MamaWritesSpells

Numbers are inputs, not instructions.

Let’s be honest for a second.

When people say they’re making “data-driven decisions,” what they usually mean is we looked at some numbers and now feel more confident about a choice we were already leaning toward.

And look — that’s not a crime. That’s human.

But it’s very different from the myth we like to sell, where data descends from the heavens, perfectly objective, and tells everyone exactly what to do next.

That version exists mostly in decks.

In real life, data is messy.
Incomplete.
Lagging.
Context-dependent.

And it almost never answers the question people actually want it to answer, which is: What should we do?

Here’s what data does do well:
It narrows the conversation.

It tells you what’s happening, where patterns are forming, and which assumptions are probably wrong. It gives you boundaries. Signals. Constraints.

What it does not do is replace judgment.

Because every meaningful decision still requires interpretation. Tradeoffs. Context you can’t chart. Human factors that don’t show up cleanly in a spreadsheet.

Two teams can look at the same data and make different — equally defensible — decisions based on their goals, risk tolerance, and reality on the ground.

That’s not a failure of data.
That’s the point.

“Data-driven” doesn’t mean following metrics blindly. It means letting evidence inform your thinking without pretending it absolves you of responsibility.

The most dangerous misuse of data I see isn’t ignoring it — it’s hiding behind it.

Using numbers as a shield.
As justification.
As a way to avoid saying, “We’re choosing this because it aligns with our priorities, even though it carries risk.”

Good decision-makers don’t ask, “What does the data say we should do?”
They ask, “What does the data change about how we think?”

That’s a subtler skill. And a harder one.

It means holding multiple truths at once:

• The data is pointing us here.
• The impact on people looks like this.
• The timing complicates things.
• The cost of waiting is also real.

That’s not indecision.
That’s discernment.

In practice, truly data-informed teams do a few unglamorous things really well:

• They question what’s missing, not just what’s present.
• They name assumptions out loud.
• They separate signal from comfort.
• They accept that sometimes the data clarifies the risk — but doesn’t remove it.

Which is why the best decisions often feel slightly uncomfortable.
You’re still choosing.
You’re still accountable.
You’re just doing it with your eyes open.

So yes — use the data. Respect it. Invest in it.

Just don’t pretend it’s a substitute for thinking.

Because in real life, “data-driven” doesn’t mean the numbers decided.
It means you did — with evidence in hand.