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Making Data-Driven Decisions That Actually Improve Performance · The Science of Leading

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  So, Edwin, I wanna start today with kind of a confession.
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  Back in my early
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  days on this product team-this must've been,
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  what, seven or eight years ago?-I remember meetings where the loudest
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  voice in the room basically decided everything.
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  Didn't matter what the
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  data said...
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  it was more like, "who's the most convincing on their feet?"Which-looking
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  back-feels kinda medieval, honestly.
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  But I still see it.
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  Like, a lot.
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  Companies say they're all about data,
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  but when the moment comes?
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  The decisions don't feel data-driven.
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  So I'm curious-how do we actually
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  tell when decisions are rooted in data,
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  not just gut or guesswork?
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  Ah, Claire-you're naming something way more
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  common than people admit.
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  There's this illusion that if you've got dashboards
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  or reports, you're making data-driven choices.
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  But collecting info isn't
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  the same as using it-and it definitely doesn't mean you're interpreting
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  it well.
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  Real data-driven leadership?
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  It's not about having more charts.
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  It's a practice.
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  A habit of consistently asking:"What happened?"Then: "Why did it
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  happen?"And-most
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  critically-"What does this mean for what we do next?"It's a shift from
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  reacting to understanding.
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  When you said "interpreting the right data,"
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  that word-"right"-really stood out.
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  Like,
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  are we talking about clean spreadsheets?
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  Or is it more about, I don't know,
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  technique?'Cause I've seen teams get so obsessed with fancy tools...But
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  the basics are still, uh, kind of a mess.
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  You're spot on.
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  The foundation
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  is always data integrity-if the inputs are messy,
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  everything else is compromised.
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  But it doesn't stop there.
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  Great analysts
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  go beyond clean numbers.
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  They apply statistical thinking.
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  They visualize trends that aren't obvious.
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  Some even use predictive modeling
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  to spot what's coming before it hits.
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  But here's the real unlock: all that
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  technique only matters if it's tied directly to business goals.
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  Otherwise,
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  it's just noise dressed up as insight.
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  Right,
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  right...
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  like, you can have the flashiest AI dashboard on the planet-But if nobody
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  trusts the numbers underneath it?
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  It's all gonna fall apart.
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  I wish someone had asked this in those old
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  meetings I mentioned earlier:"How do we stop relying on gut-and actually
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  shift the culture toward evidence?"Like,
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  what practically changes?
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  Honestly?
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  It starts with leadership.
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  If you want your team to take data seriously,
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  you have to bring it into the room-every time.
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  That means using real,
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  validated information in decision-making and being transparent about
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  how you got there.
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  Over time, people notice.
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  They start to realize-It's not ego that drives decisions here...
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  it's evidence.
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  But that takes consistency.
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  You also have to invite questions.
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  Show people how analysis leads to better outcomes.
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  Then the shift happens
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  naturally-data stops being a prop and starts becoming a compass.
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  So it's
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  like: be the example, show your receipts,
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  and don't pretend you know everything when you don't.
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  Honestly,
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  I'd love to go back and whisper that in my younger self's ear.
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  I think
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  a lot of us would, Claire.
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  Okay,
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  let's zoom in a bit.
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  How do all those dashboards and reports actually
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  turn into something...
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  useful?
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  There's this bridge between information and action,
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  right?
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  And from what I've seen,
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  that bridge is people.
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  Specifically-analysts.
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  I tell teams all the time: your data folks aren't
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  just number crunchers.
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  They're translators.
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  They take messy,
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  complicated insights-and turn them into something people can act on.
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  Absolutely.
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  And yet, a lot of folks still picture analysts as these quiet spreadsheet
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  hermits in the corner.
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  In reality,
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  they're strategic connectors.
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  And with today's business intelligence tools-wow-there's
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  a lot you can track.
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  But here's the catch: if you don't have systems in
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  place to manage and integrate all that data?
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  It just becomes another source
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  of noise.
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  Yeah-like a digital junk drawer,
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  just filled with abandoned dashboards.
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  So how do teams actually use the
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  data, instead of just...
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  hoarding it?
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  That's the make-or-break question.
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  It starts with data governance-basically,
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  rules and discipline around what data you collect,
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  how often, and from where.
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  Especially now,
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  when you're blending structured data-like sales or productivity numbers-with
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  unstructured stuff like customer reviews or social posts.
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  And then comes
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  transformation.
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  I worked with a manufacturing company that used predictive
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  analytics across procurement, logistics,
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  and production.
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  By aligning all those data points-and having analysts
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  embedded in team discussions-they cut costs by 20%.Not because of the
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  data alone-but because it got turned into decisions.
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  Wait-twenty percent?
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  That's wild.
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  Okay, but here's what I keep wondering: what about non-technical
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  leaders?
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  There are still so many managers out there who...
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  aren't data scientists.
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  How do they engage with analytics,
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  without feeling overwhelmed?
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  They don't need to be experts.
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  What they do
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  need is curiosity.
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  You don't have to build a model from scratch-you just
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  need to ask the right questions."Where's this trend coming from?""What
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  does this mean for our team's goals?"And most importantly: "Does this
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  story make sense?"When leaders bring analysts in early,
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  they're not just asking for reports-they're co-creating strategy.
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  That
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  partnership is where real transformation starts.
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  Yeah,
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  that "translator" piece really is everything.
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  Like,
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  you don't need to speak fluent data-you just need to know how to ask
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  for subtitles.
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  Exactly.
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  It's about collaboration.
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  And having systems in place to give you reliable,
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  timely insights-Because otherwise,
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  all your great questions just hit a wall.
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  Let's talk culture for a second.
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  Because
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  even with the best tools, I've seen teams kinda...
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  revolt.
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  At my last company, when these dashboards rolled out,
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  people were like-"Wait, who built this?
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  Is this even right?
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  Am I about to get graded on something broken?"Total skepticism.
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  So how
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  do you get people to trust the data-and actually use it?
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  Honestly,
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  that kind of pushback?
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  It's healthy.
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  Blind trust is just as risky as no trust.
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  Real buy-in starts
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  with data quality-metrics need to be accurate,
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  relevant, and transparently sourced.
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  But the deeper layer is data literacy.
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  If
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  people understand how to read and challenge the numbers,
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  they feel empowered instead of surveilled.
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  And as we've talked about before-leaders
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  who model that curiosity?
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  They shift the culture.
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  Slowly, but powerfully.
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  It's like the data version of giving and receiving
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  feedback.
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  Don't just accept the numbers-ask what they mean.
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  But now I'm
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  wondering-how do we stop metrics from turning into this graveyard of KPIs
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  that nobody looks at?
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  That's where alignment comes in.
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  KPIs need to track
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  back to real outcomes-customer retention,
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  faster onboarding, better engagement.
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  And they need to evolve.
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  Teams should
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  regularly review and refine what they measure.
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  Because when people see
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  a clear link between data and business wins?
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  That's when trust turns into
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  habit.
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  It stops being "just a report" and starts being part of how the
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  team learns and grows.
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  So, let me try to sum this up:Start with solid,
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  trustworthy data...Help people understand what they're looking at...And
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  always tie those numbers back to something that actually matters.
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  Then,
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  keep that feedback loop open-so the system keeps getting smarter.
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  That's
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  it.
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  And it's worth saying again:Data doesn't replace human insight.
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  It sharpens
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  it.
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  When people experience that-consistently-that's when culture
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  really
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  changes.
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  Edwin, this was sooo much deeper than "use more data."We touched
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  tech, culture, trust-it's all connected.
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  Is there one thing you'd want
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  leaders to hold onto as they take this forward?
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  Just this:The edge doesn't
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  come from having more information.
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  It comes from blending evidence with
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  thoughtful judgment.
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  If you create space for both,
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  you'll build teams that outperform instinct-every time.
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  Couldn't have
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  said it better.
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  And hey, if you're curious about how science-backed tools
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  like behavioral assessments fit into this whole puzzle,
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  go check out OAD.
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  ai.
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  You can test them for free-super simple-and it's
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  a great way to start linking people decisions to actual performance.
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  Thanks
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  for listening, and we'll see you next time on The Science of Leading.
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  Take
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  care, Claire.
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  And to all our listeners-keep leading with insight.