prioritization-frameworks
Prioritization Framework Expert
Overview
A comprehensive reference to 9 prioritization frameworks with automated scoring, ranking, and guidance on which framework to use in which situation. The core principle: prioritize problems (opportunities), not features. Features are solutions to problems. If you prioritize features directly, you skip the step of understanding whether the problem is worth solving.
When to Use
- Backlog Grooming -- Too many items, need to rank them objectively.
- Quarterly Planning -- Deciding which initiatives to invest in.
- Stakeholder Alignment -- Need a structured way to resolve competing priorities.
- Feature Triage -- Quick sorting of a long list into actionable categories.
Framework Decision Tree
Use this to pick the right framework for your situation:
START: What are you prioritizing?
|
+-- Customer problems/opportunities
| -> Opportunity Score (recommended)
|
+-- Features or initiatives
| |
| +-- Need a quick sort (< 15 items)?
| | -> ICE or Impact vs Effort
| |
| +-- Need rigorous scoring (15+ items)?
| | -> RICE
| |
| +-- Need stakeholder buy-in on criteria?
| | -> Weighted Decision Matrix
| |
| +-- Need to categorize requirements?
| -> MoSCoW
|
+-- Personal PM tasks
| -> Eisenhower Matrix
|
+-- High-uncertainty initiatives
| -> Risk vs Reward
|
+-- Understanding user expectations (not prioritizing)
-> Kano Model
The 9 Frameworks
1. Opportunity Score (Recommended for Customer Problems)
Source: Dan Olsen, Lean Product Playbook
Formula: Score = Importance x (1 - Satisfaction)
- Importance (0-10): How important is this problem to the customer?
- Satisfaction (0-1): How well do existing solutions satisfy this need? (0 = not at all, 1 = perfectly)
Why it works: It identifies the biggest gaps between what customers need and what they currently have. High importance + low satisfaction = high opportunity.
Example:
| Problem | Importance | Satisfaction | Score |
|---|---|---|---|
| Finding products quickly | 9 | 0.3 | 6.3 |
| Comparing prices | 7 | 0.8 | 1.4 |
| Tracking order status | 8 | 0.6 | 3.2 |
"Finding products quickly" scores highest because it is very important and poorly solved today.
2. ICE -- Impact x Confidence x Ease
Best for: Quick prioritization of a short list (under 15 items).
Formula: Score = Impact x Confidence x Ease
All three scored 1-10:
- Impact: How much will this move the target metric?
- Confidence: How sure are we about the impact estimate?
- Ease: How easy is this to implement? (10 = trivial, 1 = massive effort)
Strengths: Fast, simple, includes uncertainty. Weakness: Subjective. Different people give different scores. Best used as a starting point for discussion, not a final answer.
3. RICE -- (Reach x Impact x Confidence) / Effort
Best for: Rigorous prioritization of a longer list.
Formula: Score = (Reach x Impact x Confidence) / Effort
- Reach: How many users/customers will this affect in a given time period? (number)
- Impact: How much will it affect each user? (3 = massive, 2 = high, 1 = medium, 0.5 = low, 0.25 = minimal)
- Confidence: How sure are we? (100% = high, 80% = medium, 50% = low)
- Effort: Person-months of work required (number)
Strengths: Reach adds a dimension that ICE misses. Effort is estimated in real units, not abstract scores. Weakness: Requires more data (reach estimates, effort sizing).
4. Eisenhower Matrix
Best for: Personal task management for PMs, not product prioritization.
Quadrants:
| Urgent | Not Urgent | |
|---|---|---|
| Important | Do First | Schedule |
| Not Important | Delegate | Eliminate |
- Q1 (Do First): Crisis, deadline-driven. Handle immediately.
- Q2 (Schedule): Strategic work, planning, prevention. This is where PMs should spend most of their time.
- Q3 (Delegate): Interruptions, some meetings, some emails. Hand off if possible.
- Q4 (Eliminate): Time-wasters, unnecessary meetings. Stop doing these.
5. Impact vs Effort (2x2 Matrix)
Best for: Quick visual triage in a group setting.
Quadrants:
| Low Effort | High Effort | |
|---|---|---|
| High Impact | Quick Wins (do first) | Major Projects (plan carefully) |
| Low Impact | Fill-ins (do if time allows) | Money Pits (avoid) |
How to use: Plot items on a whiteboard. Discuss placement. The conversation matters more than the exact position.
6. Risk vs Reward
Best for: Initiatives with significant uncertainty.
Extension of Impact vs Effort that adds an uncertainty dimension:
- Reward = Expected impact if successful
- Risk = Probability of failure x cost of failure
Quadrants:
| Low Risk | High Risk | |
|---|---|---|
| High Reward | Safe Bets (prioritize) | Bold Bets (invest selectively) |
| Low Reward | Incremental (batch) | Avoid |
7. Kano Model
Best for: Understanding customer expectations. Not for prioritization directly.
Categories:
- Must-Be (Basic): Customers expect these. Absence causes dissatisfaction. Presence does not cause delight. (Example: a login page works.)
- One-Dimensional (Performance): More is better, linearly. (Example: faster page loads = happier users.)
- Attractive (Delighters): Unexpected features that create excitement. Absence does not cause dissatisfaction. (Example: automatic dark mode based on system setting.)
- Indifferent: Customers do not care either way.
- Reverse: Some customers actively dislike this feature.
Use Kano to understand, then use another framework (RICE, ICE) to prioritize.
8. Weighted Decision Matrix
Best for: Multi-factor decisions that need stakeholder buy-in.
Process:
- Define criteria (e.g., customer impact, revenue potential, technical feasibility, strategic alignment).
- Assign weights to each criterion (must sum to 100%).
- Score each option against each criterion (1-5 or 1-10).
- Multiply scores by weights and sum.
- Rank by total weighted score.
Strengths: Transparent, auditable, gets stakeholders to agree on criteria before scoring. Weakness: Time-consuming. Best for 5-10 high-stakes decisions, not 50-item backlogs.
9. MoSCoW
Best for: Requirements categorization within a fixed scope.
Categories:
- Must Have: Non-negotiable. Without these, the release has no value.
- Should Have: Important but not critical. Painful to leave out but the release still works.
- Could Have: Desirable. Include if time and resources allow.
- Won't Have (this time): Explicitly out of scope. Acknowledged but deferred.
Rule of thumb: Must-Haves should be no more than 60% of the total effort. If everything is a Must-Have, nothing is.
Core Principle: Prioritize Problems, Not Features
Features are solutions. Problems are what matter. Two teams can build different features to solve the same problem. If you prioritize features, you lock in a solution before understanding the problem space.
Workflow:
- List customer problems (use Opportunity Score to rank them).
- Pick the top problems to solve.
- Generate multiple solution ideas for each problem.
- Prioritize solutions using RICE or ICE.
- Build the highest-scoring solutions.
This two-step approach (prioritize problems, then prioritize solutions) produces better outcomes than a single pass over a feature list.
Tools
| Tool | Purpose | Command |
|---|---|---|
prioritization_scorer.py |
Score and rank items | python scripts/prioritization_scorer.py --input items.json --framework rice |
prioritization_scorer.py |
Demo with sample data | python scripts/prioritization_scorer.py --demo --framework rice |
Supported frameworks: rice, ice, opportunity, moscow, weighted
References
references/prioritization-guide.md-- Detailed formulas, decision tree, and facilitation tipsassets/prioritization_matrix_template.md-- Scoring templates for each framework