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Earlier this year in a workshop…

A data analyst.

Presenting a churn analysis.

It had everything.

Confidence intervals.

Cohort breakdowns.

Retention curves.

But here’s the problem.

To the analyst, it was a masterpiece.

To a stakeholder, it was a maze.

Numbers everywhere.

No clear takeaway.

They’d nod. Maybe say thanks.

Then walk out and change nothing.

No matter how great the insight was...

The impact was zero.

Warren Buffett once said,

“If you can’t communicate, it’s like winking at a girl in the dark. Nothing happens.”

He was right. 😉

Click here to watch on ​YouTube (4 min):

💡 The “Insight Illusion”

Most data professionals think their work speaks for itself.

“I ran the models. I found the insight. That’s the hard part.”

But it’s not.

Because insight ≠ impact.

Here’s the hard truth I’ve learned from training thousands of data professionals:

Impact = Insight × Communication

Your insights are only as powerful as the way you communicate them.

You might be holding gold in your hands.

But if you wrap it in a soggy napkin of jargon, people won’t touch it.

☕ Real-World Test: The Coffee Machine Moment

Imagine this:

You're at the office coffee machine.

The marketing manager walks by and asks, “Hey, how’s that churn analysis going?”

Here are two ways to answer:

❌ Option A – Explain the process:

“Yeah, I ran a few models using signup source, device type, and plan. I looked at the correlations between usage and retention…”

The result?

No interest. No action. Nothing.

Why?

Because you focused on how you did the work... not why it matters.

✅ Option B – Lead with impact:

“Most users churn by day three. That’s 40% of signups, roughly 800 customers a week. I’d recommend sending a personalized email two days after signup to reduce that drop.”

Now you’ve got their attention.

You didn’t just show the data.

You showed the impact.

You showed a decision.

🧠 The Framework: What – So What – Now What

At MindSpeaking, we teach this 3-part structure to make sure your insights land:

1. What? – The headline insight

“Most users churn by day three.”

Make it clear. Specific. No fluff.

You’re not giving a tour of your code, you’re stating the bottom line.

2. So What? – Why it matters

“That’s 800 customers lost each week. Many are high-value signups.”

This connects your analysis to business risk or opportunity.

Without it, your insight sounds like trivia.

3. Now What? – What to do next

“Let’s test a personalized retention email campaign right after signup.”

Even if you can’t give a perfect solution, offer direction.

Create momentum. That’s how you become a trusted advisor.

📧 What This Looks Like in an Email

Let’s say a stakeholder asks you for delivery data.

Here’s how many data professionals reply:

“Hi John, here’s the delivery data you asked for.”

But this is a missed opportunity.

Here’s a better version:

“Hi John,

I looked into the delivery data.

Delivery times are 8% slower this quarter.

Doesn’t sound like much, but we’re losing repeat customers, and the biggest delays are in our highest-margin products.

I recommend prioritizing delivery on those products, even if it means paying extra.

Let me know if you’d like to discuss.

Gilbert”

Same data. Different framing.

One gets archived.

The other drives decisions.

🧭 Bottom Line

If you’re always explaining, you’re not influencing.

And if people tune out when you talk, it’s not because your insights aren’t good.

It’s because the packaging makes them hard to use.

You don’t need to add more details.

You need to give more direction.

The next time someone asks you for data…

Remember:

Impact = Insight × Communication

Thanks for reading,