Using a robust prioritization method such as the RICE framework ensures you tackle the outsized opportunities first.
The RICE framework is a tool that helps product managers make informed decisions about the value and sequence of projects.
It also helps PMs get alignment on prioritization with stakeholders.
RICE has major advantages over other backlog prioritization techniques you might use. The outcome is
- Numeric: it generates a calculated cost / benefit score
- A stack ranked list based on a transparent calculation
In this article we’re going walk you through the RICE framework, including using the RICE framework in product management to organize your backlog, and the advantages and disadvantages of RICE.
We’ll cover the RICE framework’s calculation components, real-world applications, and potential pitfalls.
Free RICE Framework Template
Get the free Hustle Badger RICE Framework template (pre-calculated) here
Get the free Hustle Badger RICE Framework flashcards here
RICE framework in product management prioritization
The RICE framework has become a well known, and popular methodology for product managers to organize their product backlogs and prioritize opportunity lists. It’s commonly used.
Like all frameworks however, it works best when you understand the downsides of the framework, and adapt it to your context. In the below article we’ll take you through the standard framework, but also advocate for some adaptations to make the RICE framework for product management tasks even more effective.
Invention of the RICE framework
The RICE framework was developed by Sean McBride while working as a product manager at Intercom.
He introduced it after observing flaws in the decision making around prioritization in the company:
- Effort was not a factor in whether projects moved forwards
- Confidence in ability and value of executing was also not a factor
- Ideas favored pet projects rather than impact on goals
The RICE framework was an attempt to help the business make informed decisions about where to invest time and effort for maximum value..
Introduction to the RICE framework
RICE is a calculation methodology that enables product managers to prioritize tasks based on four key factors: Reach, Impact, Confidence, and Effort.
Get the free Hustle Badger RICE Framework flashcards here
In order to calculate RICE you apply a score to each input (Reach, Impact, Confidence, and Effort).
Then you multiply Reach, Impact and Confidence, and divide by Effort to get the overall RICE prioritization score.
This provides a quantitative measure of each task’s priority level, ranked by RICE score.
Put all your opportunities into a spreadsheet, calculate this for every input, and sort downwards to get to a prioritized list of opportunities.
Adapting RICE to your needs
RICE is a flexible framework that you can adapt to your needs. At Hustle Badger we have adapted our RICE calculation methodology from Sean McBride’s original because when we were using it, we saw ways to improve it.
We encourage you to do the same. The important thing is to come up with something which allows you to get good results for your business and is intuitively understood within your company.
That might mean changing an input estimation process. If it works for you, do it. Prioritization is as much about stakeholder management as it is about finding gains.
The below is the Hustle Badger RICE framework calculation methodology.
RICE framework: Escalating effort and time investment
It’s useful to understand each component as a cascade of validating future value and determining whether to invest further in scoping the project:
- Is it useful to calculate Impact if it doesn’t Reach many users?
- Is it useful to invest in discovery and calculate confidence score, if the Impact isn’t high?
- Is it useful to invest engineering time in sizing the project if we don’t have high confidence?
Reach in RICE
Reach refers to the potential audience or user base that will be impacted by the task.
It’s a critical input to the RICE framework, as it’s usually the number you have the most confidence in. You have data for your user base, but the other inputs are much less certain.
You can estimate Reach by calculating the number of users affected over a specified time period.
Example: if you’re launching a new feature on an area of the site that routinely sees 3,600 visitors per quarter, the number of users who will be impacted by this feature is 3,600.
Alternatively, which we prefer, you can calculate it as a percentage of total users affected.
We think this is better because it makes it easier to avoid errors based on taking different baselines.
Example:. Opportunity 1 calculates Reach as all new users for a year, compared to Opportunity 2 which calculates Reach as all new users that week.
RICE framework example of Reach: Onboarding affects 100% of new users, or 50% of all users. Checkout affects 100% of purchasing users, or 3% of all users. Commenting affects 30% of all users (new or existing).
As this number is the most likely to be correct, it’s good to evade simple errors based on time periods.
RICE framework example of Reach: if you’re making changes to a prequalification form which filters out users sequentially, if your site has:
- 20,000 visitors a week
- 1000 people start the form every week
- 30% reach the step you plan to change
Then the reach is 1000 form users / 20000 visitors * 30% reaching that step = 1.5% of users are affected, and thus 1.5% of all users is the Reach.
If you are working in product teams where squads are organized by domain (i.e. you have a B2B acquisition squad) and that squad only works on a subset of users, it would be better to cut out the visitors that that don’t hit their domain, and calculate Reach as 30% of their domain visitors.
RICE framework example of Reach: if you’re migrating users from an old product that you want to deprecate, to the dominant product for the majority of customers, impact will not be ongoing. Let’s say 542 people are customers of the old product, compared to 12830 of the new product. 542 + 12,830 = 13,372 is your total customer base. 542 / 13,372 = 4%. 4% is the reach score.
Impact in RICE
Impact quantifies the potential impact of any action or feature on affected users.
Different goals have different baselines and different units of measurement, so we recommend using a simple impact model that outputs a revenue number to understand the likely level of impact.
You ideally have some historic data you can reference from rolling out past interventions or features. Alternatively you can use benchmarks or estimates.
But ultimately you don’t know whether a new feature will drive a 3 or a 5% or a 0% or a -2% increase in conversion before you ship it.
It’s important not to get hung up on too much detail and waste time hunting an impossible degree of accuracy. You’re not trying to create a detailed financial model, you’re trying to sort opportunities by bang for buck.
However you should have a good feeling of whether it will cause a 1%, 10%, or 100% change in the metrics you’re trying to move. Use the following scale:
- 1% change in metrics – small impact
- 10% change in metrics – medium impact
- 100% change in metrics – massive impact
It’s generally obvious what is the most important thing to do, and it will have an order of magnitude bigger impact than small, or medium tasks.
It’s key to differentiate those impacts properly, and avoid using a sliding scale which might falsely conflate the values.
RICE framework example of Impact: If you scale “huge” changes as 80% impact uplift and “medium” changes as 30% impact uplift, then it’s easy to convince yourself that you should do a bunch of medium things in the time you’ve got.
Almost always you want to commit to the big thing and get it done. If there is a massive improvement you can make, then go for it. nothing else will matter.
If you’re not good at estimating scale of impact there are things you can do:
- Practice
- Talk to your users
- Score yourself retrospectively on how you do
- Seek out historic impact numbers or benchmarks
Knowing therefore that your goal is to create a simple model based on orders of magnitude; you should then round everything to the nearest order of magnitude and create buckets.
‘We think that implementing Google 1 click sign up will have a medium impact – therefore we estimate user conversion to account creation will have a 10% uplift.’
It might be that you actually think it will have a 15% uplift. But you’re not using a percentage scale, so align it to the medium impact bucket (10% uplift).
Get the free Hustle Badger RICE Framework template: Simple Impact Model here
RICE framework example of Impact: We’re implementing 1 click Google sign up for all users. We think this will have a medium (10%) impact. We’re scoring impact as 10%, and calculating incremental revenue as a result as $740,776. The Impact score is $740,776.
RICE framework example of Impact: We’re introducing prices set in local currencies according to purchasing power in the market. We expect this to have a massive (100%) impact on all users who don’t currently purchase in dollars, and who can’t afford $25 as a fee. The impact score is $165,962.
RICE framework example of Impact: We’re implementing a win back discount for users canceling their subscription as the last step in the flow. We expect this to have a low (1%) impact. The impact score is $3,151.
Choosing an impact bucket can feel like guessing, but think of it as ‘What is the most plausible impact range we believe?’ rather than ‘This is a forecast for finance’.
“Choosing an impact number may seem unscientific. But remember the alternative: a tangled mess of gut feeling.” – Sean McBride, RICE: Simple prioritization for product managers
Confidence in RICE
Confidence reflects the level of certainty or confidence you have in the project. A good way to think about it is ‘I’ve had a good idea’ vs ‘I have xx pieces of reliable data to back this up’.
For example: ‘I am 50:50 that this project will work, therefore my confidence score is 50%’ is the wrong way to score confidence. Instead you want to score
- How confident am I that the Reach is correct
- How confident am I in the Impact that the project will have
- How confident am I in the Effort the project will involve
It’s a critical input because it down weighs those ideas which you all instinctively think will be huge – but which you haven’t validated properly yet.
It’s effectively a measure of how much discovery you’ve done on a feature, and can therefore be used to guide how much effort you put into discovery.
Use Itamar Gilad’s Confidence meter as your baseline:
- Similar to when measuring Impact, using a graded, and logarithmic scale to measure risk appropriately and consistently across your backlog is the best option
- It can help to pace your discovery inline with tackling opportunities in backlog, so you’re not wasting time on things that will never come to anything, and you’re not suddenly writing PRDs for things you have not done the discovery on
RICE framework example of Confidence: I’ve got accurate data from our data warehouse regarding the reach. I’ve conducted 30 user interviews, all indicating that implementation of this feature is their number 1 priority. My confidence level therefore is 10% (medium confidence), because user interviews aren’t as accurate as an A/B test, and I’m not sure of the level of effort involved.
RICE framework example of Confidence: We did a statistically significant positive A/B test on this feature. We have very accurate forecasts for Reach and Impact, plus setting up the A/B test means the engineering team knows exactly how much effort implementation will be. Confidence score is 100%.
RICE framework example of Confidence: We have detailed Effort estimates and we’ve validated the Reach numbers with both marketing and data. However the 2 user interviews we’ve conducted mean we’re still unsure on the impact, though internal confidence is high. Confidence score is 1%.
Effort in RICE
This input starts off as a rough estimate of how long you want to invest in the problem (since you have to find your Reach data, calculate Impact, and put the discovery in to get your confidence score), and then evolves into the amount of Effort the project will take from the engineering and design team.
Don’t consider this input to be something you enter once: similar to Confidence you should be continuously evolving this metric.
Once again this is a rough estimate: it’s ok not to be super accurate since you’re looking to understand direction of travel, rather than cost up a project.
A good way to get a rough sense (once again) of the order of magnitude is to ask teams ‘Is this going to take days, weeks, or months to execute?’, and then scoring accordingly:
- ‘Not more than a day’ – score 1
- ‘A few days’ = score 3
- ‘A few weeks’ = score 15
- ‘Months’ = score 50
Avoid using: 1 (small), 2 (medium), 3 (big); because it implies there isn’t a big difference between a small and a big thing: whereas investing a tech team for 3 months is very significantly more costly than 1 day of an engineer.
RICE framework example of Effort: My growth engineer says he could add it in a hour. I’m scoring 1.
RICE framework example of Effort: We’d have to do a lot of discovery and technical work. I’m scoring 50.
RICE framework example of Effort: It’s not tiny, but it’s not massive, and it’s a known quantity. Scoring 15.
Get the free Hustle Badger RICE Framework flashcards here
Calculating overall RICE Framework score
The overall RICE score is calculated by multiplying Reach, Impact, and Confidence, and dividing by Effort.
Reach, Impact and Confidence all increase the value of the project. Effort decreases the value of the project. It’s for that reason that the calculation multiplies Reach, Impact and Confidence together then divides that output by Effort.
Here are some examples of how to calculate RICE. For this we’ve used the Hustle Badger impact scoring method (0-100 impact estimation).
RICE Framework Score Example: Full Calculation
Project: Implementing Google 1 click log in:
- Reach = 50% of all users
- Impact = $740,776
- Confidence = 100%
- Effort = 15
RICE Framework Score = 24693
RICE Framework Score Example: Full Calculation
Project: Introduce local prices in local currencies
- Reach = 3% of all users
- Impact = $165,962
- Confidence = 10%
- Effort = 50
RICE Framework Score = 10
RICE Framework Score Example: Full Calculation
Project: Introduce winback discount for cancelling subscribers
- Reach = 1% of all users
- Impact = $3,151
- Confidence = 1%
- Effort = 3
RICE Framework Score = 0
Get the free Hustle Badger RICE Framework template (pre-calculated) here
Setting up a spreadsheet in advance and inputting your Reach, Impact, Confidence and Effort assumptions can help make calculating this easy.
Remember that RICE scores aren’t a hard and fast rule: you don’t need to work from top to bottom on the list.
There’s often good reasons to tackle number 3, 7, 11, and 19 together – as pieces of work cluster, and by executing all at once, you can lower effort and increase impact.
Why use the RICE framework for prioritization
“Too often, product managers try to answer the question “is this initiative a good initiative or a bad initiative?” – but that’s not the right question to answer. Rather, the right question to answer is “which sequence of initiatives will unlock maximum value for customers, users, and the business?”” – The PM’s Guide to RICE prioritization – Product Teacher
The advantages of the RICE framework for product management
- Makes qualitative information quantifiable & level the playing field
Prioritizing future initiatives is as much an art as a science.
RICE is highly effective in leveling the playing field, allowing you to compare multiple very different options via the same framework.
It spits out 1 simple score which can be quickly understood by senior individuals as a demonstration of a cost benefit analysis – without doing a lot of complex financial modeling.
- Reduces bias
You, or your boss might really love the idea of doing something.
But if you score it robustly, you may see that it doesn’t stack up against something less appealing, or something which has been hanging around for a while.
- Makes reasoning transparent & reduces friction
If you consistently score things according to the same criteria, it promotes egalitarianism and transparency among teams about why you’re doing what you’re doing.
- Creates a stack ranked public prioritization
A public, stack ranked list can be invaluable in terms of managing people’s asks and delivering on agreed priorities in the right sequence.
It can have wide ranging impacts, from better OKRs to making your work ‘pressure-proof’.
- Gives you more time to execute
If you spend less time explaining your reasoning and demonstrating that you’ve heard asks, you have more time to execute.
- Makes you better at impact sizing
Estimation is an art form: you need to practice to get good. If you continually run things through this model, you’ll get much better at sizing effort, impact and so on.
Disadvantages of the RICE framework for product management
The limitations when the RICE framework is used day to day for product management are:
- Does not replace strategy and can be dangerous in a strategy vacuum
Without a coherent strategy, your RICE prioritized opportunity list is just a random list of things.
With a coherent strategy, your RICE prioritized opportunity list is mutually reinforcing and your initiatives add up to more than the sum of their parts.
Clara Nobre, Linkedin
- Does not replace customer discovery
Without investing the time in customer discovery in order to understand your customer needs, RICE can rapidly become a long list of maybes.
Think of RICE as a good check, but not a good starting point.
“All features become a priority because it’s not clear which part (if any) the customer needs and more importantly, will pay for. When that becomes clear, the prioritization falls inline behind it. Now that is laughably more easy to say than do. I’m essentially describing the gap between product and market. But the clearer I understand who I’m for, why I’m for them and what they’ll pay me for, the faster the prioritization falls out.“ Peter Nixey, Linkedin
- Company stage matters
Typically you have more information on product market fit, more data, and more customer understanding at different company stages.
A good rule of thumb about when to use RICE is to sense check your company stage:
- Pre PMF: lean into customer discovery and experimentation; RICE is likely to be unhelpful
- Scaling: RICE is helpful when you want to sense check instinctive prioritization and avoid bias
- Optimizing: RICE is an incredibly useful framework, and the best way to manage multiple competing needs
4. Garbage in, garbage out
Putting in the wrong estimations will lead to a wrong answer. Using the wrong scales will make everything seem similar. It’s a robust tool but make sure it’s using the right inputs.
5. Lack of ability to cluster
Sometimes a host of small things look small when itemized in a list, but are large when combined into a sequence. Similarly, sometimes some pieces of work should be done together in order to ensure proper execution.
6. Stakeholder preference
As with any tool or framework you use as a PM, it’s key that it works for your company and your stakeholders. Don’t force something they don’t engage with.
Get the free Hustle Badger RICE Framework flashcards here
Best practices when calculating a RICE score
When putting together your RICE score:
- Use real data: wherever possible
- Use tools: simple impact models to calculate feature impact
- Avoid common mistakes like over or under estimations by validating your assumptions with colleagues in marketing or data departments.
- Validate impact assumptions via qualitative user research surveys and A/B tests: especially where effort or stakeholder expectation is large
- Don’t get lost in the weeds: you can’t forecast everything perfectly – you’re looking to understand proportions of magnitude, or direction of travel, rather than contribute to Finance’s 202xx plan.
- Avoid being blind to possible side effects: try to understand whether you lose as well as gain
- Iterate: if it comes out looking weird, check everything again; and make sure to keep your RICE list up to date with the latest data, plus add in new possible projects
- Socialise: take your final list to colleagues and allies, and encourage them to play devil’s advocate. Show the list to senior management for feedback. Make your list public.
- Remember that RICE isn’t always the best framework: and familiarize yourself with other options.
Alternatives to RICE for product management tasks
There are many alternatives to RICE, including ICE. ICE is the same framework, excluding the Reach component of the calculation.
Others include MoSCoW, the Prioritization matrix, Kano, WSJF, and the Walking Skeleton approach.
As with everything it’s important to understand: which framework is right for your needs at the time, and which is most effective in helping your stakeholders understand the process of prioritization.
Other ways to think about RICE
“A project with low confidence might be one where all you have is a quick sketch on a whiteboard and a gut feeling. Another way to use the RICE score is as a framework for looking at how to develop ideas. Do you have an idea that you think could have a huge reach and impact, but the confidence is really low? If yes, then what type of user research or technical exploration could your team do to learn more and raise the confidence level?” – Sean McBride
You can think about RICE as a prioritization framework, but also as a way to:
- Ensure you collect the right sort of information about ideas
- Ways to spark creative exploration of how to deliver impact: for example, if effort is high, but all the other scores are high as well – is there another way?
- A communication tool for stakeholders: similar to a public backlog, RICE promotes transparency around why some things are low priority
Wrap on the RICE framework
RICE is a valuable tool for product managers, enabling them to produce transparent, quantifiable stack ranked lists of opportunities.
It can reduce bias in decision making and reduce the friction involved in managing multiple competing stakeholders and priorities.
In order to use RICE effectively, it’s important to be aware of its limitations, where it’s most useful and to invest in making it as robust as possible, via gathering accurate data, validating assumptions and involving your audience.
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FAQS
What is the RICE framework?
The RICE framework is a prioritization methodology often used by PMs to order their backlog for the greatest company impact. It calculates a single score to rank opportunities, based on Reach, Impact, Confidence and Effort estimates (RICE). It has advantages over other product backlog prioritization techniques because it weights complex competing factors against each other to provide increased certainty in the roadmap‘s impact.
What if I don’t have accurate data for Reach or Impact?
In the absence of precise data for Reach use estimates based on available information and assumptions, but be transparent about the level of uncertainty. For Impact use a simple impact model, and bucket impact by orders of magnitude (small – 1%, medium – 10%, large – 100%) to sort opportunities correctly by potential scale of impact.
How often should I update RICE scores?
RICE scores should be updated regularly to reflect changes in priorities, market conditions, or new information. Aim for quarterly or monthly reviews to ensure relevance and accuracy.
Can the RICE framework be applied to non-product-related tasks?
While RICE is primarily used in product management, its principles can be adapted to other domains such as project management, marketing, or strategic planning.
Where can I find a RICE template?
You can find a free RICE template here. It’s precalculated, with notes on how to score Reach, Impact, Confidence and Effort, so all you need to do is to enter your inputs. If you are running a workshop and want to ensure everyone understands RICE in your stakeholder group, we also have you covered with free RICE flashcards here.
What is Reach in the RICE framework?
Reach in the RICE framework refers to the potential audience who will be impacted by the change or feature you want to launch. There are various different ways to calculate Reach. For example, as a percentage of total users, or using the absolute number of users who will see a product or feature. We recommend using a percentage of users, since it helps ensure the same baseline for different types of initiatives. Check out our full review of what Reach is in the RICE framework and how to calculate it with examples here.
What is Impact in the RICE framework?
Impact in the RICE framework is a way to estimate the potential impact of a change, feature or launch upon your given audience group. There’s different ways to calculate it, usually a simplified scoring methodology based on estimates of impact, rather than detailed models. For example, some people score Impact on 0-3, where 0 equals negligible and 3 equals very high. We recommend using a logarithmic scale instead, where 0.1 is very little impact, and 100 is a very large impact, as it displays order of magnitude better. For our full guide to understanding Impact in RICE and scoring it well, including examples, see here.
What is Confidence in the RICE framework?
Confidence in the RICE framework is not a score of whether you have high belief that a feature or change that you make will work. Instead it is a score about how confident you are in your Reach, Impact and Effort calculations. Scoring Confidence is a way to validate your Reach, Impact and Effort assessments via discovery and more detailed analysis. We recommend using a logarithmic scale to do so since it illuminates order of magnitude differences better than a simple score. Check out our full guide to Confidence in RICE, with examples of how to score it here.
What is Effort in the Rice Framework
Effort in the RICE framework starts out as an estimation of the amount of time a product manager wants to put into a project and evolves into an estimate of the full effort required to build and ship something from everyone involved. We recommend scoring it in days and weeks. Check out our full guide to Effort in RICE, with examples of how to score it here.
