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Taylor Culver
Feb 2026
If you’re reading this, there’s a good chance someone just gave you “the data project.” It may not have been framed that way. It might have sounded like: “We need a data strategy.” “Leadership wants us to be more data-driven.” “AI is a priority this year.” “Can you help centralize reporting?” “We need to get our arms around governance.” Whatever the phrasing, the reality is the same: You’ve been handed responsibility for a complex change initiative that cuts across teams, incentives, and power structures, often without authority, extra headcount, or a clear definition of success. This post is for executives in that exact position. Not data leaders by training. Not people looking to become experts in tooling. But accountable leaders who want to deliver results without turning data into an endless internal science project.
Most data initiatives fail because they are framed incorrectly from day one.
This is not a technology problem.
It is not a reporting problem.
It is not a tooling problem.
It is not solved by hiring a consultant or buying a platform.
What you’ve been handed is a change management problem, with data as the lever.
If you over-rotate on data artifacts dashboards, models, pipelines, catalogs you will confuse your stakeholders and disengage them at the same time.
The goal is not “better data.”
The goal is better decisions, better execution, and visible business impact.
Everything else is support.
Most executives approach their first data initiative with good instincts:
They ask for a roadmap.
They request a maturity assessment.
They want benchmarks.
They want a future-state architecture.
None of these are wrong. They’re just premature.
Here’s what actually happens:
Senior stakeholders are polite but non-committal.
Feedback is vague or contradictory.
Meetings produce agreement but no follow-through.
The work starts to feel abstract.
Momentum stalls.
The initiative quietly gets deprioritized.
At this point, many leaders assume the organization “isn’t ready for data.”
That’s rarely true.
What’s missing is traction.
Data earns credibility the same way any initiative does: by solving a real problem for a real leader in a way they actually feel.
Not a global rollout.
Not an enterprise taxonomy.
Not a perfect strategy document.
One problem.
One team.
One outcome.
Here’s a simple, repeatable approach that works precisely because it does not require authority or consensus.
Start with your department or function, not the enterprise.
Write one page that answers a single question:
“How does better use of data help us achieve our mission this year?”
No buzzwords.
No platforms.
No future promises.
If you can’t explain the value in plain language, your stakeholders won’t either.
Meet with senior stakeholders individually or in small groups.
Your goal is not buy-in.
Your goal is discovery.
Ask one question:
“Where does lack of clarity, trust, or access to information slow you down?”
Expect only 10–20% of people to give you something usable.
That’s normal.
That’s enough.
Choose a problem that:
Has a visible owner
Has business impact
Creates friction today
Can be improved in weeks, not quarters
This is not about picking the “most important” problem.
It’s about picking the most solvable one.
Sit with the stakeholder’s team and clarify:
What decisions are they trying to make?
What questions do they ask repeatedly?
What do they not trust today?
Only then involve analysts or technical teams.
This step alone prevents most failed data efforts.
The output does not need to be perfect.
It needs to feel useful.
If a senior leader says, “This actually helps,” you’re on the right path.
This part is uncomfortable for many leaders, but it matters.
Tell the story.
What problem was solved.
Who benefited.
What changed.
This is how demand forms organically.
If the second use case comes easily, keep going.
If it doesn’t, pause and reassess.
Momentum is your signal, not enthusiasm.
This surprises many executives.
You do not need a Chief Data Officer.
You do not need a massive transformation program.
You do not need to centralize everything.
An accountable executive with a clear problem, a willing partner, and a bias toward action can drive real data outcomes.
Many of the strongest data-led organizations started exactly this way, long before they had formal data leadership.
They try to be helpful instead of effective.
They wait for consensus.
They avoid discomfort.
They over-explain the data.
Leadership here looks different.
It means letting things be imperfect.
It means tolerating friction.
It means choosing progress over approval.
If you’ve been handed a data initiative and it feels heavier than it should, you’re not failing.
You’re likely just aiming at the wrong target.
Start smaller.
Anchor on real problems.
Let results do the convincing.
That’s how data stops being “the data project” and starts becoming part of how the business actually runs.
