strategic-options-evaluation
Compares strategic options, including "do nothing", on a fixed set of dimensions (impact, effort, risk, reversibility, resource fit), scored independently per option and plotted on at least two views
SKILL.mdstrategic-thinking/skills/strategic-options-evaluation/SKILL.md
GitHubStrategic Options Evaluation
Purpose
Compares strategic options in a structured way — impact, effort, risk, and resource fit — so a decision is made against a consistent set of criteria instead of whichever option was argued for most persuasively.
Anchored in research
- McKinsey — structured problem solving
- Liedtka (1998) — intelligent opportunism: staying alert to good options that emerge outside the original plan, and evaluating them with the same rigor as the options that were planned for.
Method
- List the real options, including "do nothing." An evaluation with only one live option isn't a comparison — make sure at least one genuine alternative, including the status quo, is on the table.
- Fix a small, consistent set of comparison dimensions before scoring any option — typically impact, effort/cost, risk, reversibility, and resource/capability fit. Deciding the dimensions after seeing the options invites motivated reasoning toward a preferred one.
- Score each option on each dimension independently. Resist collapsing straight to a single overall ranking before the dimension-level picture is visible — a lot of the useful information is in where options diverge, not just which one wins on average.
- Plot the options on at least two views (e.g. impact vs. effort, and impact vs. risk) rather than relying on a single composite score — a single number hides trade-offs a decision-maker needs to see.
- Separate reversible from irreversible options explicitly. A high-impact but reversible option (a pilot, a limited rollout) can reasonably beat a similarly-scored irreversible one, even at the same "impact" score — reversibility changes the real risk, not just the variance.
- Produce a decision-ready comparison, not a recommendation disguised as analysis — the output should make the trade-offs legible enough that a different, reasonable person could look at the same table and pick differently for defensible reasons.
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 make the final choice for you — it structures the options into decision-ready, comparable material.
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
- Once this step is done, move to
../../../opportunity-recognition/skills/market-and-signal-scanning/SKILL.md - 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