You want RICE with that?
Imagine that you are a product manager at a software company, and you have three potential features to prioritise for the next development cycle. How do you pick between them? There are many ways, but one i recently learned about is the RICE model – a prioritisation framework used by product managers, teams, and organisations to prioritise projects, features, or tasks based on their potential impact, effort, and other factors. RICE stands for Reach, Impact, Confidence, and Effort, and it provides a quantitative approach to decision-making.
- Reach: Reach refers to the number of users, customers, or stakeholders who will be affected by the project or feature over a specific period (e.g., a month or a quarter). It is essential to estimate the reach to understand how many people will benefit from the implementation.
- Impact: Impact measures the potential benefit or positive effect that the project, feature, or task will have on users, customers, or stakeholders. Impact is usually measured on a scale, such as 1 (minimal impact) to 3 (significant impact), but the scale can be adjusted to suit the organization’s needs.
- Confidence: Confidence is an estimate of how certain the team is about the reach, impact, and effort assessments. This factor is crucial because it accounts for the inherent uncertainty in making predictions. Confidence is expressed as a percentage, typically ranging from 50% to 100%.
- Effort: Effort is an estimate of the amount of time, resources, or work needed to complete the project, feature, or task. Effort can be measured in person-hours, person-days, or any other metric that reflects the resources required to complete the work.
To use the RICE model, you assign values to each of the four factors (Reach, Impact, Confidence, and Effort) for every project, feature, or task under consideration. Then, calculate the RICE score using the following formula:
RICE score = (Reach * Impact * Confidence) / Effort
Projects or features with the highest RICE scores should be prioritised over those with lower scores. This method helps ensure that the team is working on the most valuable and impactful initiatives, while also taking into account the resources and level of certainty associated with each project.
For example:
Feature A: Improve the onboarding process for new users
- Reach: 1000 users per month
- Impact: 3 (high impact, as it can significantly improve user retention)
- Confidence: 90% (high confidence in estimates and potential outcome)
- Effort: 200 person-hours
Feature B: Implement a dark mode theme
- Reach: 300 users per month
- Impact: 2 (moderate impact, as it enhances user experience)
- Confidence: 80% (fairly confident in the estimates)
- Effort: 100 person-hours
Feature C: Optimise backend performance
- Reach: 500 users per month
- Impact: 1 (low impact, as most users won’t notice the difference)
- Confidence: 70% (uncertain about the exact impact and effort)
- Effort: 150 person-hours
Now calculate the RICE scores for each feature:
Feature A RICE score = (1000 * 3 * 0.9) / 200 = 13.5 Feature B RICE score = (300 * 2 * 0.8) / 100 = 4.8 Feature C RICE score = (500 * 1 * 0.7) / 150 = 2.33
Based on the RICE scores, the priority order for these features should be:
- Feature A: Improve the onboarding process for new users (13.5)
- Feature B: Implement a dark mode theme (4.8)
- Feature C: Optimize backend performance (2.33)
Using the RICE model, you can see that Feature A should be the top priority, as it has the highest potential impact on users with a reasonable amount of effort.
Tomorrow, i’ll explain the ICE technique.