01 / UNDERSTAND
What is RICE scoring?
RICE is a prioritisation framework introduced by Intercom. It combines reach, impact, confidence and effort to compare candidate initiatives against a common goal. The score is calculated as reach multiplied by impact and confidence, divided by effort.
RICE makes assumptions visible through a consistent calculation. It does not turn uncertain estimates into objective truth, and the ranking is not an automatic delivery order.
Why use RICE Scoring?
A team may favour a visible request while overlooking work that affects many people. RICE asks the team to consider comparable factors and show the reasoning behind them. Its most useful contribution is often the discussion about an estimate, rather than the numerical difference between two scores.
When to use it
USE IT WHEN
Several discretionary initiatives compete for limited capacity.
The team can define a common outcome and time horizon.
There is enough evidence to make estimates worth comparing.
When to choose another method
Use Impact / Effort Matrix for an earlier qualitative comparison.
Use Assumption Mapping when uncertainty makes numerical estimates misleading.
Handle required accessibility, security or legal work through the appropriate obligation and risk process rather than a popularity ranking.
What you’ll need
Define one outcome, reach period and effort unit. Decide which initiatives are eligible for comparison. Gather evidence for each estimate and involve the people responsible for delivery. Record dependencies and mandatory work separately. Use ranges when a single value would conceal meaningful uncertainty.
What the method needs
Keep the elements that help answer your question and support a decision.
How many relevant people or events are affected in the same defined period.
The expected effect per person on the chosen outcome.
A declared adjustment for the evidence supporting the estimates.
Total work in a consistent unit, including relevant design and delivery activity.
Dependencies, obligations and uncertainty that the score does not resolve.
02 / PUT IT INTO PRACTICE
How to calculate and use RICE scores
Keep evidence and assumptions distinct. Revisit your work when new information changes your understanding.
01
Set the comparison boundary
Agree the outcome, time period and eligible initiatives before scoring.
Do not compare monthly reach for one idea with annual reach for another.
02
Estimate reach and impact
Use relevant data for reach and a consistent impact scale. Intercom describes impact values of 3, 2, 1, 0.5 and 0.25.
Document what a medium impact means for this outcome.
03
Record confidence and effort
Use a confidence fraction such as 1, 0.8 or 0.5 and an agreed effort unit. Explain the evidence behind both.
Enter 80 percent as 0.8 in the calculation.
04
Calculate consistently
Multiply reach by impact and confidence, then divide by effort. Keep effort above zero.
A score is comparable only within the defined scoring setup.
05
Check sensitivity
Recalculate estimates that could plausibly change. Identify whether the leading option remains ahead.
If a small effort change reverses the ranking, investigate before committing.
06
Make and record the decision
Consider dependencies and obligations alongside the ranking. Explain any deliberate departure from score order.
A lower scoring prerequisite may need to happen first.
Example: choosing a booking improvement
Illustrative calculation with invented inputs: option A improves the booking confirmation. Its quarterly reach is 1,000 people, impact 1, confidence 0.8 and effort 2 person months. Its score is 1,000 × 1 × 0.8 ÷ 2 = 400.
Option B adds a rescheduling route: reach 400, impact 2, confidence 0.5 and effort 2. Its score is 200. A leads under these assumptions.
However, confirmation work may require an integration that raises effort to 5 person months. A then scores 160, below B. The useful decision is to investigate that dependency before treating A as the obvious priority. Neither the inputs nor the resulting scores are research findings.
03 / BELOW THE SURFACE
Below the surface: uncertainty can change the order
A clean score can hide a ranking that depends on one weak estimate.
ESTIMATE
Which input has the weakest support?
Name the missing evidence rather than only lowering confidence.
REVERSAL
What plausible change alters the order?
Recalculate the consequential assumption.
ACTION
What can we learn before committing?
Choose an investigation that may change the decision.
Confidence compresses uncertainty into a single multiplier. It does not explain whether the uncertainty concerns reach, benefit or delivery work. Two initiatives with the same confidence value can therefore have very different reasons to pause.
Identify the assumption that would reverse the choice. In the example, checking the integration effort may be more useful than debating a finer impact score. Record a plausible alternative estimate and the resulting order.
This guide proposes the sensitivity check as an editorial extension to the scoring conversation. It does not make RICE a statistical model. It helps the team direct research towards a decision rather than spend time polishing uncertain numbers.
RICE Scoring companion worksheet
The worksheet records two comparable initiatives, their inputs and calculations. Page two checks a changed assumption and the resulting decision. It is an editable recording sheet; calculations are entered manually rather than computed by the PDF.
Practical tips
Keep the same reach period and effort unit across the comparison.
Record why the team chooses to depart from score order.
Common mistakes
Entering a percentage as a whole number in only some rows.
Using different outcomes to justify each impact estimate.
Ignoring dependencies or treating required work as optional.
What you’ll get
A provisional ranking with traceable assumptions and a next decision. Revisit it when evidence changes an input or the strategic goal.