Feature Prioritization

Frameworks for prioritizing features and opportunities.

RICE Scoring

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

RICE Table:

| Feature | Reach | Impact | Confidence | Effort | RICE Score |
|---------|-------|--------|------------|--------|------------|
| [Feature A] | 5000 | 2 | 80% | 2 | 4000 |
| [Feature B] | 1000 | 3 | 50% | 1 | 1500 |

ICE Scoring (Simpler)

ICE Score = Impact × Confidence × Ease

ICE Table:

| Feature | Impact | Confidence | Ease | ICE Score |
|---------|--------|------------|------|-----------|
| [Feature A] | 8 | 7 | 5 | 280 |
| [Feature B] | 6 | 9 | 8 | 432 |

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

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