RICE Method
The RICE method helps prioritize features by scoring them based on four factors: Reach, Impact, Confidence, and Effort. Each factor contributes to the RICE score, which determines the priority of a feature.
Reach:
- How many people will be affected by the feature in a given time period (e.g., per month).
- Example: If you estimate that 1,000 users will use a new feature each month, the reach is 1,000.
Impact:
- How much the feature will contribute to the desired outcome. It's often measured on a scale:
- 3 = massive impact
- 2 = high impact
- 1 = medium impact
- 0.5 = low impact
- 0.25 = minimal impact
- Example: If you believe the feature will significantly improve user engagement, you might rate its impact as 2 (high impact).
- How much the feature will contribute to the desired outcome. It's often measured on a scale:
Confidence:
- How confident you are in your estimates for reach and impact. This is also measured on a scale:
- 100% = high confidence
- 80% = medium confidence
- 50% = low confidence
- Example: If you are fairly sure about your estimates, you might rate your confidence as 80%.
- How confident you are in your estimates for reach and impact. This is also measured on a scale:
Effort:
- The amount of work required to complete the feature, typically measured in person-months (the work one team member can do in a month).
- Example: If a feature is estimated to take a team of two developers one month to complete, the effort would be 2 person-months.
The RICE score is calculated using the formula:
RICE Score=Reach×Impact×ConfidenceEffort\text{RICE Score} = \frac{\text{Reach} \times \text{Impact} \times \text{Confidence}}{\text{Effort}}RICE Score=EffortReach×Impact×Confidence
Referenced in:
All notes