Feature Prioritization

Frameworks for prioritizing features and opportunities.

RICE Scoring

RICE Score = (Reach × Impact × Confidence) / Effort

Factor Definition Scale

Reach Users affected per quarter Actual number

Impact Effect on users 3=Massive, 2=High, 1=Medium, 0.5=Low, 0.25=Minimal

Confidence How sure are you? 100%=High, 80%=Medium, 50%=Low

Effort Person-months to ship Actual estimate

RICE Table:

ICE Scoring (Simpler)

ICE Score = Impact × Confidence × Ease

Factor Scale

Impact 1-10 (potential value)

Confidence 1-10 (certainty of impact)

Ease 1-10 (implementation simplicity)

ICE Table:

Opportunity Solution Tree

Structure:

Outcome (measurable business goal) ├── Opportunity 1 (unmet customer need) │ ├── Solution 1a │ │ └── Experiment: [test] │ └── Solution 1b │ └── Experiment: [test] ├── Opportunity 2 (another need) │ └── Solution 2a │ └── Experiment: [test] └── Opportunity 3 └── ...

OST Template:

Outcome

Goal: [Measurable objective] Current: [Baseline metric] Target: [Target metric] Timeline: [By when]

Opportunity Map

Opportunity 1: [Customer need/pain point]

Evidence: [Interview quotes, data] Size: [How many users affected]

Solutions considered:

1. [Solution A]

   • Effort: [S/M/L]
   • Experiment: [How to test cheaply]
   • Success metric: [What to measure]

2. [Solution B]

   • Effort: [S/M/L]
   • Experiment: [How to test cheaply]
   • Success metric: [What to measure]

Selected: [Which and why]

When to Use Each

Framework Best For Limitations

RICE Large teams, many features Requires reach data

ICE Quick decisions, small teams More subjective

OST Strategy alignment Requires outcome clarity

Prioritization Anti-Patterns

• HiPPO (Highest Paid Person's Opinion) → Use data

• Squeaky wheel (loudest customer wins) → Weight by segment size

• Pet projects (internal favorites) → Require evidence

• Sunk cost (we started, must finish) → Re-evaluate regularly