Have you ever noticed that a marketing meeting can suddenly turn into a courtroom?

You come in to discuss what to do next.

But instead, the whole conversation shifts to a different trial:

Where did this number come from?
Why is it calculated this way?
Can we even trust it?
Why doesn’t it match the other report?

And suddenly the CMO is no longer leading the discussion.

They’re defending the data.

Basically acting as a lawyer for their own dashboard. Which is not exactly what anyone signed up for.

I’ve seen this many times when I worked in-house. Half the meeting goes not into decisions, but into explaining sources, logic, definitions, assumptions, and why this number is “actually fine if you look at it correctly”.

Now, as a fractional Head of Marketing Analytics, I see the same pattern from the outside.

And the logic I recommend is simple:

before asking people to make decisions based on the numbers, make sure they understand where those numbers come from.

Not in a “here is a 47-page data dictionary, good luck” way.

More like:

  • what is the source of truth?
  • how is this metric calculated?
  • what does it include and exclude?
  • why can it differ from another tool?
  • what is this number good for - and what is it not good for?

Because no, this problem doesn’t happen because everyone is stupid.

It happens because the system is not transparent enough.

If people don’t understand:

  • where the data comes from
  • how it is collected
  • how metrics are calculated
  • what assumptions sit behind the report
  • why different tools show different numbers

then the numbers don’t feel like a foundation.

They feel like one more version of reality.

And that’s where analytics starts doing the opposite of what it should do.

Instead of speeding up management decisions, it slows them down.

Every new report becomes another attempt to prove that the numbers are even real.

Spending half your team’s life explaining why the numbers don’t match?

Not ideal. Mildly soul-destroying, actually.

But it’s fixable.

Start by investing in:

  • transparent calculation logic
  • clear data sources
  • shared metric definitions
  • one set of rules for reporting
  • a simple explanation of what each number means and what it doesn’t mean

When this layer is clear, numbers stop being the topic of the meeting. They become the basis for the meeting.

And that’s when the conversation finally moves from:

“Can we trust this?”

to:

“What do we do next?”

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