Purpose

Guide product managers in choosing the right prioritization framework by asking adaptive questions about product stage, team context, decision-making needs, and stakeholder dynamics. Use this to avoid "framework whiplash" (switching frameworks constantly) or applying the wrong framework (e.g., using RICE for strategic bets or ICE for data-driven decisions). Outputs a recommended framework with implementation guidance tailored to your context.

This is not a scoring calculator—it's a decision guide that matches prioritization frameworks to your specific situation.

Key Concepts

The Prioritization Framework Landscape

Common frameworks and when to use them:

Scoring frameworks:

•RICE (Reach, Impact, Confidence, Effort) — Data-driven, requires metrics
•ICE (Impact, Confidence, Ease) — Lightweight, gut-check scoring
•Value vs. Effort (2x2 matrix) — Quick wins vs. strategic bets
•Weighted Scoring — Custom criteria with stakeholder input

Strategic frameworks:

•Kano Model — Classify features by customer delight (basic, performance, delight)
•Opportunity Scoring — Rate importance vs. satisfaction gap
•Buy-a-Feature — Customer budget allocation exercise
•Moscow (Must, Should, Could, Won't) — Forcing function for hard choices

Contextual frameworks:

•Cost of Delay — Urgency-based (time-sensitive features)
•Impact Mapping — Goal-driven (tie features to outcomes)
•Story Mapping — User journey-based (narrative flow)

Why This Works

•Context-aware: Matches framework to product stage, team maturity, data availability
•Anti-dogmatic: No single "best" framework—it depends on your situation
•Actionable: Provides implementation steps, not just framework names

Anti-Patterns (What This Is NOT)

•Not a universal ranking: Frameworks aren't "better" or "worse"—they fit different contexts
•Not a replacement for strategy: Frameworks execute strategy; they don't create it
•Not set-it-and-forget-it: Reassess frameworks as your product matures

When to Use This

•Choosing a prioritization framework for the first time
•Switching frameworks (current one isn't working)
•Aligning stakeholders on prioritization process
•Onboarding new PMs to team practices

When NOT to Use This

•When you already have a working framework (don't fix what isn't broken)
•For one-off decisions (frameworks are for recurring prioritization)
•As a substitute for strategic vision (frameworks can't tell you what to build)

Application

This interactive skill asks up to 4 adaptive questions, offering 3-4 enumerated options at each step.

Question 1: Product Stage

Agent asks: "What stage is your product in?"

Offer 4 enumerated options:

•Pre-product/market fit — "Searching for PMF; experimenting rapidly; unclear what customers want" (High uncertainty, need speed)
•Early PMF, scaling — "Found initial PMF; growing fast; adding features to retain/expand" (Moderate uncertainty, balancing speed + quality)
•Mature product, optimization — "Established market; incremental improvements; competing on quality/features" (Low uncertainty, data-driven decisions)
•Multiple products/platform — "Portfolio of products; cross-product dependencies; complex stakeholder needs" (Coordination complexity)

Or describe your product stage (new idea, growth mode, established, etc.).

User response: [Selection or custom]

Question 2: Team Context

Agent asks: "What's your team and stakeholder environment like?"

Offer 4 enumerated options:

•Small team, limited resources — "3-5 engineers, 1 PM, need to focus ruthlessly" (Need simple, fast framework)
•Cross-functional team, aligned — "Product, design, engineering aligned; clear goals; good collaboration" (Can use data-driven frameworks)
•Multiple stakeholders, misaligned — "Execs, sales, customers all have opinions; need transparent process" (Need consensus-building framework)
•Large org, complex dependencies — "Multiple teams, shared roadmap, cross-team dependencies" (Need coordination framework)

Or describe your team/stakeholder context.

User response: [Selection or custom]

Question 3: Decision-Making Needs

Agent asks: "What's the primary challenge you're trying to solve with prioritization?"

Offer 4 enumerated options:

•Too many ideas, unclear which to pursue — "Backlog is 100+ items; need to narrow to top 10" (Need filtering framework)
•Stakeholders disagree on priorities — "Sales wants features, execs want strategic bets, engineering wants tech debt" (Need alignment framework)
•Lack of data-driven decisions — "Prioritizing by gut feel; want metrics-based process" (Need scoring framework)
•Hard tradeoffs between strategic bets vs. quick wins — "Balancing long-term vision vs. short-term customer needs" (Need value/effort framework)

Or describe your specific challenge.

User response: [Selection or custom]

Question 4: Data Availability

Agent asks: "How much data do you have to inform prioritization?"

Offer 3 enumerated options:

•Minimal data — "New product, no usage metrics, few customers to survey" (Gut-based frameworks)
•Some data — "Basic analytics, customer feedback, but no rigorous data collection" (Lightweight scoring frameworks)
•Rich data — "Usage metrics, A/B tests, customer surveys, clear success metrics" (Data-driven frameworks)

Or describe your data situation.

User response: [Selection or custom]

Output: Recommend Prioritization Framework

After collecting responses, the agent recommends a framework:

markdown

# Prioritization Framework Recommendation

**Based on your context:**
- **Product Stage:** [From Q1]
- **Team Context:** [From Q2]
- **Decision-Making Need:** [From Q3]
- **Data Availability:** [From Q4]

---

## Recommended Framework: [Framework Name]

**Why this framework fits:**
- [Rationale 1 based on Q1-Q4]
- [Rationale 2]
- [Rationale 3]

**When to use it:**
- [Context where this framework excels]

**When NOT to use it:**
- [Limitations or contexts where it fails]

---

## How to Implement

### Step 1: [First implementation step]
- [Detailed guidance]
- [Example: "Define scoring criteria: Reach, Impact, Confidence, Effort"]

### Step 2: [Second step]
- [Detailed guidance]
- [Example: "Score each feature on 1-10 scale"]

### Step 3: [Third step]
- [Detailed guidance]
- [Example: "Calculate RICE score: (Reach × Impact × Confidence) / Effort"]

### Step 4: [Fourth step]
- [Detailed guidance]
- [Example: "Rank by score; review top 10 with stakeholders"]

---

## Example Scoring Template

[Provide a concrete example of how to use the framework]

**Example (if RICE):**

| Feature | Reach (users/month) | Impact (1-3) | Confidence (%) | Effort (person-months) | RICE Score |
|---------|---------------------|--------------|----------------|------------------------|------------|
| Feature A | 10,000 | 3 (massive) | 80% | 2 | 12,000 |
| Feature B | 5,000 | 2 (high) | 70% | 1 | 7,000 |
| Feature C | 2,000 | 1 (medium) | 50% | 0.5 | 2,000 |

**Priority:** Feature A > Feature B > Feature C

---

## Alternative Framework (Second Choice)

**If the recommended framework doesn't fit, consider:** [Alternative framework name]

**Why this might work:**
- [Rationale]

**Tradeoffs:**
- [What you gain vs. what you lose]

---

## Common Pitfalls with This Framework

1. **[Pitfall 1]** — [Description and how to avoid]
2. **[Pitfall 2]** — [Description and how to avoid]
3. **[Pitfall 3]** — [Description and how to avoid]

---

## Reassess When

- Product stage changes (e.g., PMF → scaling)
- Team grows or reorganizes
- Stakeholder dynamics shift
- Current framework feels broken (e.g., too slow, ignoring important factors)

---

**Would you like implementation templates or examples for this framework?**

Examples

Example 1: Good Framework Match (Early PMF, RICE)

Q1 Response: "Early PMF, scaling — Found initial PMF; growing fast; adding features to retain/expand"

Q2 Response: "Cross-functional team, aligned — Product, design, engineering aligned; clear goals"

Q3 Response: "Lack of data-driven decisions — Prioritizing by gut feel; want metrics-based process"

Q4 Response: "Some data — Basic analytics, customer feedback, but no rigorous data collection"

Recommended Framework: RICE (Reach, Impact, Confidence, Effort)

Why this fits:

•You have some data (analytics, customer feedback) to estimate Reach and Impact
•Cross-functional team alignment means you can agree on scoring criteria
•Transitioning from gut feel to data-driven = RICE provides structure without overwhelming complexity
•Early PMF stage = need speed, but also need to prioritize high-impact features for retention/expansion

When to use it:

•Quarterly or monthly roadmap planning
•When backlog exceeds 20-30 items
•When stakeholders debate priorities

When NOT to use it:

•For strategic, multi-quarter bets (RICE favors incremental wins)
•When you lack basic metrics (Reach requires usage data)
•For single-feature decisions (overkill)

Implementation:

Step 1: Define Scoring Criteria

•Reach: How many users will this feature affect per month/quarter?
•Impact: How much will it improve their experience? (1 = minimal, 2 = high, 3 = massive)
•Confidence: How confident are you in your Reach/Impact estimates? (50% = low data, 80% = good data, 100% = certain)
•Effort: How many person-months to build? (Include design, engineering, QA)

Step 2: Score Each Feature

•Use a spreadsheet or Airtable
•Involve PM, design, engineering in scoring (not just PM solo)
•Be honest about Confidence (don't inflate scores)

Step 3: Calculate RICE Score

•Formula: (Reach × Impact × Confidence) / Effort
•Higher score = higher priority

Step 4: Review and Adjust

•Sort by RICE score
•Review top 10-20 with stakeholders
•Adjust for strategic priorities (RICE doesn't capture everything)

Example Scoring:

Feature	Reach	Impact	Confidence	Effort	RICE Score
Email reminders	5,000	2	70%	1	7,000
Mobile app	10,000	3	60%	6	3,000
Dark mode	8,000	1	90%	0.5	14,400

Priority: Dark mode > Email reminders > Mobile app (despite mobile app having high Reach/Impact, Effort is too high)

Alternative Framework: ICE (Impact, Confidence, Ease)

Why this might work:

•Simpler than RICE (no Reach calculation)
•Faster to score (good if you need quick decisions)

Tradeoffs:

•Less data-driven (no Reach metric = can't compare features affecting different user bases)
•More subjective (Impact/Ease are gut-feel, not metrics)

Common Pitfalls:

•Overweighting Effort — Don't avoid hard problems just because they score low. Some strategic bets require high effort.
•Inflating Confidence — Be honest. 50% confidence is okay if data is scarce.
•Ignoring strategy — RICE doesn't capture strategic importance. Adjust for vision/goals.

Example 2: Bad Framework Match (Pre-PMF + RICE = Wrong Fit)

Q1 Response: "Pre-product/market fit — Searching for PMF; experimenting rapidly"

Q2 Response: "Small team, limited resources — 3 engineers, 1 PM"

Q3 Response: "Too many ideas, unclear which to pursue"

Q4 Response: "Minimal data — New product, no usage metrics"

Recommended Framework: ICE (Impact, Confidence, Ease) or Value/Effort Matrix

Why NOT RICE:

•You don't have usage data to estimate Reach
•Pre-PMF = you need speed, not rigorous scoring
•Small team = overhead of RICE scoring is too heavy

Why ICE instead:

•Lightweight, gut-check framework
•Can score 20 ideas in 30 minutes
•Good for rapid experimentation phase

Or Value/Effort Matrix:

•Visual 2x2 matrix (high value/low effort = quick wins)
•Even faster than ICE
•Good for stakeholder alignment (visual, intuitive)

Common Pitfalls

Pitfall 1: Using the Wrong Framework for Your Stage

Symptom: Pre-PMF startup using weighted scoring with 10 criteria

Consequence: Overhead kills speed. You need experiments, not rigorous scoring.

Fix: Match framework to stage. Pre-PMF = ICE or Value/Effort. Scaling = RICE. Mature = Opportunity Scoring or Kano.

Pitfall 2: Framework Whiplash

Symptom: Switching frameworks every quarter

Consequence: Team confusion, lost time, no consistency.

Fix: Stick with one framework for 6-12 months. Reassess only when stage/context changes.

Pitfall 3: Treating Scores as Gospel

Symptom: "Feature A scored 8,000, Feature B scored 7,999, so A wins"

Consequence: Ignores strategic context, judgment, and vision.

Fix: Use frameworks as input, not automation. PM judgment overrides scores when needed.

Pitfall 4: Solo PM Scoring

Symptom: PM scores features alone, presents to team

Consequence: Lack of buy-in, engineering/design don't trust scores.

Fix: Collaborative scoring sessions. PM, design, engineering score together.

Pitfall 5: No Framework at All

Symptom: "We prioritize by who shouts loudest"

Consequence: HiPPO (Highest Paid Person's Opinion) wins, not data or strategy.

Fix: Pick any framework. Even imperfect structure beats chaos.

References

Related Skills

•user-story.md — Prioritized features become user stories
•epic-hypothesis.md — Prioritized epics validated with experiments
•recommendation-canvas.md — Business outcomes inform prioritization

External Frameworks

•Intercom, RICE Prioritization (2016) — Origin of RICE framework
•Sean McBride, ICE Scoring (2012) — Lightweight prioritization
•Luke Hohmann, Innovation Games (2006) — Buy-a-Feature and other collaborative methods
•Noriaki Kano, Kano Model (1984) — Customer satisfaction framework

Dean's Work

•[If Dean has prioritization resources, link here]

Skill type: Interactive Suggested filename: prioritization-advisor.md Suggested placement: /skills/interactive/ Dependencies: None (standalone, but informs roadmap and backlog decisions)