name: priority-matrix
description: "Rank opportunities and work threads across multiple prioritization dimensions. Produces actionable priority matrices with calibrated scores, bias-checked rationale, and stakeholder-aligned rankings. Creates the prioritized backlog that feeds into proposal building."
phase: IMPLEMENT
category: specialized
version: "2.0.0"
depends_on: ["context-cultivation"]
tags: [planning, prioritization, analysis, decision-making, frameworks]

Priority Matrix

Rank opportunities and work threads across multiple prioritization dimensions.

When to Use

• Multiple competing opportunities -- Several options identified, need systematic ranking
• Resource allocation decisions -- Limited capacity, must choose what to pursue first
• Stakeholder alignment -- Different stakeholders advocate for different priorities
• Post-cultivation synthesis -- Context cultivation surfaced many threads, need to converge
• Strategic planning -- Quarterly or initiative-level prioritization across a portfolio
• When you say: "prioritize these", "what should we focus on", "rank the options", "which one first?"

Reference Requirements

MUST read before applying this skill:

Read if applicable:

Verification: Ensure at least one scored matrix is produced with documented rationale for every score.

Required Deliverables

Core Concept

Priority Matrix answers: "What should we do first, and why?"

Prioritization decisions are:
- Systematic -- Use structured frameworks, not gut feeling
- Transparent -- Every score has documented rationale
- Calibrated -- Scores are consistent across options and dimensions
- Stakeholder-aligned -- Methodology agreed upon before scoring begins
- Actionable -- Results in a clear, ordered backlog with next steps

Prioritization is NOT:
- Voting or popularity contests (that is opinion gathering)
- One-time decisions set in stone (priorities evolve; re-score periodically)
- A substitute for strategy (strategy defines goals; prioritization orders the path)
- Detailed project planning (that is spec and scaffold)

The Priority Matrix Process

+---------------------------------------------------------------+
|                    PRIORITY MATRIX PROCESS                     |
|                                                                |
|  1. OPTION ENUMERATION                                         |
|     +-> Collect and define all candidate work threads          |
|                                                                |
|  2. FRAMEWORK SELECTION                                        |
|     +-> Choose the right prioritization framework              |
|                                                                |
|  3. DIMENSION DEFINITION                                       |
|     +-> Define and weight scoring dimensions                   |
|                                                                |
|  4. CALIBRATION                                                |
|     +-> Establish scoring anchors and reference points         |
|                                                                |
|  5. SCORING                                                    |
|     +-> Score each option on each dimension with rationale     |
|                                                                |
|  6. AGGREGATION                                                |
|     +-> Calculate weighted scores and produce rankings         |
|                                                                |
|  7. BIAS CHECK                                                 |
|     +-> Review for cognitive biases and political distortion   |
|                                                                |
|  8. VALIDATION                                                 |
|     +-> Sanity check results against intuition and strategy    |
+---------------------------------------------------------------+

Step 1: Option Enumeration

Before scoring anything, build the complete list of candidates.

Option Definition Template

For each candidate, capture enough context to score it:

### Option: [Name]

**Description:** [One-paragraph summary of what this work thread entails]

**Origin:** [Where this option came from -- cultivation theme, stakeholder request, gap analysis]

**Scope estimate:** [T-shirt size: XS / S / M / L / XL]

**Dependencies:** [Other options or external factors this depends on]

**Stakeholder champion:** [Who is advocating for this option, if anyone]

Enumeration Checklist

- [ ] All context cultivation themes represented
- [ ] All stakeholder requests captured
- [ ] All gap analysis items included
- [ ] Options are at comparable granularity
- [ ] Duplicates and overlaps merged
- [ ] Each option has a clear one-line description
- [ ] Total option count is manageable (3-15 is ideal)

If you have more than 15 options: Group them into categories first, prioritize categories, then prioritize within the top 2-3 categories. Avoid scoring 20+ items in a single matrix -- cognitive load degrades scoring quality.

Step 2: Framework Selection

Choose the prioritization framework that fits your context. No single framework is universally best.

Framework Comparison

Framework Selection Guide

Use Weighted Scoring when:
- You need full customization of dimensions
- Stakeholders need to see transparent methodology
- Options span diverse categories (technical, business, operational)

Use RICE when:
- Prioritizing product features or growth initiatives
- You have data on reach (users affected) and can estimate confidence
- The team is familiar with product management practices

Use ICE when:
- Speed matters more than precision
- Early-stage exploration with high uncertainty
- You need a quick first pass before deeper analysis

Use MoSCoW when:
- Working with a fixed deadline or scope boundary
- Stakeholders think in terms of "must have" vs "nice to have"
- Negotiating scope for an MVP or release

Use Eisenhower when:
- Triaging a mix of urgent and important work
- Team is overwhelmed and needs to cut non-essential work
- Distinguishing between reactive and proactive priorities

Use Cost of Delay when:
- Options have different time sensitivities
- Delay has measurable economic impact
- You want to optimize sequencing, not just ranking

Framework Decision Record

### Framework Choice: [Name]

**Selected:** [Framework name]
**Reason:** [Why this framework fits]
**Alternatives considered:** [What else was considered and why rejected]
**Adaptations:** [Any modifications to the standard framework]

Step 3: Dimension Definition

Define the scoring dimensions and their weights. Dimensions should be:

• Independent -- Avoid double-counting the same factor
• Measurable -- Each dimension must be scorable (even if subjective)
• Relevant -- Every dimension should matter for this specific decision
• Balanced -- No single dimension should dominate unless intentional

Default Weighted Scoring Dimensions

RICE Dimensions

RICE score = (Reach x Impact x Confidence) / Effort

ICE Dimensions

ICE score = Impact x Confidence x Ease

Custom Dimension Template

### Dimension: [Name]

**Weight:** [Percentage]
**Description:** [What this dimension measures]

**Scoring guide:**
- 1-2: [Low anchor description]
- 3-4: [Below average description]
- 5-6: [Average description]
- 7-8: [Above average description]
- 9-10: [High anchor description]

**Example scores:**
- [Concrete example] = [Score] because [rationale]
- [Concrete example] = [Score] because [rationale]

Weight Allocation Checklist

- [ ] Weights sum to 100%
- [ ] No single dimension exceeds 40% (unless deliberately chosen)
- [ ] Stakeholders agree on dimension definitions
- [ ] Stakeholders agree on weight distribution
- [ ] Score guides are documented before scoring begins

Step 4: Calibration

Calibration ensures scores are consistent and meaningful. This is the most overlooked step and the most important for producing trustworthy results.

Calibration Techniques

Anchor Setting Process

1. Choose 2-3 well-understood options as anchors
2. Score anchors first on all dimensions
3. Use anchors as reference points when scoring remaining options
4. If a new score feels wrong relative to an anchor, adjust

### Calibration Anchors

| Anchor Option | Dimension | Score | Rationale |
|---------------|-----------|-------|-----------|
| [Well-known option A] | Impact | 8 | [Why this is an 8] |
| [Well-known option B] | Impact | 3 | [Why this is a 3] |
| [Well-known option A] | Effort | 5 | [Why this is a 5] |
| [Well-known option B] | Effort | 9 | [Why this is a 9] |

Score Distribution Health Check

After scoring, verify the distribution looks reasonable:

- [ ] Scores use at least 60% of the 1-10 range (not all clustered at 6-8)
- [ ] At least one option scores below 5 on some dimension
- [ ] At least one option scores above 8 on some dimension
- [ ] No dimension has all identical scores (that dimension is useless)
- [ ] Anchor options still feel correctly placed relative to others

Step 5: Scoring

Score every option on every dimension. Document rationale for every score.

Scoring Template

## Scores: [Option Name]

| Dimension | Score | Rationale |
|-----------|-------|-----------|
| Impact | [1-10] | [Why this score -- specific evidence or reasoning] |
| Effort | [1-10] | [Why this score -- reference comparable past work] |
| Urgency | [1-10] | [Why this score -- what happens if we delay] |
| Alignment | [1-10] | [Why this score -- which strategic goals does it serve] |

Scoring Discipline Rules

1. Score one dimension at a time across all options -- Not one option at a time. This improves consistency.
2. Write rationale before moving to the next score -- Forces deliberate thinking.
3. Reference anchors frequently -- "Is this more or less impactful than Anchor A?"
4. Flag low-confidence scores -- Mark scores where you are guessing with a (?) suffix.
5. Separate fact from opinion -- Note when a score is data-driven vs. judgment-based.

Handling Uncertainty

Step 6: Aggregation

Calculate weighted scores and produce the final ranking.

Weighted Score Calculation

For each option: Final Score = SUM(dimension_score x dimension_weight)

Full Matrix Template

# Priority Matrix

**Framework:** [Framework name]
**Date:** [Date scored]
**Scored by:** [Who participated]

## Dimension Weights

| Dimension | Weight |
|-----------|--------|
| Impact | 30% |
| Effort | 25% |
| Urgency | 25% |
| Alignment | 20% |

## Scoring Matrix

| # | Option | Impact | Effort | Urgency | Alignment | Weighted Score | Rank |
|---|--------|--------|--------|---------|-----------|----------------|------|
| 1 | Option Alpha | 9 | 7 | 8 | 9 | **8.25** | 1 |
| 2 | Option Beta | 8 | 6 | 9 | 7 | **7.65** | 2 |
| 3 | Option Gamma | 7 | 9 | 5 | 8 | **7.10** | 3 |
| 4 | Option Delta | 6 | 8 | 4 | 6 | **5.90** | 4 |

## Score Breakdown

[Include rationale tables from Step 5 for each option]

RICE Score Calculation

| Option | Reach | Impact | Confidence | Effort | RICE Score | Rank |
|--------|-------|--------|------------|--------|------------|------|
| Alpha | 5000 | 2 | 80% | 3 | 2667 | 1 |
| Beta | 2000 | 3 | 100% | 2 | 3000 | -- |

Note: RICE produces absolute scores, not 1-10 normalized scores. Rankings compare relative positions.

Tie-Breaking Rules

When two options have the same or very close scores (within 5%):

1. Impact wins -- Higher impact option ranks higher
2. Effort wins -- If impact is equal, lower effort option ranks higher
3. Confidence wins -- If still tied, higher confidence option ranks higher
4. Stakeholder tiebreak -- Escalate to the decision maker

Step 7: Bias Check

After scoring and ranking, explicitly check for common cognitive biases that distort prioritization.

Bias Checklist

Bias Mitigation Techniques

- [ ] Score independently before group discussion
- [ ] Randomize the order options are presented
- [ ] Assign a "devil's advocate" for top-ranked options
- [ ] Compare effort estimates to actual past effort on similar work
- [ ] Ask: "Would we still rank this #1 if [champion] were not advocating?"
- [ ] Ask: "What would need to be true for the bottom option to be #1?"
- [ ] Re-score any flagged low-confidence scores after bias review

See references/bias-mitigation.md

Step 8: Validation

The matrix produces a ranking. Validation ensures the ranking makes sense.

Validation Questions

- [ ] Does the #1 option feel right? If not, what is the matrix missing?
- [ ] Would a reasonable stakeholder object to the top 3? Why?
- [ ] Do the bottom 3 genuinely deserve to be deprioritized?
- [ ] Does the ranking align with stated strategy and goals?
- [ ] Are there dependencies that make the ranking impractical?
- [ ] Is there an obvious "do first" option the matrix ranked low?
- [ ] Has the methodology been explained and accepted by stakeholders?

The Gut Check Test

If the matrix ranking contradicts strong intuition, do not simply override it. Instead:

1. Identify the gap -- Which dimension is causing the surprising result?
2. Check scoring -- Was that dimension scored correctly for the surprising option?
3. Check weighting -- Should that dimension's weight be adjusted?
4. Resolve explicitly -- Either fix the model or document why intuition is wrong

### Gut Check: [Surprising Result]

**Expected rank:** [What you expected]
**Actual rank:** [What the matrix produced]
**Root cause:** [Which dimension/weight caused the surprise]
**Resolution:** [Adjusted score/weight OR accepted the matrix result because...]

Dependency Validation

Even if Option A outranks Option B, if A depends on B, then B must come first. After ranking:

- [ ] Check for dependency cycles (A needs B, B needs A)
- [ ] Adjust execution order for hard dependencies
- [ ] Note where parallel execution is possible
- [ ] Document any re-ordering and rationale

Output Formats

Quick Priority List (3-5 Options)

# Priorities: [Context]

**Date:** [Date]
**Framework:** ICE (quick scoring)

## Priority Stack

1. **[Option Name]** (Score: 8.5)
   - Why first: [One-line rationale]
   - Next action: [Concrete next step]

2. **[Option Name]** (Score: 7.2)
   - Why second: [One-line rationale]
   - Next action: [Concrete next step]

3. **[Option Name]** (Score: 6.8)
   - Why third: [One-line rationale]
   - Next action: [Concrete next step]

## Deprioritized

- **[Option Name]** (Score: 4.1) -- [Why not now]
- **[Option Name]** (Score: 3.5) -- [Why not now]

## Methodology

[Brief description of framework and dimensions used]

Full Priority Matrix (6+ Options)

# Priority Matrix: [Context]

**Date:** [Date]
**Framework:** [Framework name]
**Scored by:** [Participants]
**Confidence:** [Overall confidence level]

## Executive Summary

[Top 3 priorities in one paragraph. Key trade-offs and rationale.]

## Priority Stack

### Tier 1: Do Now
| Rank | Option | Score | Key Rationale |
|------|--------|-------|---------------|
| 1 | [Name] | [Score] | [Why] |
| 2 | [Name] | [Score] | [Why] |

### Tier 2: Do Next
| Rank | Option | Score | Key Rationale |
|------|--------|-------|---------------|
| 3 | [Name] | [Score] | [Why] |
| 4 | [Name] | [Score] | [Why] |

### Tier 3: Do Later
| Rank | Option | Score | Key Rationale |
|------|--------|-------|---------------|
| 5 | [Name] | [Score] | [Why] |
| 6 | [Name] | [Score] | [Why] |

### Not Now
| Option | Score | Why Deprioritized |
|--------|-------|-------------------|
| [Name] | [Score] | [Reason] |

## Full Scoring Matrix

[Include the complete matrix table from Step 6]

## Dimension Definitions and Weights

[Include the dimension table from Step 3]

## Calibration Notes

[Include anchors and calibration decisions from Step 4]

## Score Rationale

[Include per-option rationale tables from Step 5]

## Bias Review

[Include completed bias checklist from Step 7]

## Validation Notes

[Include completed validation checklist from Step 8]

## Execution Dependencies

[Dependency map and any re-ordering from validation]

## Next Steps

1. [Concrete action for priority #1]
2. [Concrete action for priority #2]
3. [When to re-score -- trigger conditions]

Common Patterns

The Portfolio Prioritization

Score strategic initiatives across business dimensions: revenue impact, customer satisfaction, operational efficiency, competitive positioning.

Use when: Annual or quarterly planning, allocating a fixed budget across initiatives.

The Feature Backlog Triage

Apply RICE scoring to a product feature backlog. Emphasize reach and confidence to avoid building low-impact, high-uncertainty features.

Use when: Sprint planning, product roadmap creation, feature grooming sessions.

The Technical Debt Matrix

Score technical debt items on: blast radius (what breaks if ignored), fix effort, frequency of pain, and dependency blocking. Weight blast radius and dependency blocking heavily.

Use when: Deciding which tech debt to address during a maintenance sprint or platform stabilization.

The Opportunity Assessment

Combine market analysis with feasibility scoring. Dimensions include: market size, competitive intensity, capability fit, time to value.

Use when: Evaluating new business opportunities, partnership proposals, or market entry decisions.

Relationship to Other Skills

Key Principles

Methodology before scoring. Agree on framework, dimensions, and weights before anyone scores a single option. Changing methodology mid-scoring invalidates prior scores.

Rationale is the product. The ranked list is useful; the documented rationale is invaluable. Future prioritization decisions build on today's reasoning, not just today's numbers.

Calibrate relentlessly. Uncalibrated scores are meaningless. Two people giving "7 out of 10" may mean completely different things. Anchors and examples make scores comparable.

Separate scoring from advocacy. The person who proposed an option should not be the only person scoring it. Separation reduces champion bias and increases trust in results.

Prioritization is perishable. A priority matrix has a shelf life. Re-score when new information emerges, when market conditions change, or at regular intervals (monthly or quarterly).

Explicit is better than implicit. A mediocre framework applied transparently beats a brilliant decision made in someone's head. The matrix makes reasoning visible, challengeable, and improvable.

References

• references/prioritization-frameworks.md: Detailed framework implementations (RICE, MoSCoW, ICE, Eisenhower, Cost of Delay)
• references/scoring-calibration.md: Calibration techniques, anchor setting, score normalization
• references/bias-mitigation.md: Cognitive biases in prioritization and countermeasures
• references/stakeholder-alignment.md: Techniques for building consensus on methodology and results
• references/effort-estimation.md: Effort estimation approaches for the effort/ease dimension