Prioritizing Work

Prioritizing Work

Overview

Applies structured prioritization frameworks to feature lists, preventing bias by requiring explicit scoring criteria and separating data from judgment.

When to Use

• User has a backlog of features or ideas
• User asks to "prioritize", "rank", "stack rank", or "decide what's next"
• User needs to make tradeoffs between competing items
• User wants to justify roadmap decisions

Core Pattern

Step 1: Gather Inputs

Collect for each item:

• Name/description
• Any existing data (usage, revenue, customer requests)

Step 2: Select Framework

Step 3: Apply Framework

RICE Scoring

Formula: RICE = (Reach × Impact × Confidence) / Effort

MoSCoW Classification

Impact/Effort Matrix

           High Impact
               │
    Quick Wins │  Major Projects
               │
  ─────────────┼─────────────
               │
    Fill-ins   │  Avoid/Deprioritize
               │
           Low Impact
     Low Effort    High Effort

Step 4: Generate Output

Write to outputs/roadmap/prioritization-YYYY-MM-DD.md:

---
generated: YYYY-MM-DD HH:MM
skill: prioritizing-work
sources:
  - [backlog source file if any]
downstream:
  - outputs/roadmap/Qx-YYYY-charters.md
---

# Prioritization: [Context]

## Framework Used
[RICE / MoSCoW / Impact-Effort] — Rationale: [why this framework]

## Scoring Inputs
| Item | Reach | Impact | Confidence | Effort | RICE Score |
|------|-------|--------|------------|--------|------------|
| [A] | [#] | [0.25-3] | [50-100%] | [#] | [calc] |

## Prioritized Backlog

### Tier 1 (Do First)
1. **[Feature A]** — Score: X / Rationale: [evidence]
2. **[Feature B]** — Score: Y / Rationale: [evidence]

### Tier 2 (Do Next)
3. **[Feature C]** — Score: Z / Rationale: [evidence]

### Not Now
- **[Feature Z]** — Rationale: [why deprioritized]

## Assumptions Made
| Assumption | Impact on Ranking | Validation Needed |
|------------|-------------------|-------------------|
| [Assumption] | [Which items affected] | [How to validate] |

## Sources Used
- [file paths]

## Claims Ledger
| Claim | Type | Source |
|-------|------|--------|
| [Reach number] | Evidence/Estimate | [Analytics data / "PM estimate"] |
| [Impact score] | Evidence/Assumption | [User research / "Team consensus"] |

Step 5: Copy to History & Update Tracker

• Copy to history/prioritizing-work/prioritization-YYYY-MM-DD.md
• Update alerts/stale-outputs.md

Quick Reference

Common Mistakes

• Gut-feel scoring: "Impact feels high" → Require explicit criteria
• Missing Confidence: Treating estimates as facts → Always include uncertainty
• Ignoring Effort: "This is important!" → High impact + high effort may still rank low
• Over-precision: RICE of 847.3 vs 845.1 → Scores are estimates, not facts
• Stakeholder bias: HiPPO wins → Use framework to surface assumptions
• No rationale: Just listing scores → Every ranking needs explanation

Verification Checklist

• All items have consistent scoring inputs
• Confidence levels explicitly stated
• Framework choice justified
• Output is a ranked list, not just scores
• Deprioritized items have rationale
• Assumptions documented
• Metadata header complete
• Copied to history, tracker updated

Evidence Tracking