: using evidence to sharpen judgment, not replace it.

Claire Monroe

That hits. Gut feelings aren’t bad—but if you don’t test them, how do you ever grow? And now the smartest HR teams are kind of blending both. Human wisdom plus data clarity. Okay, so let’s get into how this actually plays out…

Claire Monroe

Let’s get practical. Because all this talk about “data-driven HR” can sound so... high-level. But in real life, it’s like—predicting who’s likely to succeed, spotting burnout early, seeing turnover before it happens. What have you seen shift in the trenches?

Edwin Carrington

The shift is very real. Take hiring—it’s no longer just “strong CV, good chat.” Now teams look at predictive patterns. What traits, backgrounds, or behaviors actually correlate with success in the role long-term? Same for retention—what early signs tend to show up before someone disengages? We’re moving from firefighting to forecasting.

Claire Monroe

And even old-school stuff like engagement surveys are getting… smarter, right? You told me about a case where surveys didn’t just confirm the vibe—but explained it.

Edwin Carrington

Yes. A company noticed morale dipping. Instead of guessing, they went deep on survey data—and it didn’t just say, “People feel off.” It pinpointed which teams felt undervalued and why. That insight didn’t lead to a vague morale initiative—it led to specific manager coaching and a new feedback cadence. Retention jumped. Engagement rebounded.

Claire Monroe

That’s so much more powerful than just... launching a pizza party and hoping for the best.

Edwin Carrington

Exactly. Real insight drives real action.

Claire Monroe

And then there’s DEI. I’ve seen companies run actual pay equity analyses, or track promotion rates across different groups—not just say “we care about inclusion.” Like, the numbers either support the story... or they don’t.

Edwin Carrington

Yes. That’s the difference between intention and accountability. DEI analytics isn’t just “how many hires were diverse?” It’s: Who’s getting promoted? Who’s getting raises? Do people from different backgrounds feel equally heard? The data often reveals gaps that aren’t visible from the top.

Claire Monroe

And honestly, it’s kind of a leap—from “I think we’re doing okay” to “Let’s check.” You go from anecdote to actual proof. But… it also sounds like a lot. Dashboards everywhere, reports, models. Is it ever too much?

Edwin Carrington

It can be. Drowning in metrics is real. But the upside—when you stay focused on insight—is huge. Smart teams pick the data that matters. Not all of it. They track what moves outcomes: better hires, higher belonging, real retention. It’s about clarity, not complexity.

Claire Monroe

Okay. That brings us to the messier part. Because it’s not all dashboards and glory...

Claire Monroe

Let’s be honest—“data-driven HR” sounds amazing on stage. But in real life? It’s messy. I remember my first HR dashboard... I felt like I needed a PhD and a therapist. What’s the stuff that trips people up most when they first get into analytics?

Edwin Carrington

You’re not alone. Common traps? Bad data quality—garbage in, garbage out. Overwhelm—too much data, no clear direction. Privacy—massive risk if mishandled. Skill gaps—most HR folks weren’t trained for analytics. And then there’s the biggest one: resistance to change.

Claire Monroe

Ohhh the resistance. I’ve seen leaders bristle the second you say “data.” Like you’re doubting their instincts, or replacing their years of experience with an algorithm.

Edwin Carrington

Exactly. That’s why it’s critical to start small. Pilot one tool. Show results. Invest in data literacy—make sure people understand what they’re looking at. And integrate your systems—don’t make people jump between eight apps to answer one question. Transparency helps too: show what’s being tracked and why.

Claire Monroe

That’s big. Because I’ve been in that moment—staring at a dashboard, feeling frozen. Like if I make the wrong data-driven move, I’ll break something. Total “analysis paralysis.”

Edwin Carrington

It’s real. The key is to anchor in outcomes. Ask: “What are we trying to change?” Then find the data that points the way. You don’t need perfect. Just progress. Use data as a compass—not a cage. Move, learn, recalibrate.

Claire Monroe

Okay, wait—say that again? Data as a…?

Edwin Carrington

As a compass. Not a cage.

Claire Monroe

That’s gonna stick with me. Because, yeah... HR doesn’t need to become data scientists overnight. But we do need to become more curious, more evidence-minded, more... courageous.

Edwin Carrington

Well said.

Claire Monroe

And if anyone out there’s wondering how to actually start—you don’t have to guess. You can test out OAD’s tools—like behavioral assessments—for free at O-A-D-dot-A-I. It’s a smart way to streamline hiring and improve team fit without adding more guesswork.

Edwin Carrington

That’s right. And more than anything, remember—data doesn’t replace your insight. It expands it. It reveals what you might’ve missed.

Claire Monroe

And that’s a wrap for today. Edwin, as always, thank you for being the quiet voice of reason in my very loud HR brain.

Edwin Carrington

Thank you, Claire. And to everyone listening—keep questioning, keep learning. That’s how we lead better.

Claire Monroe

We’ll be back soon with more stories from the front lines of smarter, fairer people decisions. Until next time, Edwin—

Edwin Carrington

Goodbye, Claire.

Claire Monroe

Bye, everyone!