Storytelling with data — making the case to GM and owner

Tuesday morning, November 21, Hotel Peaqplus City. Daniel walks into Adam’s office with four printed tables: a pace report (pace — the tempo of booking build-up against the historical curve), a booking window analysis (how far before arrival guests book), a segment breakdown, a compset extract. His proposal: −18% off the BAR (Best Available Rate — the best publicly available rate) for the weekdays between December 4 and 21, locked into a two-night package. The pace of the Christmas-market weekdays is at a three-year low.

At the third table Adam looks up and cuts him off: “Stop. We have never cut rates in the Christmas season. It’s our strongest brand period — if we give in now, we tell the market something is wrong. And the owners? What they will see is that we discounted the peak season. No.” The conversation is over in four minutes.

Daniel sits back down in his office and forces himself not to be angry at Adam but to look at his own performance. The analysis was good. The numbers were right. The sale failed. He carried tables into a decision situation — and Adam didn’t react to the tables but to the phrase he heard in the first sentence: “a rate cut in the Christmas season”. From that moment on he wasn’t listening to an analysis; he was defending.

This lesson is about what Daniel learns that afternoon: after analysis and decision-making, the senior RM has a third skill — making the case. A decision is worth as much of it as gets accepted and executed. Routine decisions are carried through by routine; the ones that depart from the usual have to be sold — and the sale doesn’t turn on the quantity of the numbers but on their arrangement.

The third skill — and what it is not

Let’s first clear up what storytelling is not. Not manipulation, not “rounding the numbers prettier”, not a rhetorical trick. Storytelling with data means: you arrange the numbers into an order fit for a decision, adjusted to the listener’s head. The same facts, the same truth — but built so that the recipient can follow the path from problem to decision, and gets answers to their own objections along the way.

In lesson 53 we saw how forty pages of numbers become a five-sentence, human-readable report — there the subject was the machine narrative: the system writes up what happened and why. This lesson is its pair, from the human side — and the difference is sharp. The narrative informs: it makes the past understandable. The argument persuades: it gets a contested future step accepted. The narrative a machine can write for you; the argument it cannot — because there it isn’t the numbers that are hard but the human sitting across the table, with their own experience, fears and responsibility towards the owners. Adam’s “no” didn’t come from a lack of data; it came from the proposal detonating on his risk map: brand, precedent, owner reaction. Until those have answers, the fifteenth table won’t help.

The story arc — six elements of a persuasive data story

The methodological core is an arc along which a proposal that departs from the usual can be walked. It is not decoration — each element covers a typical point of failure:

Notice what Daniel’s first, Tuesday attempt did: he started at element 2 (the pace tables) and would have continued at 4 — elements 1, 3 and 5 never appeared at all. So what Adam heard was a rate cut with no shared goal, no stakes and no risk handling. In that structure his “no” was a rational answer.

Element three deserves its own spotlight, because almost everyone skips it. The risk of your proposal is always visible — the risk of inaction never is, until you compute it. Yet the status quo is a decision too (we saw it in lesson 47: not deciding is also a decision — there taken consciously, here slipping in by reflex), and it has a price. Until you say that price out loud in EUR, in the debate your proposal is the “risky” one and doing nothing is the “safe” one — when it is often exactly the other way round.

The worked example: building the case package

Let’s see how Daniel’s case package is built along the six elements — with the numbers he assembles by the next day.

The terrain: between December 4 and 21, 12 weekday nights (Monday–Thursday), 80 rooms → 960 sellable room nights. The weekends are fine — the Christmas market brings them —; the problem is specifically midweek.

(1) Anchor. Not a number but the first sentence — we’ll see it live in the Wednesday scene. Its essence: the shared goal stated before anything contestable is said.

(2) Tension — the pace table:

The 31% sits meaningfully below the same-point values of the past three years (44–47%), and the booking window is shortening too — demand is arriving later and thinner.

(3) Stakes — the cost of inaction. Daniel projects the pace ratio forward (lesson 20’s proportional method): this year’s OTB is 66% of last year’s; if the remaining pickup arrives in the same proportion, last year’s 203 room nights yield ~134, so the expected final without a pricing move is 432 room nights (45%). Handling the uncertainty of the window shift and the compset pressure with a ±22 room-night band: 410–454. Against last year’s 654, the shortfall at the midpoint is 222 room nights (band: 200–244). Last year’s realised weekday ADR for the period was 126 EUR, so the expected cost of inaction in room revenue: 222 × 126 = 27,972 — call it 28,000 EUR (band: 25,200–30,750). That is the amount by which December’s weekdays close below their last-year selves if we do nothing — and since the Q4 target was built on last year’s level, this hole will be missing from the Q4 target one for one.

(4) Solution — with a mechanism. The weekday BAR is 128 EUR. The proposal: a two-night midweek Christmas-market package at 105 EUR/night (−18%), exclusively on closed channels — newsletter, regular-guest circle, direct offers. Why a package and why closed: the public price position doesn’t move (we come back to this in the steelmanning part). Why −18: by lesson 36’s elasticity logic, midweek city-break demand moves in the price-sensitive band, and based on earlier closed campaigns the expected yield at this depth is +45 package bookings, i.e. +90 room nights, under a 20% cannibalization assumption (a fifth of the package guests would have booked at BAR anyway). The net effect: 72 genuinely new room nights × 105 EUR = 7,560 EUR, minus the price loss on the 18 cannibalized room nights (128 − 105 = 23 EUR/night → 414 EUR) = +7,146 EUR in room revenue, plus the package guests’ F&B spend (~22 EUR per room night × 72 ≈ 1,600 EUR). (In a margin view, per lesson 46, the variable cost of the new nights would also be deducted — it doesn’t change the proportions.) And Daniel also says what a weaker persuader would hide: this is roughly a quarter of the 28,000 hole. The package doesn’t make the problem disappear — it brings back the realistically recoverable part, with price discipline, while protecting organic pickup by leaving the public rate untouched.

(5) Risk handling — trigger and retreat. If the package doesn’t bring at least +30 room nights (15 bookings) in its first 10 days, we withdraw it. The worst case then: every package booking so far was cannibalization — 30 × 23 = 690 EUR of capped loss. So the exposure is not symmetric: the expected cost of inaction is 28,000 EUR, the proposal’s closed-off maximum risk is under 700 — a forty-to-one ratio.

(6) The decision question: “May I launch the closed package from Thursday, with the 10-day trigger? If we don’t decide by Thursday, the offer no longer reaches the first Christmas-market week’s weekdays.” One question, one deadline, and the deadline has a reason — not pressure, but the fact of the booking window.

Answering the objections in advance — steelmanning

The story arc alone is not enough if three objections keep rattling in the listener’s head — because while they rattle, he isn’t listening. The rule: you say the counter-argument first — whoever says it first, handles it. And say it in its strongest form (this is called steelmanning, the opposite of strawmanning), not in an easily knocked-down version — Adam will notice immediately if all he gets back is a caricature of his own argument.

From Adam’s Tuesday reaction Daniel already knows the three objections, and he builds the answers into the Wednesday material:

Notice: all three answers became part of the proposal, not after-the-fact defence. The closed channel, the condition-bound rule and the owner supplement are not communication scenery — they are what made the proposal better than Tuesday’s version. Pre-processing the counter-arguments often improves not only the sale but the decision itself.

The same argument, in two languages

The root of the principle goes back to lesson 4: we saw there that RevPAR is the language of the bank and of compset comparison, while TRevPAR is the house-level verdict — the same house speaks a different metric at a different table. Lesson 53 brought the same back for the machine narrative: the same data wants a different reading for the RM, the GM, the owner. In persuasion all this is doubly true — because here understanding isn’t enough; the listener has to say yes, and everyone says yes to what feels reassuring on their own risk map.

• For Adam (the GM) the argument speaks operations and brand: what shows on the outside (nothing), what happens at the front office (a package code, two minutes of training), what the retreat plan is, and what he tells the owners. For him, the 28,000 figure lands as the defence of the Q4 target.
• For the ownership circle the same speaks cash flow and risk: expected revenue impact, capped downside, control points. Not “pace gap” and “BAR”, but “we have far fewer bookings than usual for December’s weekdays; without a move this means a ~28,000 EUR shortfall, and our move brings part of it back at a risk capped below 700 EUR”.

And here the senior RM’s real position shows: a mediator. The same reality told to the GM in brand language, to the owner in money language, to sales in partner language — and to Esther in marketing in campaign language, because the closed-channel send-out will be her handiwork. There aren’t four truths; there is one truth in four vocabularies. Experienced as translation drudgery, it is a burden; experienced as the work of making the case, it is the top of the craft.

Format: one page, one message

A few practical rules on which surprisingly many good arguments fail:

• One page, one message. The main material is a single page, the six arc elements in six paragraphs. The four tables go into an appendix — whoever wants to verify finds them there. A table is evidence, not an argument: the argument stands in the sentences.
• Say the headline number; don’t just show it. “Look at the third column” is not arguing. “Without a move we leave 28,000 euros on the table” — that is. A number works when it is caught in a sentence.
• A live meeting and a written document are not the same genre. Live, lesson 47’s principles rule: the data goes on the table before any opinion is voiced, and at the end stands a single decision question with a deadline. The written material, though, has to stand without you — the owner reads it when you are not in the room, which is why the pre-answered objections section is unskippable there.

Back to Tuesday — the second conversation

On Wednesday morning Daniel asks Adam for ten minutes. He puts down one page and starts with the anchor: “We want the same thing — holding the Q4 target and keeping the Christmas season strong. I have one problem, and one proposal with a capped risk.”

He walks the arc. At the pace table Adam still hums — “the window is shortening, they’ll come later” — and Daniel nods: “I counted that in; that’s why the estimate has a band. Late booking doesn’t explain a gap this size — this house has never produced that much late pickup.” The turn comes at the stakes. Adam looks at the number for a long time, then: “Against the 28 thousand I have no argument. So far I’ve been talking about what a move could cost us — not about what not moving costs.” When the closed channel and the 690 EUR capped downside land as well, Tuesday’s “no” becomes a conditional “yes”: “All right. I’ll send out the owner one-pager myself, with your text. And we honour the trigger — if it doesn’t bring the thirty room nights in ten days, we stop it, no debate.”

On Thursday the package goes live. Ten days later, the first read-back: 19 package bookings, 38 room nights — above the trigger threshold (30), and judging by where the bookings came from, cannibalization is running around the 20% assumption. The package stays; the next review point goes onto the weekly revenue meeting (lesson 28) as an agenda item with a metric. At the meeting Adam adds a single sentence: “The next proposal like this — bring it in exactly this format straight away.”

Traps

1. Data dumping. Twenty tables are not an argument but work-shifting: you push the synthesis — what follows from the twenty — onto the recipient, who won’t take it on; they reject or postpone instead. Daniel’s Tuesday failure was this. The table lives in the appendix; the argument lives in sentences.
2. Hiding the uncertainty. The temptation: instead of the 25,200–30,750 band, state a confident point estimate because it “sounds stronger”. It is the other way round: stating the band raises credibility — it signals that you know what you don’t know. And if your point estimate once misses spectacularly, it takes the credit of your next proposal with it; a band-stated estimate’s error stays inside the band, and your method stands.
3. The “the machine said so” argument. If you push the proposal away from yourself by pointing at the forecast or a model (“the system says we must act”), you lose two things: the responsibility — which since lesson 51 we know cannot be delegated — and the argument’s force, because Adam won’t debate a model; he will debate you, only now with distrust. The machine supplies the facts; the proposal is yours, with your name and your reasoning.
4. Playing to win. The goal is not defeating Adam but a jointly good decision. Whoever wins a debate often loses execution: the “persuaded” party who in truth merely lost returns at the first bad weekly number with “I told you so”. That is why the arc starts with the anchor, and why by the end Adam is co-owner of the decision — he sends the owner letter, he guards the trigger. At the end of a good argument what shows is not who won, but that the decision has two owners.

Key takeaways

• Making the case is the senior RM’s third skill: after analysis and decision, a decision is worth as much of it as gets accepted. Storytelling is not manipulation but arranging the numbers into a decision-ready order, adjusted to the listener — lesson 53’s machine narrative informs; this skill persuades.
• The six elements of the story arc: anchor (shared goal) → tension (the problem in numbers) → stakes (the cost of inaction) → solution (with mechanism) → risk handling (trigger + retreat plan) → decision question (one question, with a deadline). The most commonly skipped element is the stakes — yet until the price of the status quo is spoken, doing nothing looks safe.
• Risk asymmetry is the strongest argument: in the example the expected cost of inaction is ~28,000 EUR, the proposal’s trigger-capped risk 690 EUR — a forty-to-one ratio. Adam didn’t turn on the −18%; he turned on discovering that not moving has a price too.
• Say the counter-argument first, in its strongest form (steelmanning) — whoever says it first, handles it. And a well-handled objection often improves the proposal itself: the closed channel, the condition-bound rule and the owner supplement became part of the decision.
• One truth, several vocabularies: brand and operations language for the GM, cash-flow and risk language for the owner — the RM is the mediator. The four traps (data dumping, hiding uncertainty, “the machine said so”, playing to win) all destroy the same thing: credibility, the persuader’s only durable capital.