Prioritize Backlog

Apply prioritization frameworks to: $ARGUMENTS

Your Task

Systematically prioritize the backlog items above using proven PM frameworks. Produce a ranked list with RICE scores, priority tiers, and actionable recommendations for sprint/quarter planning.

Steps

1. Gather Backlog Items

   • Parse "$ARGUMENTS" for backlog items to prioritize
   • Search Coda for roadmap and backlog documents
   • Review Dovetail for user research supporting items
   • Identify stakeholder requests

2. Score Each Item

   • Apply RICE framework (Reach, Impact, Confidence, Effort)
   • Consider strategic alignment
   • Factor in dependencies
   • Assess urgency vs. importance

3. Apply Prioritization Framework

   RICE Scoring (Primary):

   • Reach: How many users per quarter?
   • Impact: Minimal (0.25), Low (0.5), Medium (1), High (2), Massive (3)
   • Confidence: High (100%), Medium (80%), Low (50%)
   • Effort: Person-months estimate
   • Score: (Reach × Impact × Confidence) / Effort

   Kano Model (Context):

   • Categorize features as Basic/Performance/Delighter
   • Ensure all Basics are covered first
   • Balance Performance features with some Delighters

   Pareto Principle (80/20 Rule):

   • Identify the vital 20% of features driving 80% of value
   • Focus on optimizing high-impact features

   Lifecycle-Aware Prioritization:

   • Adjust strategy based on product stage (Introduction/Growth/Maturity/Decline)
   • Introduction: Focus on must-haves and validation
   • Growth: Balance quick wins with strategic bets
   • Maturity: Apply Pareto heavily, optimize vital 20%

   Reference: See product-frameworks skill for detailed frameworks:

   • prioritization-frameworks.md for RICE, MoSCoW, Kano, Pareto
   • lifecycle-guidance.md for stage-specific strategies

4. Consider Additional Factors

   • Strategic initiatives and OKRs
   • Technical debt and maintenance
   • Competitive pressure
   • Regulatory or security requirements
   • Quick wins vs. long-term investments

5. Generate Prioritized List

   • Rank by RICE score
   • Group into priority tiers (P0-P3)
   • Suggest sprint/quarter assignments
   • Identify trade-offs and dependencies

Prioritization Frameworks

RICE Framework (Primary)

Best for comparing diverse features objectively. Provides quantitative scoring for data-driven decisions.

Detailed guidance: prioritization-frameworks.md

Kano Model (Supplementary)

Categorizes features by customer satisfaction impact:

• Basic Features (Must-haves): Absence causes dissatisfaction, presence is expected
• Performance Features (Satisfiers): More is better, linear satisfaction
• Delighters (Exciters): Unexpected features that create wow moments

When to use: Ensure basic features are covered before adding delighters. In mature products, focus on performance features and sprinkle delighters.

Detailed guidance: prioritization-frameworks.md

Pareto Principle (80/20 Rule)

Identify the 20% of features that drive 80% of user value.

Application:

• Focus optimization on high-usage features
• Consider deprecating rarely-used features
• In mature products, ruthlessly focus on the vital few

Detailed guidance: prioritization-frameworks.md

Lifecycle-Aware Prioritization

Adjust prioritization based on product stage:

Introduction:

• Must-haves only, keep scope tight
• High confidence items, minimize risk
• Focus on product-market fit validation

Growth:

• Balance quick wins with strategic bets
• Invest in differentiation and scalability
• High reach features matter more

Maturity:

• Pareto principle heavily (optimize vital 20%)
• Retention over acquisition features
• Efficiency and cost reduction

Decline:

• Minimal investment (harvest) or bold bets (reinvention)
• Only critical fixes unless pivoting

Detailed guidance: lifecycle-guidance.md

MoSCoW Method (Supporting)

• Must have: Critical for launch
• Should have: Important but not critical
• Could have: Nice to have
• Won't have: Out of scope

Value vs. Effort Matrix

Plot items on 2x2 matrix:

• High value, low effort → Do first (quick wins)
• High value, high effort → Plan carefully
• Low value, low effort → Do if time permits
• Low value, high effort → Don't do

Output Format

Prioritized Backlog

Rank	Feature	RICE Score	Priority	Quarter	Rationale
1	Feature A	85	P0	Q1	High user demand, low effort
2	Feature B	72	P0	Q1	Strategic initiative
3	Feature C	45	P1	Q2	Good impact, higher effort

Priority Tiers

P0 - Critical (Do Now)

• Features essential for product strategy
• High RICE scores (>70)
• Blocking other initiatives

P1 - High Priority (Do Next)

• Important features with strong justification
• RICE scores 40-70
• Clear user value

P2 - Medium Priority (Do Later)

• Nice-to-have features
• RICE scores 20-40
• Enhancement opportunities

P3 - Low Priority (Consider)

• Nice-to-have with unclear impact
• RICE scores <20
• Defer or decline candidates

Supporting Evidence

For each high-priority item:

• User research insights (Dovetail links)
• Usage data or analytics
• Competitive context
• Strategic alignment

Recommendations

• Suggested sprint planning
• Resource allocation advice
• Risk callouts
• Trade-off decisions

Examples

Example 1: Sprint Planning

User: "We have 25 backlog items. Help me prioritize for next sprint."

[Command analyzes]:
- Scores each item with RICE
- Searches Dovetail for supporting research
- Considers team capacity
- Recommends top 5-7 items for sprint

Example 2: Quarterly Roadmap

User: "Prioritize our backlog for Q2 planning"

[Command generates]:
- Full RICE scoring for all items
- Groups into quarters
- Identifies dependencies
- Suggests quarterly themes

Best Practices

Do:

• Be transparent about scoring methodology
• Ground decisions in user research and data
• Consider opportunity cost
• Review and update priorities regularly
• Communicate trade-offs clearly
• Factor in team velocity and capacity

Don't:

• Prioritize solely by stakeholder requests
• Ignore technical debt
• Overlook quick wins
• Forget to validate assumptions
• Neglect to communicate decisions

Common Pitfalls

1. HiPPO (Highest Paid Person's Opinion)

   • Solution: Use data-driven frameworks like RICE

2. Feature Bloat

   • Solution: Ruthlessly cut low-impact items

3. Ignoring Technical Debt

   • Solution: Reserve 20% capacity for maintenance

4. Analysis Paralysis

   • Solution: Set time limits for prioritization exercises

5. Shifting Priorities

   • Solution: Define stable planning horizons (quarters)

Related Commands

• /analyze-feature-request - Deep dive on specific features
• /create-prd - Document high-priority features
• /search-user-research - Find supporting evidence

Framework References

For detailed guidance on prioritization methods:

• RICE, MoSCoW, Kano, Pareto: prioritization-frameworks.md
• Lifecycle-aware strategies: lifecycle-guidance.md
• Combining frameworks: prioritization-frameworks.md (Decision Framework section)

Checklist

Before finalizing prioritization:

• All items scored with consistent framework
• User research consulted for evidence
• Strategic alignment verified
• Dependencies identified
• Team capacity considered
• Trade-offs documented
• Stakeholders aligned
• Rationale documented for decisions