Prioritization
RICE scoring explained, with a worked example
Reach × Impact × Confidence ÷ Effort. The formula is simple; using it honestly is the hard part. Here's how each factor works and a full example you can copy.
RICE is the most widely used product prioritization formula because it does one thing well: it lets you compare features that have nothing in common — a bug fix, a new integration, an onboarding redesign — on a single scale. The formula is (Reach × Impact × Confidence) ÷ Effort. The discipline is in how you set each factor honestly.
The four factors
Reach — how many people or events this affects in a set time period. A real number, not a rating: "users per quarter," "checkouts per month." If a feature touches 2,000 users a quarter, Reach is 2,000.
Impact — how much it moves the needle for each person it reaches, on a fixed scale: 3 = massive, 2 = high, 1 = medium, 0.5 = low, 0.25 = minimal. The fixed scale is what keeps "Impact" from becoming wishful thinking.
Confidence — how sure you are of your reach and impact estimates: 100% (high, you have data), 80% (medium), 50% (low, it's a hunch). This is the honesty valve. When you're guessing, lower it.
Effort — total work in person-months, across design, engineering, and QA. It's the denominator, so high-effort items get pushed down unless their numerator is large.
A worked example
Say you're a PM for a mobile app weighing three items:
| Item | Reach | Impact | Confidence | Effort | RICE |
|---|---|---|---|---|---|
| Faster onboarding | 5,000 | 2 | 0.8 | 2 | 4,000 |
| Add Apple Pay | 3,000 | 1 | 1.0 | 1.5 | 2,000 |
| Dark mode | 8,000 | 0.5 | 1.0 | 3 | 1,333 |
Onboarding wins despite a smaller reach than dark mode, because its impact is higher and its effort is lower. Dark mode reaches everyone but barely moves satisfaction per person and costs a lot — exactly the kind of popular-but-low-leverage work RICE is designed to catch.
Where RICE misleads
RICE can be precisely wrong. The risks: inventing reach numbers and leaving Confidence at 100%; rating everything Impact 2 or 3 because you like it; and forgetting that the score is a starting point for a conversation, not a verdict. A 4,000 and a 3,800 are a tie — don't let two decimal places of false precision override judgment. Use the score to surface the obvious wins and obvious skips, and reason about the middle.
- RICE = (Reach × Impact × Confidence) ÷ Effort — one number to compare unlike features.
- Reach is a real count per time period; Impact uses a fixed scale (3/2/1/0.5/0.25); Confidence is 100/80/50%.
- Effort is person-months, and it's the denominator — so cheap wins float to the top.
- Confidence is the honesty valve: low it when your reach and impact are guesses.
Try the Prioritization workflow in Cadenly
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