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What could go wrong during Definition? - Part 2

Mar 10, 2026
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I think a Data Design Process encourages teams to approach dashboards with methodology instead of focusing only on tools.

To test your team’s methodological maturity, ask a data analyst about the last dashboard released:

  • Who were the target users?
  • How they can share feedback or questions?
  • What decision is this solution supposed to support?

Very often, the answer is: "I don’t know" or "we don’t have a method".

Last week, we explored the Discovery step.

Today, we move to the next step: Define.

And I think this is one of the most overlooked step in BI projects.

Discovery creates divergence.
Define should create convergence.

This is where insights become decisions.
Where use cases are prioritized.
Where the scope of the project becomes clear.

I often think BI dashboards are used for macro-level steering.
They touch many teams.
Many questions.
Large portions of the data landscape.

Without a strong Define phase, the scope expands endlessly.

The dashboard becomes a compromise between perspectives.

But the dashboards that truly create value are different.

In my experience, they are tied to specific users.
Specific decisions.
Specific objectives.

That clarity should happen during the Define step.

This is part 2 of a 4 part series.

Next week, we’ll explore the Design phase.

If you feel your team is building dashboards without a clear framework, we can start with a methodology audit this week:

Begin your Analytics framework audit

Have a great week everyone!

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The moment "we’re too busy" becomes the norm, it’s already too late
*]:pointer-events-auto scroll-mt-(--header-height)" dir="auto" tabindex="-1"> *]:pointer-events-auto scroll-mt-[calc(var(--header-height)+min(200px,max(70px,20svh)))]" dir="auto" tabindex="-1"> If your team keeps saying "we’re too busy", you’ve already lost control. People are doing their best.But without a solid system in place, they have almost no chance to succeed. And to be fair, succ...
Data-to-Decision Leakage
*]:pointer-events-auto scroll-mt-(--header-height)" dir="auto" tabindex="-1"> *]:pointer-events-auto scroll-mt-[calc(var(--header-height)+min(200px,max(70px,20svh)))]" dir="auto" tabindex="-1"> Most data teams track what they produce. Number of dashboards.Number of reports.Number of requests delivered. It looks like performance. It’s not. I think most organizations have no idea how much v...
I think most companies don’t really have an Analytics Operating Model. Do you?
*]:pointer-events-auto scroll-mt-(--header-height)" dir="auto" tabindex="-1"> *]:pointer-events-auto scroll-mt-[calc(var(--header-height)+min(200px,max(70px,20svh)))]" dir="auto" tabindex="-1"> Most data team efforts never translate into actual business decisions. Not because they don’t invest.Not because they lack tools or skills. From what I see, it’s more about how everything is struct...

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