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Mastering Data Based Decisions · The Science of Leading

• 0:00
  Alright-welcome back to The Science of Leading.
• 0:02
  I'm Claire Monroe, and with me-as always-is the one and only Edwin
• 0:02
  Carrington.
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  Today
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  we're digging into something that honestly...
• 0:11
  I've been chewing on since our last episode.
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  Data-based decisions.
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  And
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  Edwin-I've gotta say-that analogy you dropped about data sharpening,
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  not replacing our judgment?
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  That stuck with me.
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  I'm glad it did.
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  Because that's really the crux here.
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  When we say "data-based," we're not
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  talking about letting spreadsheets or algorithms run the show.
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  We're talking
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  about using observable evidence-numbers tied to real behaviors,
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  structured feedback you can track,
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  test, revisit.
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  Not whoever has the strongest opinion in the room that
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  day.
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  Yeah, okay...
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  but hold on.
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  For people who aren't knee-deep in analytics,
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  there's this blur-right?"Data-based," "data-driven"-they sound interchangeable,
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  but are they actually different?
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  They are.
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  And it matters.
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  Data-based means the data supports the decision.
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  But the decision?
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  Still made by people.
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  Data-driven tends to mean automation-decisions flowing
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  straight from algorithms, models,
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  rules.
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  That can work in, say, e-commerce.
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  But in HR?
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  You lose context.
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  You lose the messy,
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  human side of things that doesn't always show up in a dashboard.
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  Right-so
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  like, if you take it too far, you're basically outsourcing your thinking.
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  That
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  feels dangerous...
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  especially when it's about who to hire or promote.
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  We're not talking widgets-we're talking real lives and teams here.
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  Exactly.
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  I
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  remember this hiring panel I was on-early in my career,
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  maybe late '80s.
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  We had this candidate-brilliant on paper.
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  Bit reserved in person.
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  We had structured tools, but the panel?
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  Defaulted to gut instinct.
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  Loudest voices won.
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  We passed on her.
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  Six months
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  later, she's working at a competitor-crushing every single
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  performance
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  metric.
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  That moment changed everything for me.
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  If we'd had real criteria-auditable,
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  consistent-we might've made a different call.
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  Oof.
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  Yeah, that's brutal.
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  So really,
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  being data-based is about structure.
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  Like-giving your decisions a backbone.
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  You set your criteria,
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  gather what matters, make the call,
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  and log it.
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  That way you can...
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  actually learn from it?
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  That's it.
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  Otherwise,
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  you're just guessing, forgetting,
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  and repeating the same mistakes under a different name.
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  That's not leadership.
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  It's roulette.
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  Okay, let's get tactical then.
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  Say I'm on a team that usually
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  wings it-some sticky notes, maybe a Slack thread.
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  What does it actually
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  look like to build better data habits?
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  Is it just "buy a tool"-or is there
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  more to it?
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  There's always more to it.
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  Most teams already have data-it's
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  just messy, scattered, or ignored.
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  The real move is to slow down and ask:"What
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  decision are we making?
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  Who owns it?
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  And what does success look like?"Once that's clear,
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  you define just enough criteria to guide the decision.
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  So it's not about
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  collecting more-it's about collecting smarter.
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  I picture this nightmare
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  spreadsheet where each person's looking at a different tab...
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  thinking they have the truth.
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  No wonder everyone's exhausted.
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  You're not
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  wrong.
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  That's where something simple-like a shared decision log-changes
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  the game.
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  Hiring?
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  Define your must-haves before you open a single CV.
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  Use scorecards,
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  not scribbles.
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  When you decide,
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  write down what you chose and why.
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  And later-when that person's thriving
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  or struggling-you actually have the receipts.
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  That's the loop.
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  That's how you improve.
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  So even without a huge platform,
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  you can make things traceable-repeatable.
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  You've mentioned data systems
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  before.
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  For smaller orgs-what's step one?
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  Start with one trusted source.
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  Pick a
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  home for your data.
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  Clean up your terms-make sure "time to hire" doesn't mean three different
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  things to three different teams.
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  Lock down who can edit what.
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  Fancy tools
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  come later.
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  In the beginning?
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  It's about clarity, ownership,
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  and enough structure that people trust the numbers.
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  That reminds me-I
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  saw this case study where a company moved from unstructured interviews
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  to structured candidate assessments.
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  And like...
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  it flipped their whole hiring game.
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  Suddenly managers could actually compare
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  people.
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  The drama?
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  Gone.
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  The "he said, she said"?
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  Gone.
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  It was just-here's the scorecard.
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  Here's what we chose.
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  Here's what happened.
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  I've seen that exact shift.
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  Over and over.
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  Structured, repeatable evaluations reduce bias,
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  speed up hiring, and improve retention.
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  But even more than that-they lower
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  the emotional noise.
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  Because when decisions are documented,
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  they stop being about blame.
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  They become about learning.
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  Okay-let's zoom
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  out.
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  What's a moment you've seen this work in another function-like marketing
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  or ops-where the data actually moved the needle?
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  Marketing's a great one.
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  You
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  run a campaign, collect real results-not guesses.
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  And maybe you learn Segment
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  A clicks more on Tuesdays, and Message X converts better.
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  So you shift
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  budget.
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  And suddenly-your conversion rate climbs,
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  churn drops.
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  It wasn't magic.
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  It was clarity.
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  Same in ops-track delays,
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  map the shifts, and boom: you see most errors happen at night.
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  You retrain,
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  fix the handoff, and your costs plummet.
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  Data didn't decide-it pointed.
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  And you moved fast.
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  And that's where culture shows up,
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  right?
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  Because you can build the slickest dashboard in the world,
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  but if no one acts on it...
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  what's the point?
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  Exactly.
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  If leaders treat data like a scorecard-or worse,
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  a weapon-people will game the system.
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  But if leaders use data to learn-to
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  ask better questions-it changes the entire culture.
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  It takes consistency.
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  Shared definitions.
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  Regular review.
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  Even a chief data officer,
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  if you're big enough, who sets the standard so the whole org speaks the
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  same language.
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  Okay-quick one from my side.
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  I nudged my team to start logging
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  our hiring decisions.
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  Nothing fancy-just a shared doc.
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  We did it for two
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  cycles and suddenly...
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  patterns emerged.
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  We saw who actually stuck,
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  who exceeded, and-like-why.
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  It was weirdly empowering.
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  That's the muscle.
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  Not
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  just reporting-reviewing.
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  Those little habits-documenting,
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  checking your own assumptions-that's where data becomes a culture.
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  It's
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  not flashy.
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  But it works.
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  Alright-perfect note to end on.
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  If you want better decisions:Start
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  small.
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  Define your criteria.
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  Gather what matters.
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  Keep track of what works.
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  And if you're wondering how to put this into
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  action...You can actually test out OAD's tools-like behavioral assessments-for
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  free at o-a-d-dot-a-i.
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  It's a practical way to strengthen your hiring process
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  and improve team fit.
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  Thank you,
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  Edwin.
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  And thanks to all of you for listening to The Science of Leading.
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  We'll
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  see you next time.
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  Until next time-keep learning.
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  Good decisions aren't magic.
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  They're built.