RICE Score Framework Complete Guide (2024)

Prioritization is super important in product management. You can only spend your time once, so you need to make sure you're doing the right things.

In my 9 years of consulting at Accenture and Ernst & Young, I've seen a lot of companies struggle with this.

Often, product managers prioritize based on gut feeling or who shouts the loudest (usually the boss).

But that's not the best way to do business. You want a more objective way to set priorities.

There are several prioritization frameworks that can help you with this.

I'll walk you through the RICE scoring model, sharing my tips and tricks along the way.

Table of contents

1. What is the RICE Scoring Model?
2. Components of RICE
3. The RICE Prioritization Process
4. RICE in Action: Real-World Examples
5. RICE Prioritization with AI
6. Benefits and Drawbacks of RICE
7. RICE vs. ICE: Which is Better?
8. Do's and don'ts of RICE
9. Conclusion

What is the RICE Scoring Model?

This framework is great for product managers who are just starting out with prioritization, but even the pros can benefit from it.

The RICE framework was developed by Intercom's product team and has gained popularity due to its comprehensive approach.

The RICE framework helps you make a data-driven guess at priority. It's not perfect, but it helps you figure out which features are awesome and which ones you should probably skip.

RICE stands for four factors:

• Reach – How many people will this impact in a given time period?

• Impact – How much does this help us reach our goals?

• Confidence – How sure are we that this will actually work?

• Effort – How much time will it take to implement this?

The basic formula for calculating the RICE score is:

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

It's like the classic impact/effort analysis, but with reach and confidence thrown in for good measure.

Let's break down each component and then we'll walk through the process of using RICE for prioritization.

Components of RICE

Reach

Reach measures how many people your feature or project will affect within a specific time frame (usually a quarter). This could be the number of customers, users, or transactions.

Here's a suggested scale for Reach:

Examples

• Feature A: Add dark mode (Reach score: 8) - This could affect 80,000 users per quarter.

• Feature B: Implement AI-powered recommendations (Reach score: 10) - This could impact all 150,000 active users.

Impact

Impact measures how much a feature contributes to your goals. Before scoring impact, ensure your goals are clearly defined. A great tool for this is the Product Vision Board, which helps you articulate your vision, target group, needs, product, and business goals.

When scoring impact, use a 1-10 scale. Here's an example scale:

Examples

• Feature A: Add dark mode (Impact score: 6) - This will improve user experience for some users, but it's not transformative.

• Feature B: Implement AI-powered recommendations (Impact score: 9) - This could significantly increase user engagement and retention.

Confidence

Confidence helps distinguish between data-backed ideas and mere opinions. It's crucial to involve your team when determining confidence scores, as different perspectives can reveal potential concerns.

Here's a scale you can use for Confidence:

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(Source: Itamar Gilad)

Effort

Effort is all about how hard it is to implement something. Think of this as the traditional effort factor. How many person-months will it take to build?

Here's an example scale for Effort:

Examples

• Feature E: Fix a minor UI bug (Effort score: 1) - This is a quick fix that can be done in less than a month.

• Feature F: Integrate a new payment gateway (Effort score: 3) - This requires significant backend work and testing, estimated at 2-3 months.

The RICE Prioritization Process

Now that we understand the components, let's walk through the process of using RICE for prioritization.

1. List features, enablers, regulatory items

First things first, make a list of all the tasks and features you're thinking about.

Try to keep things MECE (Mutually Exclusive, Collectively Exhaustive). This means your items should not overlap (mutually exclusive) and should cover all possibilities (collectively exhaustive).

For example, "SSO login" and "Tagging" are on the same level and don't overlap. But "Change button color" and "Build a whole new app" are definitely not on the same level.

Take your time to make a good list. It's a pain when you're halfway through prioritizing and someone throws in a new idea. I usually ask customers, partners, and coworkers for their input using surveys or a feedback tool.

Let's add the list in the Score-based Prioritization module:

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2. Score each component

Now, go through your list and score each item on Reach, Impact, Confidence, and Effort using the scales we discussed earlier.

In our tool, we make decisions based on how many votes a feature gets. We also look at conversion, which is likes divided by views. Even though the SSO login feature has fewer votes, it has the highest conversion rate, showing it's important.

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3. Calculate scores

Now it's time to do some math! The RICE score calculation is:

Priority = (Reach x Impact x Confidence) / Effort

After entering all the data, the tool automatically calculates the RICE score. With the RICE scores calculated, we can reorder the list to view features from highest to lowest priority. This helps in identifying which features should be addressed first.

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4. Review with team and stakeholders

After calculating the scores, it's important to review the results with your team and key stakeholders. This step helps catch any oversights and ensures everyone is aligned on the priorities.

5. Finalize and make roadmap

Finally, with all the data entered, we can use this input to determine the roadmap.

We review each item on the list. In ProductLift, we can change the status of the items we have reviewed. This step immediately updates users that voted for the feature request.

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As we update the statuses of the items, they are automatically added to our roadmap. This ensures that our roadmap is always up-to-date with the latest priorities and statuses.

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RICE in Action: Real-World Examples

Many successful companies have used RICE to drive their product development. Here are a couple of examples:

routespring

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Routespring, a fast-growing startup optimizing business travel management for centralized payments, uses a modified version of the RICE model called SU-RICE (Source-User RICE) for prioritizing their product features. By focusing on ideas that score highest in their adapted framework, Routespring has been able to develop features that streamline travel booking processes and improve user experience for their corporate clients.

Intercom_logo

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Intercom, the messaging software company that originally developed the RICE framework, used it to improve their internal decision-making processes for product development. By implementing RICE, Intercom was able to objectively determine which features to build first, based on their potential value and the effort required. This approach helped Intercom grow rapidly and become a leader in the customer communication platform space.

RICE Prioritization with AI

While the RICE framework is a powerful tool, it can be time-consuming to implement manually, especially for a large number of features. This is where AI-powered prioritization can come in handy.

The AI prioritization feature helps us decide which features to focus on in 30 seconds.

We start by setting up our product vision and adding features we want to consider. As users vote on their favorites, the AI analyzes this data and our vision to find the top 5 features.

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Benefits and Drawbacks of RICE

Benefits:

1. It helps you avoid making decisions based on gut feeling or emotions.

2. It focuses your time and resources on the most impactful tasks or features.

3. It aligns your work with your business goals.

4. It improves communication and collaboration in your team by providing a standard way to evaluate ideas.

5. It includes a reach factor, which helps prioritize features that affect more users.

Drawbacks:

1. The factors can be subjective. Who decides what's a 1 or a 2?

2. It can be more time-consuming to implement than simpler frameworks.

3. Scores can change over time. You'll need to regularly review and update your factors.

4. It may not be suitable for all types of projects or features.

RICE vs. ICE: Which is Better?

ICE is another popular prioritization framework that stands for Impact, Confidence, and Ease. The main difference is the absence of the Reach factor in ICE.

So which is better? It depends on your needs:

• The ICE method is simpler and faster to use, making it great for quick decisions or when you don't have detailed user data.

• RICE is more comprehensive and can be more accurate, especially for consumer products where reach is a critical factor.

In general, if you're just starting out or need to make quick decisions, ICE prioritization might be a good choice. As your product matures and you have more data about your users, RICE can provide more nuanced prioritization.

Do's and don'ts of RICE

The RICE prioritization framework can be a powerful tool for product managers, but it's important to use it properly. Here are some do's and don'ts to keep in mind when applying RICE:

Do:

• Start by clearly defining your objectives and goals.

• Involve the right stakeholders in the prioritization process.

• Use the RICE score to prioritize features or ideas, but also consider other factors such as resources, technical feasibility, and market demand.

• Revisit and update your RICE priority regularly as new information becomes available or priorities change.

• Communicate your prioritization decisions transparently and explain the rationale behind them.

Don't:

• Rely solely on the RICE methodology to make decisions. Use it as one of several inputs in your prioritization process.

• Ignore feedback from users or other stakeholders just because a feature or idea scored low on the RICE scale.

• Rush through the prioritization process without giving it enough time and attention.

• Base your RICE scores solely on your own opinions or assumptions. Use data and insights from multiple sources to inform your scores.

• Use RICE as a one-size-fits-all solution. Different projects or products may require different prioritization frameworks or approaches.

Conclusion

Prioritizing features is tough and takes time and discipline. The RICE scoring model helps you make a data-driven estimate of priority. Now you have the tools to do this for your product.

Remember to revisit your RICE scores regularly, as your experience, goals, and confidence will change over time.

Finally, share your priority outcomes with your customers and stakeholders using your product roadmap or kanban board. This keeps everyone aligned and excited about what's coming next!