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Getting Real About Data-Driven HR · The Science of Leading

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  Welcome back, everyone, to The Science of Leading.
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  I'm Claire Monroe, here with my favorite contrarian and wise mentor,
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  Edwin Carrington.
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  Edwin, how are you doing today?
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  Doing well,
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  Claire.
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  Always glad to be here and-if you'll forgive the cliché-help shine a
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  little light through the fog of conventional wisdom.
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  That's the good stuff!
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  Because today we're diving into a topic that always gets people talking-sometimes
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  defensively, honestly.
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  This shift from gut-feel HR to data-driven decision making...
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  it's wild how fast it's moved.
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  Edwin, can you just... set the scene for a sec?
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  HR used to feel like this mix of folklore and vibes.
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  Who seemed right, who felt like they were thriving.
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  You're not wrong.
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  For a long time, HR was basically oral tradition-passed down manager
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  to manager.
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  Stories, instincts, "what's worked before." And that had its place.
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  But organizations got bigger, messier.
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  The complexity outgrew the playbook.
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  That's where people analytics changed the rules.
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  Yeah.
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  And it's not like intuition vanished overnight-I mean,
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  I still catch myself wanting to trust a hunch.
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  But now it's like...
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  what even is "data-driven HR"?
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  I've told people, "It's not just spreadsheets making decisions," but
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  I don't know if that helps.
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  Actually,
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  that's a good instinct.
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  Data-driven HR starts with meaningful questions.
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  Like, "Why are people leaving this department?" or "Which hires actually
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  succeed?" Then you go find evidence that either confirms-or challenges-what
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  you think you know.
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  The goal isn't more reports.
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  It's better judgment.
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  So like...
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  using data to test whether your story about someone holds up.
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  Or if you're just stuck in an old script.
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  Exactly.
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  I'll be honest-early in my career,
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  I once hired someone who checked all the "right" boxes.
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  On paper, in the interview, the vibe felt solid.
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  My gut was all-in.
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  But if I'd looked closer-benchmark data,
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  peer performance, even past project feedback-I'd have seen the warning
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  signs.
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  I didn't.
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  And they struggled.
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  Hard.
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  So, like... full-on regret?
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  Yeah.
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  And not because I used my gut.
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  But because I only used my gut.
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  Data wouldn't have made the decision for me-it would've shown me where
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  my blind spots were.
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  That's the shift: using evidence to sharpen judgment,
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  not replace it.
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  That hits.
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  Gut feelings aren't bad-but if you don't test them,
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  how do you ever grow?
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  And now the smartest HR teams are kind of blending both.
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  Human wisdom plus data clarity.
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  Okay, so let's get into how this actually plays out...Let's get practical.
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  Because all this talk about "data-driven HR" can sound so...
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  high-level.
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  But in real life, it's like-predicting who's likely to succeed,
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  spotting burnout early, seeing turnover before it happens.
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  What have you seen shift in the trenches?
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  The shift is very real.
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  Take hiring-it's no longer just "strong CV,
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  good chat." Now teams look at predictive patterns.
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  What traits, backgrounds, or behaviors actually correlate with success
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  in the role long-term?
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  Same for retention-what early signs tend to show up before someone disengages?
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  We're moving from firefighting to forecasting.
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  And even old-school stuff
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  like engagement surveys are getting... smarter,
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  right?
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  You told me about a case where surveys didn't just confirm the vibe-but
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  explained it.
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  Yes.
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  A company noticed morale dipping.
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  Instead of guessing, they went deep on survey data-and it didn't just
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  say, "People feel off." It pinpointed which teams felt undervalued and
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  why.
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  That insight didn't lead to a vague morale initiative-it led to specific
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  manager coaching and a new feedback cadence.
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  Retention jumped.
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  Engagement rebounded.
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  That's so much more powerful than just...
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  launching a pizza party and hoping for the best.
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  Exactly.
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  Real insight drives real action.
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  And then there's DEI.
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  I've seen companies run actual pay equity analyses,
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  or track promotion rates across different groups-not just say "we care
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  about inclusion." Like, the numbers either support the story...
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  or they don't.
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  Yes.
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  That's the difference between intention and accountability.
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  DEI analytics isn't just "how many hires were diverse?" It's: Who's getting
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  promoted?
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  Who's getting raises?
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  Do people from different backgrounds feel equally heard?
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  The data often reveals gaps that aren't visible from the top.
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  And honestly,
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  it's kind of a leap-from "I think we're doing okay" to "Let's check."
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  You go from anecdote to actual proof.
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  But... it also sounds like a lot.
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  Dashboards everywhere, reports,
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  models.
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  Is it ever too much?
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  It can be.
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  Drowning in metrics is real.
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  But the upside-when you stay focused on insight-is huge.
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  Smart teams pick the data that matters.
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  Not all of it.
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  They track what moves outcomes: better hires,
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  higher belonging, real retention.
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  It's about clarity, not complexity.
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  Okay.
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  That brings us to the messier part.
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  Because it's not all dashboards and glory...Let's be honest-"data-driven
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  HR" sounds amazing on stage.
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  But in real life?
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  It's messy.
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  I remember my first HR dashboard...
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  I felt like I needed a PhD and a therapist.
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  What's the stuff that trips people up most when they first get into analytics?
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  You're
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  not alone.
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  Common traps?
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  Bad data quality-garbage in, garbage out.
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  Overwhelm-too much data, no clear direction.
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  Privacy-massive risk if mishandled.
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  Skill gaps-most HR folks weren't trained for analytics.
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  And then there's the biggest one: resistance to change.
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  Ohhh the resistance.
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  I've seen leaders bristle the second you say "data." Like you're doubting
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  their instincts, or replacing their years of experience with an algorithm.
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  Exactly.
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  That's why it's critical to start small.
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  Pilot one tool.
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  Show results.
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  Invest in data literacy-make sure people understand what they're looking
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  at.
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  And integrate your systems-don't make people jump between eight apps
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  to answer one question.
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  Transparency helps too: show what's being tracked and why.
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  That's big.
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  Because I've been in that moment-staring at a dashboard,
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  feeling frozen.
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  Like if I make the wrong data-driven move,
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  I'll break something.
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  Total "analysis paralysis."It's real.
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  The key is to anchor in outcomes.
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  Ask: "What are we trying to change?" Then find the data that points the
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  way.
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  You don't need perfect.
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  Just progress.
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  Use data as a compass-not a cage.
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  Move, learn, recalibrate.
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  Okay,
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  wait-say that again?
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  Data as a...?As a compass.
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  Not a cage.
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  That's gonna stick with me.
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  Because, yeah...
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  HR doesn't need to become data scientists overnight.
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  But we do need to become more curious,
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  more evidence-minded, more...
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  courageous.
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  Well said.
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  And if anyone out there's wondering how to actually
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  start-you don't have to guess.
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  You can test out OAD's tools-like behavioral assessments-for free at
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  O-A-D-dot-A-I.
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  It's a smart way to streamline hiring and improve team fit without adding
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  more guesswork.
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  That's right.
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  And more than anything, remember-data doesn't replace your insight.
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  It expands it.
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  It reveals what you might've missed.
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  And that's a wrap for today.
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  Edwin, as always, thank you for being the quiet voice of reason in my
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  very loud HR brain.
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  Thank you, Claire.
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  And to everyone listening-keep questioning,
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  keep learning.
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  That's how we lead better.
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  We'll be back soon with more stories from the
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  front lines of smarter, fairer people decisions.
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  Until next time, Edwin-Goodbye,
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  Claire.
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  Bye, everyone!