Rice prioritization

rice-prioritization

When to use

• A backlog has more candidates than capacity for the next quarter and someone has to pick.
• A PM and an engineering lead disagree on what ships first and need a shared framework.
• A draft roadmap reads like a wish list — no transparency on why these and not those.

Do NOT use for valuation, OKR decomposition, or funnel-stage diagnosis (see Related Skills).

Procedure

Step 0: Inspect

1. Confirm there are at least 5 candidates. RICE on 2 items is theatre; just argue the merits.
2. Confirm there is a shared definition of the target user for "Reach" — RICE breaks if two scorers count different populations.

Step 1: Score Reach

1. Reach = number of users / events / requests per fixed time window (per quarter is the default).
2. Use absolute counts pulled from analytics or product DB, not percentages — percentages hide tiny denominators.
3. If the data isn't there, write the query you'd run and say so. Do not invent numbers.

Step 2: Score Impact

1. Use the canonical 5-point scale: 0.25 (minimal) · 0.5 (low) · 1 (medium) · 2 (high) · 3 (massive).
2. Anchor each level with a concrete past shipped feature ("medium = like the search filter we shipped Q2"). Without anchors, scorers drift.
3. Impact is per affected user, not aggregate. Aggregate is what RICE produces, not what you input.

Step 3: Score Confidence

1. Confidence is a percentage — 100 / 80 / 50 / "low and we should not score this yet".
2. Anything below 50 means: stop, do a spike or a research week, then re-score. RICE does not rescue ignorance.
3. Confidence multiplies — it is the model's discount for unknown unknowns.

Step 4: Score Effort

1. Effort = person-months for the smallest viable shippable slice. Not the fantasy version.
2. Engineering owns this number. PMs scoring effort is the most common process failure.
3. Effort < 0.5 person-months almost always means scope is underestimated — surface and ask.

Step 5: Compute and rank

1. RICE = (Reach × Impact × Confidence) / Effort.
2. Rank descending. The score is the artefact, not the answer — read the top 5 with a critical eye.
3. Anti-pattern: treating RICE rank as a contract. It is a structured argument, not a verdict.

Step 6: Audit the bottom

1. Look at the bottom quartile. If a strategic must-have lives there, the model has a calibration error — usually Reach or Impact.
2. Look at the top item. If it is obviously absurd (e.g. one ad-hoc admin tool above a strategic platform play), the input scoring is uncalibrated.

Gotcha

• Reach in percentages hides "this feature affects 100% of … 12 users."
• Impact inflation: every PM thinks every feature is a 2 or 3. Force at least 30% of items to score 0.5 or below.
• Confidence is the only multiplier that punishes uncertainty — do not let it default to 80 for everything.
• Effort discrepancy between PM and engineering on the same row is itself the signal — investigate, do not average.

Do NOT

• Do NOT rank fewer than 5 candidates with RICE — overhead exceeds value.
• Do NOT mix strategic bets and BAU tickets in the same RICE table; their effort scales differ by 10×.
• Do NOT ship a roadmap that is exactly the RICE-sorted top-N — you need at least one strategic outlier with a written rationale.

Related Skills

WHEN to use this

• Ranking is the actual question.
• The team needs a shared, auditable scoring frame.

WHEN NOT to use this

• ONE choice between alternatives on custom criteria (not many items on the fixed R×I×C/E formula) — route to decision-record § Weighted-matrix mode.
• Decomposing an objective into KRs — route to okr-tree-modeling.
• Diagnosing why a funnel stage drops — route to funnel-analysis.
• Modelling whether an investment is worth its capital cost — route to dcf-modeling.
• CAC / LTV / payback questions — route to unit-economics-modeling.

When the agent should load this

• "Help me prioritize the backlog for Q3."
• "RICE-score these features."
• "Why is X above Y on the roadmap?"
• "We have 30 ideas and 6 engineers — what ships?"
• "Audit our roadmap for low-value work."

Output

1. rice-table.md — markdown table: Item · Reach · Impact · Confidence · Effort · RICE · Owner · Notes. Sorted descending by RICE.
2. calibration-notes.md — one paragraph per anchor (what "Impact = 2" means with a named past feature) plus a list of items with confidence < 50 marked for spike-first.
3. top-5-critique.md — one paragraph per top-5 item: is the rank defensible, and what would change it.