Case Study 1 — Dana's One-Pager: Twenty-Two Pages, One Decision, Sixty Seconds

A worked transformation. We follow Dana Whitfield's churn analysis—the finding you watched her rebuild three ways in Chapter 27—through its final, hardest compression: from a full report into a single page that the leadership team can read in a minute and act on. Fictional but realistic; the failure is one of the most common in business.

The setup

Dana Whitfield, a data scientist, has finished the analysis the whole company has been waiting on. New-customer churn nearly doubled in two quarters (5.1% → 9.3%), and her model identified the cause: onboarding speed, not price or product. Customers who reach their first real "win" within a week churn at 3%; those who take longer than three weeks churn at 22%—seven times higher. The leak is in week one, which is exactly where the company's retention budget isn't. Her recommendation is clear: move retention spend upstream into a first-week onboarding redesign.

She wrote it up properly—a twenty-two-page report with the model, the data, the validation, and the secondary findings. She sent it to the leadership team ahead of their Monday strategy meeting. On Friday, her manager forwarded a reply from above:

"Can someone get me a one-pager on this before Monday? I won't have time for the full deck."

This is the moment the chapter is about. The analysis is done and it's good. The decision now depends entirely on whether Dana can get it onto one page that survives a sixty-second read—because for the leader who sent that note, the one-pager is the twenty-two pages. Everything Dana did is about to be experienced through a single sheet of paper.

The first attempt: a shrunken report

Under time pressure, Dana did what most people do first: she took the report's executive summary, trimmed it, and squeezed it onto a page.

Customer Retention Analysis — Summary Background: Over the trailing two quarters, the analytics team analyzed customer retention in response to leadership's concern about rising attrition. Methodology: We extracted cancellation records for 4,812 new accounts and built a random-forest classifier (300 trees, 5-fold cross-validation, ROC-AUC 0.81) to identify the strongest predictors of 90-day churn, controlling for plan tier and acquisition channel. Findings: Time-to-first-value emerged as the dominant predictor. Accounts reaching first value within 7 days churned at 3%; those exceeding 21 days churned at 22%. Quarterly churn rose from 5.1% to 9.3%. Secondary findings regarding support-ticket volume and plan tier are detailed in the full report. Recommendation: Leadership may wish to consider reallocating retention resources toward the onboarding experience…

It fit on a page. It was accurate. And it failed—for the same reason her first churn memo failed back in Chapter 27. It led with "Background" and "Methodology." The random-forest details (300 trees, ROC-AUC 0.81) ate space a leader cannot use. The recommendation—the only thing the reader actually needs—was the last line, softened to "may wish to consider." She had kept the report's priorities, not the reader's. It was twenty-two pages with the air let out, and the decision was still buried at the bottom.

The diagnosis

Dana caught it herself by running the chapter's two tests.

The standalone test (Chapter 20): Could the leader decide from this page alone? Barely. The recommendation was there, but at the bottom, hedged, after a methodology wall. A sixty-second reader would not reach it.

The altitude check (Chapter 2): What is this reader's job, and what do they need to do? Decide whether to move budget. They do not need to evaluate her model—they need her judgment, which they trust, distilled to the decision and its justification. She was showing her labor; they were paying for her judgment.

The fix was not to trim more words. It was to rebuild the page around the decision, using the one-pager hierarchy: recommendation → 2–3 numbers → the single strongest piece of evidence → cost/risk → dated next step → everything else demoted.

The rewrite: re-conceived around the decision

ONE-PAGER · Customer Retention · For: Leadership Team · From: D. Whitfield · [date]

Recommendation: Move retention budget out of renewal win-backs and into a redesigned first-week onboarding experience. Requesting approval Monday to scope it.

Why it matters: - We lose ~1 in 4 new customers in their first 90 days. Churn has nearly doubled in two quarters (5.1% → 9.3%). - This is our largest controllable drag on new-customer revenue right now.

The finding that decides it: - The leak is in week one, not at renewal. Customers who reach their first "win" within a week churn at 3%; those who take longer than three weeks churn at 22%—seven times higher. - The cause is onboarding speed—not price, not product. (Holds across plan tiers.)

What it takes / the risk: - One quarter of redesign work; temporary reallocation of ~2 marketing headcount. - Risk is low and reversible—we can measure the effect within one onboarding cohort before committing further.

Next step: Approve scoping on Monday. Costed plan to leadership by month-end.

Full model, data, and secondary findings available on request.

What changed, and why each change matters:

  • The recommendation is the first line. A sixty-second reader gets the decision before anything else—BLUF (Chapter 4) at the scale of a whole report.
  • Two stakes numbers, not ten. "1 in 4" and "nearly doubled" carry the urgency; the random-forest internals are gone (they don't help this reader decide).
  • The single decisive comparison gets its own prominent line. 3% vs. 22%, seven times—the one fact that makes the case. Everything Dana proved compresses into that contrast.
  • Cost and risk are named honestly (one quarter, ~2 headcount, low/reversible). Naming the catch builds trust (Chapter 20); hiding it would look naïve.
  • The method—the entire apparatus that filled the "before"—is demoted to one line: "Full model, data, and secondary findings available on request." It's there for anyone who wants it; it's out of the way of the decision.
  • The ask is dated and specific: approve scoping Monday, costed plan by month-end. Not "may wish to consider."

The page wasn't shortened. It was rebuilt. And notice what it is: the exact same finding from Dana's Chapter 27 memo, carried one more rung up the compression ladder—from a memo for one VP to a one-pager for the leadership team.

What the one page unlocked

On Monday, the leader who'd asked for the one-pager opened the meeting with it already decided: "I've read Dana's page. The week-one number is the thing—let's scope the onboarding redesign. Dana, what do you need?" The twenty-two-page report was never opened in the room. It didn't need to be. It existed as the depth behind the page—the thing one skeptical VP asked Dana to walk him through afterward, the thing that made the page trustworthy. But the decision was made off the single sheet.

That is the chapter's whole thesis in one scene. Dana's three weeks of rigorous analysis reached the decision-makers and changed what the company did—not because the analysis was good (it always was), but because the delivery finally matched the reader. The work and its delivery are separate skills, and the leader only ever experienced the second one.

The lesson

The one-pager that worked wasn't shorter than the one that failed—it was the same length. It was re-conceived: built around the one decision the reader had to make, with the recommendation first, the stakes quantified, the single strongest fact made prominent, the method demoted, and a dated ask at the end. The failed version kept the report's order; the successful one kept the reader's. A one-pager is not a small report—it is a decision, on a page, for someone who has a minute. Dana's analysis didn't change between Friday and Monday. The page did.

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