Why Most Data Strategies Fail (And What To Do Instead)
- Dave Findlay
- Jun 5
- 2 min read
You’ve probably seen this before.
A company spends months crafting a data strategy. There’s a task force. Stakeholder interviews. A roadmap full of hexagons and horizons. A deck so big you wonder if it’s trying to win a tender or block sunlight.
And yet, nothing changes.
Business users still can’t get answers without pinging a data analyst. The fancy BI tool still gets used as a glorified PDF exporter. Everyone quietly goes back to Excel.
Why does this happen?
1. The strategy is too abstract
Most strategies focus on future-state diagrams, maturity models, and best practices. That stuff looks good on paper — but it’s not how people experience data problems.
Your users don’t want a data lake. They want to stop waiting two weeks for a basic sales report.
If your strategy doesn’t speak to that pain, it won’t get used.
2. It’s all planning, no doing
A lot of data strategies are deliverables in disguise. The job becomes “finish the strategy” instead of “solve the problem.”
If your plan doesn’t help anyone do something better in the next 30 days, people will lose interest — and fast.
3. Nobody owns the outcomes
Who’s accountable for making the strategy real? Often, no one. Or worse, everyone. Which means it quietly drifts into obscurity while other priorities take over.
What to do instead
We use a different approach at Fuse Data:
Start with pain. What’s annoying your team right now?
Solve something quickly. Prove that things can be better.
Use that success to build momentum. That’s how you get buy-in.
This way, your strategy isn’t a static document — it’s a series of real wins that stack up over time.
If this resonates, or if you’ve got a strategy gathering dust on the shelf, let’s talk. I offer a free 30-minute call to help get things unstuck.
