Do 20% more bookings prove the thesis?
Test an AI-written demand claim against cash, inventory and customer evidence.
“Recognize variant views versus the market” (opens the source)
The question
You are researching fictional Alder Signal. A quarter’s bookings rose from $100m to $120m. A draft pitch calls this evidence of 20% end-customer demand growth. Bookings are customer orders, not revenue. The table covers the same quarter in each year.
| Prior year | This year | |
|---|---|---|
| Bookings ($m) | 100 | 120 |
| Cash receipts ($m) | 80 | 80 |
| Distributor inventory (months) | 2 | 4 |
Invented observations. They are warning signals, not proof of fraud or a forecast of earnings.
Use public filings and approved research channels. Do not request confidential customer orders, unpublished results or other restricted information.
“What is the variant view, how would you test it, and what evidence would make you reject it?”
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A strong answer, step by step
Open each step in turn. This is one strong answer, not the only one.
Step 1: Separate the observation from the claim
What would you do here? Open the move you’d make.
Call the business fraudulent because cash did not rise.
Tempting, but it misses something. Timing differences can explain the gap; these data do not prove intent.
Keep 20% bookings growth as fact; treat demand growth as a hypothesis.
The strong move. The three series measure different things and may have different timing.
See how a strong candidate says it
“Bookings rose 20%. Cash receipts are flat and distributor inventory doubled. That does not yet establish 20% growth in end-customer use.”
Why it works: The three series measure different things and may have different timing.
Step 2: State a real disagreement
What would you do here? Open the move you’d make.
Say the consensus is wrong because AI says so.
Tempting, but it misses something. The prompt gives no consensus forecast and no source for that claim.
Compare the pull-forward hypothesis with published expectations.
The strong move. A variant view needs an actual baseline; disagreement cannot be invented.
See how a strong candidate says it
“My candidate variant is that distributors pulled orders forward, so the market may overstate repeat demand. I first need a documented market expectation.”
Why it works: A variant view needs an actual baseline; disagreement cannot be invented.
Step 3: Choose evidence that distinguishes the views
What would you do here? Open the move you’d make.
Ask a distributor for Alder’s unpublished quarterly results.
Tempting, but it misses something. Confidential results are not a permissible shortcut.
Test sell-through and cancellations through approved channels.
The strong move. The research must test the mechanism and obey the firm’s rules.
See how a strong candidate says it
“I would reconcile booking terms and reported revenue, then use approved channel checks for sell-through and cancellations. I would separate price, volume and timing.”
Why it works: The research must test the mechanism and obey the firm’s rules.
Step 4: Write the kill criterion before the result
What would you do here? Open the move you’d make.
Keep the short thesis until the share price falls.
Tempting, but it misses something. Price alone cannot prove the demand mechanism; this makes the thesis unfalsifiable.
Name a measurable result that would reject the pull-forward view.
The strong move. The threshold is an authored test of this thesis, not an industry rule or a fact already observed.
See how a strong candidate says it
“My pull-forward view weakens if the next quarter’s publicly reported or approved-channel sell-through index is at least 110 against last year’s 100 and inventory returns to two months without discounting.”
Why it works: The threshold is an authored test of this thesis, not an industry rule or a fact already observed.
The answer, in short
- Decision
- Do more research before using 20% demand growth in a pitch.
- Because
- Bookings rose 20%, cash stayed flat and inventory rose from two to four months. None is a clean end-demand measure.
- What would change it
- Sustained sell-through, normal inventory and a reconciliation of bookings to revenue that rejects the pull-forward hypothesis.
Common traps
- Inventing a consensus estimate.
- Treating a warning signal as proof of fraud.
- Moving the falsification threshold after new facts arrive.
Check your answer
- Did I separate bookings from end demand?
- Did I avoid claiming fraud?
- Did I ask for lawful evidence that distinguishes explanations?
- Did I state a falsification threshold before seeing the result?
Last reviewed Nov 10, 2026