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Did I Actually Answer That Question?” — The Hidden Challenge Every Analyst Faces

Michael Lee, MBA
20 hours ago
4 min read

If you work in analytics long enough, you’ll recognise this scene.

You’re halfway through presenting a dashboard to stakeholders. The story is flowing well. People look engaged. Someone even leans forward — always a good sign.

Then a hand goes up.

“Just a quick question…”(Of course it’s never just a quick question.)

You begin answering. You talk about the data. Then the filter logic. Then the campaign period. Then the customer segment. Something about seasonality. A side note on outliers.

You stop talking.

And in that split second of silence, you feel it:

You explained a lot… but you didn’t really answer the question.

I’ve watched this happen in training rooms, boardrooms, and project meetings across industries. One participant once laughed and told me afterwards, “Michael, I gave them everything except what they asked.”

It’s not a skill issue. It’s not confidence. It’s not intelligence.

It’s something more human.

When we work with data, our minds don’t think in straight lines. We see relationships, assumptions, caveats, edge cases, and exceptions — and when someone asks a question, all those mental tabs fly open at once.

So we talk our way towards the answer, hoping clarity eventually arrives.

Meanwhile, stakeholders don’t want the journey.They want the destination.

And that’s why analysts often struggle in Q&A — not because they don’t know the answer, but because they try to answer everything around the answer.

Here’s one thing I’ve learned over years of teaching and working with analysts:

Analysts rarely struggle with answers.They struggle with structure.

Which is why a simple framework can change everything.

One of the most effective is PREP.

PREP: The Analyst’s Secret Weapon for Clear, Confident Answers

PREP is not fancy. It’s not proprietary. It doesn’t require certification or a three-day workshop.

It’s simply a reliable structure for responding to questions with clarity — especially when the pressure is on.

PREP stands for:

P — Point
R — Reason
E — Example
P — Point (reinforced)

Think of PREP as a mental “reset button.”It organizes your thoughts before your thoughts overwhelm you.

Here’s how it works.

1. POINT — Start by answering the question directly

Most analysts warm up — talk around the edges — before actually getting to the answer.

PREP forces you to begin with it:

“Yes, the spike is significant.”
“No, the metric isn’t reliable yet.”
“Yes, the trend is real.”
“No, we shouldn’t use an average here.”

It’s the communication equivalent of showing the final dashboard before drilling into details.

2. REASON — Give the logic behind your answer

After the point comes the explanation:

“Because the pattern doesn’t match any historical behaviour.”
“Because the sample size is too small for a stable estimate.”
“Because returning users — our most stable segment — are dropping.”

Stakeholders don’t need the whole SQL query. They just need the reasoning.

3. EXAMPLE — Bring the answer to life

Examples are where analysts shine.This is the moment clarity becomes visible:

“For instance, last quarter this metric only moved when we changed pricing.”
“In the churn dataset, the spike only appears after the July onboarding cohort.”
“When we ran the pilot, approval time dropped from two days to two hours.”

Examples give people something to see — and what people see, they remember.

4. POINT — Land the conclusion with intention

No drifting. No soft endings.

Close the loop:

“And that’s why this spike needs investigation.”
“So no — the metric isn’t ready for decision-making yet.”
“Which is why consolidating the data early prevents larger issues later.”

A clean ending signals confidence and clarity.

A Before/After That Shows the Difference

Before: Unstructured Answer

“Yeah, so the spike… we think it might matter, because last year we saw something similar, though that one was tied to the campaign, but this time we didn’t have one, although the customer mix changed, so maybe it’s something but we need to confirm…”

After: PREP

Point: Yes, this spike is worth investigating. Reason: It doesn’t align with historical patterns or seasonality. Example: In the past three years, this metric only moved when pricing or campaigns changed — neither happened this month. Point: So this spike is unusual and deserves attention.

Same knowledge. Better structure. Greater impact.

Three Analyst Scenarios Where PREP Shines

1. During Dashboard Review

Question: “Is this drop in conversion serious?”

P: Yes, it’s significant.

R: Traffic and targeting remained stable, so the drop isn’t noise.

E: For instance, returning users — usually our most predictable group — fell sharply.

P: So yes, this drop needs investigation.

2. When Methodology Gets Challenged

Question: “Why can’t we just take the average?”

P: Because it won’t represent typical behaviour.

R: The data is skewed, heavily influenced by outliers.

E: For example, 90% of customers spend under $300, but a few corporate accounts spend above $10,000 — the average hides this.

P: So a median or segmented view is more accurate.

3. When Leaders Want a Quick Read

Question: “Are we improving overall?”

P: Yes, we are.

R: Both month-on-month and quarter-on-quarter trends show positive movement.

E: Conversion rose from 4.2% to 5.1% — the highest since 2021.

P: So yes, performance is genuinely improving.

Why PREP Works — Especially for Analysts

PREP helps analysts overcome the two habits we default into:

Explaining everything before answering anything
Sharing the thought process instead of the conclusion

PREP flips that.

It brings order to complexity. It ensures clarity comes before detail. And it helps you communicate like someone who not only understands the data…but helps people make decisions with it.

It doesn’t make you sound rehearsed. It makes you sound intentional.