Scenario planning

SkillDev tools

Plans under genuine uncertainty — building scenarios, identifying which assumptions are load-bearing, setting early-warning indicators, and stress-testing a plan against futures rather than forecasting one. Use this when a decision depends on something unknowable, when a plan assumes conditions that may not hold, before a large irreversible commitment, or when a market, regulatory, or technology shift could invalidate the strategy.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Scenario planning skill

What this skill tells your AI

The instructions your AI receives, as published by cbrock84/headcount in plugins/corporate-strategy/skills/scenario-planning/SKILL.md and read by ahel’s review.

Forecasting produces one number and false confidence. Scenario planning produces a plan that survives being wrong, which is the realistic goal.

Separate what you know from what you are assuming

List the plan's assumptions explicitly, then sort them:

  • Predetermined — things that will happen regardless. Demographics, contracted commitments, technology already deployed. Plan around them; do not spend analysis on them.
  • Genuinely uncertain and load-bearing — the plan changes materially depending on how they resolve.

Almost every plan has two or three load-bearing uncertainties. Finding them is most of the value, and the exercise usually surfaces one nobody had articulated.

Build scenarios from the uncertainties, not from moods

The common failure is three scenarios named optimistic, base, and pessimistic — which is one scenario with the numbers scaled, and it teaches nothing.

Take the two most consequential uncertainties and build the quadrants. Each scenario should be internally coherent: if demand is high and supply is constrained, what else follows — pricing, competitor behavior, regulatory attention?

Give each a name that captures its logic. Names make scenarios usable in conversation, which is where they earn their keep.

Three or four scenarios. More cannot be held in mind; two collapses into best and worst.

Stress-test the plan against each

For every scenario: does the plan still work, what breaks first, and what would we wish we had done sooner?

The output is not a prediction. It is three things:

  • Robust moves — sensible in every scenario. Do these now, with confidence.
  • Contingent moves — right in some scenarios only. Prepare, do not commit.
  • Options — small investments that buy the right to act later. Deliberately underrated, because they look like indecision and are actually the cheapest way to handle uncertainty.

Early-warning indicators

For each scenario, name the observable signal that would show it is arriving — and specify it precisely enough to be checked. "Regulatory pressure increases" is not observable. "A second jurisdiction opens a consultation" is.

Assign each indicator an owner and a review cadence. Scenario work that produces no monitoring is a workshop, not a plan.

Revisit on the trigger, not the calendar

Most scenario planning is done once and filed. Its value comes from being revisited when an indicator fires — that is the moment the earlier thinking pays, because the options were identified before anyone was under pressure.

Never

  • Assign probabilities to scenarios and then plan only for the likeliest. That is forecasting with extra steps.
  • Build a scenario nobody in the room believes possible. It will be ignored, and the exercise loses credibility.
  • Let the exercise end without naming what to do on Monday in every scenario.

Signals

GitHub stars
1k
Forks
209
Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
scenario-planning
Source
github.com/cbrock84/headcount