Pilot2Service Hypothesis-Driven Strategy
Purpose
Structures a strategic problem with MECE and an issue tree, then tests the resulting hypotheses against data — instead of either guessing an answer or trying to analyze everything before forming a point of view.
Anchored in research
- McKinsey — MECE / issue trees / hypothesis-driven problem solving
- Liedtka (1998) — hypothesis-driven
- Conn & McLean (2018), Bulletproof Problem Solving — a detailed, published account of this exact method: state a hypothesis early, break it into a MECE issue tree, and prioritize the branches by how cheaply and decisively they can be tested.
Method
- State an initial hypothesis — your best current answer to the strategic question, stated specifically enough to be provably wrong. "We should grow" is not a hypothesis; "we should grow by expanding into segment X before competitor Y does" is.
- Break the question behind the hypothesis into a MECE issue tree. Each branch should be a sub-question that must be true for the hypothesis to hold, and the branches together should cover the question completely without overlapping (Mutually Exclusive, Collectively Exhaustive).
- For each branch, define the minimum evidence that would prove or disprove it — not "more data is better," but the smallest, cheapest, most diagnostic piece of evidence that would move your confidence.
- Prioritize branches by diagnostic value, not by ease of access. Test the branch most likely to kill the hypothesis first — a hypothesis that survives its own strongest challenge is far more useful than one that was only ever tested against easy questions.
- Update the hypothesis as evidence comes in. This is iterative, not a single pass: a disproven branch should change the hypothesis itself, not just get logged as a caveat.
- Stop when the hypothesis is decision-ready, not when the tree is exhaustively filled in — the goal is a defensible point of view fast enough to act on, not total analysis.
What this skill does NOT do
- Doesn't make the final decision for you — it produces a structured draft to support a human decision.
- Doesn't confirm figures, market data, or competitor data from memory — it
uses the inputs you provide, or marks an assumption clearly
(
[assumption — verify]). - Doesn't collect or analyze data on your own behalf — it structures the questions the data needs to answer.
Refinement notes
Areas to keep deepening with real practice:
- your own rules of thumb and heuristics for this technique
- concrete templates (into
../../references/) - reference cases / your own examples
- what this skill deliberately does not do (guardrails, common mistakes) — add to the list above
This is an internal working note, not a claim about the skill's current
usability. Track depth privately via the maturity field in
skills_index.json (see
../../../meta/maturity_levels.md).
Don't add new fields to the frontmatter — name and description are
the only ones allowed (see
../../../meta/frontmatter_schema.md).
Continue from here
- Next in this pack:
../scenario-and-foresight/SKILL.md— Builds alternative future scenarios and stress-tests a strategy against them. - A ready-made skill chain for this situation: see
../../../playbooks/ - This pack's shared guardrails:
../../CLAUDE.md
References
../../references/— the pack's shared background material../../CLAUDE.md— the pack's shared guardrails