Opportunity Evaluation And Judgment

---
name: opportunity-evaluation-and-judgment
description: "Restates an identified opportunity as a falsifiable claim and structurally evaluates it against fixed criteria — market viability, feasibility, resource fit, strategic fit, risk — before resources are committed. Use once an opportunity has already been noticed and needs a deliberate go/no-go judgment, not another round of scanning for more ideas."
---

# Opportunity Evaluation & Judgment

## Purpose

Structurally assesses the viability of an identified opportunity before
resources are committed to it — the deliberate, evaluative counterpart to
the noticing done in `market-and-signal-scanning` and the connecting done in
`pattern-and-analogy-connector`.

## Anchored in research

- Tang, J., Kacmar, K. M., & Busenitz, L. (2012), "Entrepreneurial Alertness
  in the Pursuit of New Opportunities," *Journal of Business Venturing*,
  27(1), 77–94 — **evaluation and judgment**, the third of the paper's three
  dimensions of entrepreneurial alertness (alongside scanning-and-search and
  association-and-connection, which anchor
  `../market-and-signal-scanning/SKILL.md` and
  `../pattern-and-analogy-connector/SKILL.md` respectively). Evaluation and
  judgment is the deliberate weighing of a noticed opportunity against
  criteria such as feasibility, risk, and fit — distinct from the earlier,
  more intuitive noticing and connecting stages.
- SFIA (Skills Framework for a Digital World) — **Business Situation
  Analysis**, a professional skill definition describing the systematic
  investigation of a business situation or problem to identify options,
  risks, and success criteria before a course of action is chosen.

## Method

1. **State the opportunity as a testable claim, not a description.** Before
   evaluating, restate the opportunity as a specific claim that could turn
   out to be false (e.g. "Segment X will pay for Y because Z"), not just a
   general description of an idea — evaluation only works against a claim
   that's falsifiable.
2. **List the criteria the opportunity will be judged against**, decided in
   advance rather than picked to fit the answer you already want: typically
   market viability, technical/operational feasibility, resource fit,
   strategic fit, and risk exposure. Keep the criteria list stable across
   opportunities you're comparing, so judgments stay comparable.
3. **Gather the evidence available for each criterion**, and be explicit
   about the strength of that evidence — a validated customer interview is
   not the same class of evidence as an internal assumption. Where evidence
   is missing, mark it, don't fill the gap with a guess
   (`[assumption — verify]`).
4. **Apply deliberate judgment, separated from the initial noticing.** This
   is the step Tang, Kacmar & Busenitz's model is built around: consciously
   switch from "does this feel promising" (the alertness that got you here)
   to "does this hold up against the stated criteria" — the two are
   different cognitive modes, and collapsing them tends to let excitement
   about the pattern override an honest look at the evidence.
5. **Identify the single biggest point of uncertainty** — the one
   assumption that, if wrong, would most change the conclusion. Naming it
   explicitly turns the evaluation into an actionable next step (test that
   assumption) rather than a static verdict.
6. **Produce a structured verdict**: viable / viable with named conditions /
   not viable as currently framed — each with the reasoning that led there,
   so the next reader can see *why*, not just *what*.
7. **Route the outcome onward.** A "viable" or "viable with conditions"
   result feeds into `../opportunity-value-assessment/SKILL.md` (or this
   pack's own scoring, once the owner's version is filled in) for a fuller,
   two-dimensional assessment.

## 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 clearly flags an assumption
  (`[assumption — verify]`).
- Doesn't make a binding go/no-go call — it structures the criteria for the
  decision-maker.
- Doesn't skip straight to judgment without first stating the opportunity as
  a testable claim and naming the evaluation criteria — doing so invites
  post-hoc rationalization of a conclusion already reached informally.

## 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

Once this section is filled in and validated in practice, update the
`maturity` field in `skills_index.json` to `draft`, `validated`, or
`canonical` (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: `../market-sizing-tam-sam-som/SKILL.md` — Quantitatively
  sizes the market and the genuinely reachable share of it.
- The owner's validated, productized version of this same task:
  `../opportunity-value-assessment/SKILL.md` — a concrete 2D matrix + 7-lens
  assessment, `maturity: validated`.
- 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` — this pack's shared guardrails