Prioritise features with RICE scoring
RICE cuts through "loudest voice" prioritisation. Every feature gets a score from the same formula; the list sorts itself.
The formula
RICE = (Reach × Impact × Confidence) / Effort
| Factor |
What it measures |
Scale |
| Reach |
Users affected per time period (e.g. per quarter) |
Raw number (not a 1–5 scale) |
| Impact |
Effect on the metric per user who encounters the feature |
0.25 (minimal) / 0.5 / 1 / 2 / 3 (massive) |
| Confidence |
How certain are the estimates? |
0.5 (low) / 0.8 (medium) / 1.0 (high) |
| Effort |
Person-months of work |
Raw number (not a 1–5 scale) |
A higher score = build sooner. Within a sprint, also apply capacity constraints (effort sum ≤ sprint capacity).
Common calibration mistakes
- Reach is per time period — "all users" is meaningless; specify the window (per quarter / per month).
- Impact uses the fixed scale — resist the urge to invent 1–10 scales; the fixed scale forces honest comparisons.
- Confidence should hurt — if you're guessing, use 0.5. Most estimates that feel like 0.8 are actually 0.5.
- Effort in person-months — a 1-week task for 2 engineers = 0.5 person-months, not 1.
Steps
- Define the metric. RICE scores are only comparable when measuring impact on the same metric. Establish the North Star before scoring.
- List features. Collect all candidates. Don't pre-filter — let scoring do the filtering.
- Score each feature using the four factors. Be explicit about assumptions; document them next to the score.
- Apply confidence calibration. Push back on confidence scores above 0.8 unless there is user research, analytics, or a successful prior experiment behind the estimate.
- Rank. Sort descending by RICE score.
- Apply capacity constraints (if sprint planning). Sum effort from the top until capacity is consumed. Flag any item ≥ 5 person-months for decomposition.
- Sanity-check the top 5. Do the top items match intuition? If not — is the formula right, or is intuition wrong? Challenge both.
CSV input format (for batch scoring)
feature,reach,impact,confidence,effort
Dark mode,5000,1,0.8,0.5
API v2,12000,2,0.9,3
SSO integration,3000,1,0.7,2
Mobile app,20000,3,0.5,8
RICE score = (reach × impact × confidence) / effort. Sort descending.
Review checklist
- North Star metric defined — all impact scores reference the same metric.
- Reach is time-bounded — "per quarter" or "per month"; not an absolute number.
- Confidence calibrated honestly — no confidence > 0.8 without user research or prior experiment.
- Effort in consistent units — person-months across all items.
- Top 5 sense-checked — scoring result reviewed against team intuition; discrepancies investigated.
Rules
- Don't skip features before scoring — your gut's ranking is exactly what RICE is designed to override.
- Confidence 1.0 requires a completed experiment or hard data; 0.8 requires prior research; everything else is 0.5.
- RICE scores become stale in ≥ 3 months — rescore before a major planning cycle.
1---2name: rice3description: Use when prioritising a feature backlog using RICE scoring (Reach, Impact, Confidence, Effort) or making a capacity-constrained prioritisation decision. Triggers on "prioritise these features", "RICE scoring", "what should we build first", "rank the backlog", or "capacity planning for the sprint".4---56# Prioritise features with RICE scoring78RICE cuts through "loudest voice" prioritisation. Every feature gets a score from the same formula; the list sorts itself.910## The formula1112```13RICE = (Reach × Impact × Confidence) / Effort14```1516| Factor | What it measures | Scale |17|--------|-----------------|-------|18| **Reach** | Users affected per time period (e.g. per quarter) | Raw number (not a 1–5 scale) |19| **Impact** | Effect on the metric per user who encounters the feature | 0.25 (minimal) / 0.5 / 1 / 2 / 3 (massive) |20| **Confidence** | How certain are the estimates? | 0.5 (low) / 0.8 (medium) / 1.0 (high) |21| **Effort** | Person-months of work | Raw number (not a 1–5 scale) |2223A higher score = build sooner. Within a sprint, also apply capacity constraints (effort sum ≤ sprint capacity).2425## Common calibration mistakes2627- **Reach is per time period** — "all users" is meaningless; specify the window (per quarter / per month).28- **Impact uses the fixed scale** — resist the urge to invent 1–10 scales; the fixed scale forces honest comparisons.29- **Confidence should hurt** — if you're guessing, use 0.5. Most estimates that feel like 0.8 are actually 0.5.30- **Effort in person-months** — a 1-week task for 2 engineers = 0.5 person-months, not 1.3132## Steps33341. **Define the metric.** RICE scores are only comparable when measuring impact on the *same* metric. Establish the North Star before scoring.352. **List features.** Collect all candidates. Don't pre-filter — let scoring do the filtering.363. **Score each feature** using the four factors. Be explicit about assumptions; document them next to the score.374. **Apply confidence calibration.** Push back on confidence scores above 0.8 unless there is user research, analytics, or a successful prior experiment behind the estimate.385. **Rank.** Sort descending by RICE score.396. **Apply capacity constraints** (if sprint planning). Sum effort from the top until capacity is consumed. Flag any item ≥ 5 person-months for decomposition.407. **Sanity-check the top 5.** Do the top items match intuition? If not — is the formula right, or is intuition wrong? Challenge both.4142## CSV input format (for batch scoring)4344```csv45feature,reach,impact,confidence,effort46Dark mode,5000,1,0.8,0.547API v2,12000,2,0.9,348SSO integration,3000,1,0.7,249Mobile app,20000,3,0.5,850```5152RICE score = (reach × impact × confidence) / effort. Sort descending.5354## Review checklist5556- **North Star metric defined** — all impact scores reference the same metric.57- **Reach is time-bounded** — "per quarter" or "per month"; not an absolute number.58- **Confidence calibrated honestly** — no confidence > 0.8 without user research or prior experiment.59- **Effort in consistent units** — person-months across all items.60- **Top 5 sense-checked** — scoring result reviewed against team intuition; discrepancies investigated.6162## Rules6364- Don't skip features before scoring — your gut's ranking is exactly what RICE is designed to override.65- Confidence 1.0 requires a completed experiment or hard data; 0.8 requires prior research; everything else is 0.5.66- RICE scores become stale in ≥ 3 months — rescore before a major planning cycle.
tmj-90