── ── Strategy
Scenario Planning
Scenario planning accepts that certain futures are genuinely unknowable and prepares for several of them rather than betting on one forecast. Pierre Wack formalized this at Shell in the early 1970s; Shell's pre-built Scenario B let it survive the 1973 oil shock while competitors were unprepared. Schwartz: "The goal is not to predict the future but to make decisions that…
Run Scenario Planning on a real problem
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How it works
Run the Scenario Matrix. Focal question first, then drivers, then the 2×2, then strategy derivation.
Stop-rule: At Step 3, if you cannot find at least one critical uncertainty that is both (a) highly impactful and (b) genuinely bi-directional, stop — run a sensitivity analysis instead.
1. State the focal strategic question. Specific: names a decision, a time horizon, and the driving uncertainty. 2. Identify key drivers. Sort into predetermined elements (background constants) and critical uncertainties (highly impactful, genuinely bi-directional). 3. Select the two most critical uncertainties. Most impactful on the focal question AND most independent of each other. Each axis has two plausible poles — not "good vs bad." 4. Build the 2×2 Scenario Matrix. Name each quadrant memorably. Write a full narrative paragraph per scenario: internally consistent, no contradictions. Quality check: does at least one scenario make the team uncomfortable? 5. Derive strategic implications. For each scenario: current strategy performance, biggest opportunities, biggest threats, most valuable capabilities. 6. Identify robust moves and contingent bets. Robust moves = act now. Contingent bets = hold until leading indicators fire. Assign 3–5 leading indicators per scenario with monitoring owner and review cadence.
When to use it
- user says 'what are the scenarios,' 'stress test our strategy,' 'what if X happens,' 'multiple futures,' 'strategic resilience,' or is making a high-stakes irreversible decision with a 3+ year horizon where a single forecast could be catastrophically wrong
When not to use it
When the decision is routine and reversible, applying a formal method costs more than it returns.
Worked example
An Enterprise Buyer's AI-Adoption Bet Under the Capex + Chip Fog (2024–2026)
A companion to the infrastructure-provider case, viewed from the other side of the invoice. Where that example is a compute-heavy vendor sizing its buildout, this one is a large enterprise (say, a bank, retailer, or manufacturer) deciding how deeply to commit to a single AI vendor and platform over a multi-year horizon. Same two macro uncertainties; a different decision-maker seat, and therefore different robust moves. As of early 2026 the outcome was genuinely open, which is the condition under which the method earns its keep…
Install this skill (free, MIT)
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