RICE Prioritisation Skill
Purpose
Apply consistent, criteria-based RICE scoring to a list of features or initiatives to produce an objective prioritisation ranking.
RICE Definitions (adapt to your context)
- Reach: Number of users affected per quarter (use actual DAU/MAU data where available)
- Impact: Effect on your primary metric — use scale: 3=massive, 2=high, 1=medium, 0.5=low, 0.25=minimal
- Confidence: How certain are we about R and I estimates? 100%=high, 80%=medium, 50%=low
- Effort: Person-months required across all functions
RICE Formula
RICE Score = (Reach × Impact × Confidence) / Effort
Process
- For each initiative provided, gather or estimate R, I, C, E values
- Flag where estimates are weak and note what data would improve them
- Calculate RICE score for each
- Rank highest to lowest
- Flag any "quick wins" (high RICE score, low effort) and "moonshots" (high impact, high effort)
- Note dependencies between items that affect sequencing
Output Format
RICE Prioritisation: [Backlog/Quarter]
| Initiative | Reach | Impact | Confidence | Effort | RICE Score | Notes |
|---|---|---|---|---|---|---|
| [name] | [n] | [score] | [%] | [months] | [score] | [flags] |
Recommended Sequence
[Top 5 initiatives with rationale]
Data Gaps to Address
[What information would most improve scoring accuracy]