Prioritization Framework Advisor
Pick the right prioritization framework (RICE, ICE, Value/Effort, Kano, Buy-a-Feature) based on product stage, team context, decision needs, and data availability — avoid framework whiplash.
Your team adopted RICE last quarter, and now you're spending 30 minutes per ticket arguing about Reach numbers you can't actually measure. RICE isn't bad — it's wrong for your stage. Pre-PMF needs ICE. Misaligned stakeholders need Buy-a-Feature. Strategic bets need Kano. There's no "best" framework — only the wrong one for your situation.
Who it's for: PMs choosing first prioritization framework, product leads switching from broken process, founders aligning stakeholders, engineering managers ending HiPPO debates
Example
"We have 100+ backlog items, no usage data yet, and we're pre-PMF" → Recommendation: ICE or Value/Effort (not RICE — no Reach data; speed > rigor) + 4-step implementation + alternative + pitfalls + reassess triggers
CLAUDE.md Template
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npx ccplaybooks add prioritization-advisor# Prioritization Advisor
Choose the right prioritization framework based on stage, team context, decision-making needs, and data availability. Avoid framework whiplash and applying the wrong tool (e.g., RICE for strategic bets, ICE for data-driven decisions).
Not a scoring calculator — a decision guide that matches frameworks to your situation.
## The Framework Landscape
**Scoring frameworks:**
- **RICE** (Reach, Impact, Confidence, Effort) — data-driven, requires metrics
- **ICE** (Impact, Confidence, Ease) — lightweight, gut-check
- **Value vs. Effort** (2x2) — quick wins vs. strategic betsGet new playbooks like this one
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What This Does
Asks 4 adaptive questions (stage / team / decision need / data) and recommends from RICE, ICE, Value/Effort, Weighted Scoring, Kano, Opportunity Scoring, Buy-a-Feature, MoSCoW, Cost of Delay, Impact Mapping, or Story Mapping. Outputs implementation steps, example scoring, and an alternative for hedging.
Pairs with user-story (output of prioritization), epic-hypothesis, and recommendation-canvas.
Quick Start
mkdir -p ~/Documents/PrioritizationAdvisor
mv ~/Downloads/CLAUDE.md ~/Documents/PrioritizationAdvisor/
cd ~/Documents/PrioritizationAdvisor
claude
Provide product stage, team context, primary decision-making challenge, and data availability. Claude recommends the right framework with implementation guidance.
The 4 Questions
| Question | Drives |
|---|---|
| Product stage (pre-PMF / scaling / mature / multi-product) | Speed vs. rigor tradeoff |
| Team context (small / aligned / misaligned / large org) | Process weight + consensus needs |
| Decision-making need (filtering / alignment / data-driven / tradeoffs) | Framework type |
| Data availability (minimal / some / rich) | Scoring sophistication |
Tips & Best Practices
- Match framework to stage, not preference. Pre-PMF doesn't need RICE; mature products shouldn't run on ICE.
- Commit for 6-12 months. Switching every quarter creates whiplash and erodes trust.
- Score collaboratively. PM-only scoring lacks buy-in; engineering + design must participate.
- Override scores when strategic. Frameworks are inputs, not automation. PM judgment wins ties.
- Reassess triggers. Stage change, team reorg, stakeholder shift = reassess. Otherwise leave alone.
Common Pitfalls
- Pre-PMF startup using weighted scoring with 10 criteria (overhead kills speed)
- Switching frameworks every quarter (no consistency, lost trust)
- Treating scores as gospel ("8000 vs. 7999 means A wins")
- Solo PM scoring with no design/eng input
- No framework at all → HiPPO (Highest Paid Person's Opinion) wins