Scores multiple solution directions with the RICE model (Reach, Impact, Confidence, Effort) to select an MVP, and turns the choice into an MVP definition, a one-sentence positioning statement, and three 'why we win' claims.
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---
name: rice-scoring-and-mvp-synthesis
description: "Scores multiple solution directions with the RICE model (Reach, Impact, Confidence, Effort) to select an MVP, and turns the choice into an MVP definition, a one-sentence positioning statement, and three 'why we win' claims."
---
# RICE Scoring and MVP Synthesis
## Purpose
Turn a comparison of multiple solution alternatives into an objective,
justified MVP choice using the RICE model, and translate that choice
directly into a usable strategy: what the MVP exactly does, how it's
positioned in one sentence, and why exactly this one wins. This is a
bridge skill between solution ideation (many alternatives) and writing
the PRD (one chosen direction).
## Based on
- The RICE prioritization model (Reach, Impact, Confidence, Effort) — a
generally known product-prioritization framework, not the owner's own.
- The methodology of an external "AI-first SaaS Product" workshop,
applied by the owner to one own case — see
`../../references/ai-first-saas-workshop-source.md` and the worked
example `../../cases/ai-decision-coach-mvp-case.md`, sections 6–7.
**Note:** applied only once so far — not broadly validated.
## Method (draft — to be filled in further)
1. **Score each solution direction on four criteria (1–5):**
- **Reach** — how many users this would touch.
- **Impact** — how significant the effect is for the user it touches.
- **Confidence** — how sure you are that your Reach/Impact/Effort
estimates hold up (high = strong evidence, low = a guess).
- **Effort (inverted: 5 = easiest/lowest effort, 1 = hardest/highest
effort)** — note the inversion: in this model a high Effort score
means LOW build cost, so all four criteria sum in the same
direction (higher = better MVP candidate).
2. **Calculate the total RICE score** (max 20 across the four criteria,
or scale as needed) for each direction and rank them.
3. **Briefly justify the score for each criterion** — don't leave scores
unexplained. In particular, tie the Effort estimate concretely to the
existing tech stack/data/tools (what already exists vs. what needs to
be built from scratch).
4. **Choose the MVP with the highest RICE score**, UNLESS a specific
strategic reason favors another (e.g. a higher-Effort direction is the
only one that proves a genuine differentiator, not just table-stake
value). If you deviate from the highest score, explicitly justify why.
5. **Write the MVP definition (2-3 sentences).** Combine the chosen AI
wedge (differentiator need) and the essential table-stake needs into
one concise description of what the MVP does and for whom.
6. **Sketch the MVP flow concisely** (5-8 steps): user input → AI
synthesis/scoring → decision engine/logic → AI output(s) → next-step
plan → (optional) communication support → (optional) path to deeper
tools.
7. **Write a one-sentence positioning statement.** Format: "[Product]
gives [target customer] [core benefit] through [distinctive
mechanism]." Test: could this sentence describe any competitor? If
yes, it isn't specific enough yet.
8. **Write 3 "why we win" claims.** Each claim ties one strength
(differentiator need, existing data/tool, unique approach) to a
concrete competitive advantage — not general claims ("we're better")
but justified reasons.
9. Carry the MVP definition, flow, positioning statement, and "why we
win" claims into `../ai-buildable-prd-writing/SKILL.md` as the basis
for the PRD.
## What this skill does NOT do
- Does not make the final MVP choice for you in a fully mechanical way —
the RICE score supports the decision, it isn't an automatic rule; a
strategic deviation from the highest score is allowed if justified.
- Does not assess financial viability or unit economics — only relative
prioritization between solution alternatives. See
`../../../../business-case-and-analysis/skills/roi-npv-sensitivity-model/SKILL.md`
for deeper financial modeling once the MVP is chosen.
- Does not replace `../../../opportunity-recognition/skills/opportunity-evaluation-
and-judgment/SKILL.md` — this is a narrower, faster choice between
2-3 already-identified solution directions, not a full assessment of
an opportunity from scratch.
## Refinement notes
This skill has so far been applied to one case (the owner's own case).
As you apply it to more businesses, add:
- your own rules of thumb for when it's worth deviating from the
highest RICE score
- concrete examples of positioning statements and "why we win" claims
from other cases in the `../../cases/` folder
Once this section has been filled in with multiple cases, raise
`skills_index.json`'s `maturity` field to `validated`
(see `../../../../meta/maturity_levels.md`).
## Continue from here
- Preceding skill in this pack:
`../ai-differentiator-solution-ideation/SKILL.md` — produces the three
alternatives scored here.
- Next skill in this pack: `../tiny-core-identification-and-feature-freeze/SKILL.md`
— once a direction is chosen here, isolates the one interaction that
is its actual reason to exist and blocks feature creep before the PRD
is written.
- Next skill in this pack: `../ai-buildable-prd-writing/SKILL.md`
— writes the PRD for the chosen MVP.
- Related skill in this pack, if the chosen MVP is a conversational/
agentic product: `../ai-native-conversational-os-design/SKILL.md`.
- Worked example: `../../cases/ai-decision-coach-mvp-case.md`, sections 6–7.
- The pack's shared guardrails: `../../CLAUDE.md`
## References
- `../../references/ai-first-saas-workshop-source.md` — source information
- `../../cases/ai-decision-coach-mvp-case.md` — worked example
- `../../CLAUDE.md` — the pack's shared guardrails