prioritization-frameworks

name

prioritization-frameworks

description

Applies the right prioritization framework for the context — Opportunity Score, RICE, ICE, MoSCoW, or Kano — with formulas, scoring guidance, and when-to-use rationale. Use when ranking features or problems, comparing approaches, or preparing a prioritized backlog. Triggers on: prioritization, RICE, ICE, MoSCoW, Kano, backlog prioritization, feature ranking, opportunity score, prioritize features, what to build next.

Prioritization Frameworks

Core Philosophy

Never let customers prioritize solutions. Your job is to prioritize problems (opportunities), then find the best solution for the highest-priority problem. When you ask customers which feature to build, they'll always say "all of them."

The right framework depends on the context. No single framework is universally best — pick the one that matches your uncertainty level, team size, and the type of decision you're making.

When to Use

• When the backlog is too large and trade-offs need to be explicit
• When stakeholders disagree on what to build next
• When running a discovery sprint and need to rank opportunities
• When comparing RICE vs ICE vs Opportunity Score for your context

Framework Selection Guide

Framework	Best For	Key Trade-off
Opportunity Score	Ranking customer problems	Most rigorous, requires survey data
RICE	Features at scale, larger teams	More granularity than ICE
ICE	Quick idea triage, early stage	Fast but more subjective
MoSCoW	Scoping releases and negotiations	Qualitative, stakeholder-facing
Kano Model	Understanding feature expectations	Analysis only, not a scoring system
Impact vs Effort	Quick 2×2 for personal task management	Not rigorous for strategic decisions

Frameworks in Detail

Opportunity Score (Recommended for problem prioritization)

Created by Dan Olsen. The most rigorous method for ranking customer problems.

Survey customers on each need:

• Importance: How important is this to you? (1–10)
• Satisfaction: How satisfied are you with current solutions? (1–10)

Normalize to 0–1 scale, then:

• Opportunity Score = Importance × (1 − Satisfaction)
• High Importance + Low Satisfaction = highest priority

Plot on an Importance vs. Satisfaction chart. Upper-left quadrant = sweet spot. Prioritizes problems, not features.

RICE (Recommended for feature prioritization at scale)

Score = (Reach × Impact × Confidence) / Effort

• Reach: Number of customers affected per time period
• Impact: Value per customer (use Opportunity Score or 0.25 / 0.5 / 1 / 2 / 3)
• Confidence: How confident are you? (0–100%)
• Effort: Person-months to implement

Higher score = prioritize first. Accounts for reach as a distinct factor from impact.

ICE (Recommended for quick triage)

Score = Impact × Confidence × Ease

• Impact: Expected outcome improvement (1–10)
• Confidence: How confident are you this will work? (1–10)
• Ease: How easy to implement? (1–10)

Best for fast prioritization of a large idea list. More subjective than RICE.

MoSCoW (Recommended for scoping and stakeholder alignment)

Classify each item:

• Must have: Launch-blocking — the product doesn't work without it
• Should have: High value, not launch-blocking
• Could have: Nice to have, include if time allows
• Won't have (now): Explicitly out of scope this cycle

Caution: "Must have" inflation is common — teams call everything critical. Challenge each Must relentlessly.

Kano Model (For understanding, not scoring)

Classify features by customer expectation:

• Must-be: Expected baseline — absence causes dissatisfaction, presence is neutral
• Performance: More = better (speed, storage, price)
• Attractive: Unexpected delighters — presence drives satisfaction, absence is fine
• Indifferent: Doesn't affect satisfaction either way
• Reverse: Presence annoys some users

Use Kano to understand why a feature matters, not to rank it.

Workflow

1. Choose framework based on what you're prioritizing (problems → Opportunity Score; features → RICE or ICE; scoping → MoSCoW)
2. Gather inputs: Reach from analytics, Impact from user research, Confidence from evidence quality, Effort from engineering estimate
3. Score items using the formula
4. Rank and review: Top-scored items should feel right. If they don't, examine your inputs for bias
5. Socialize: Present the ranked list with the formula and inputs visible — don't just show the scores

Output Format

## Prioritized Backlog — [Product / Sprint / Quarter]

Framework used: [RICE / ICE / Opportunity Score / MoSCoW]

| Item | Reach | Impact | Confidence | Effort | Score | Priority |
|---|---|---|---|---|---|---|

### Top 3 to build next
1. [Item] — Score: X — Rationale: [why this wins]
2. ...
3. ...

### Explicitly deprioritized
[Item] — Why not now: [reason]

Antipatterns

• HiPPO prioritization: Highest Paid Person's Opinion overrides the scores. Use frameworks to make the basis of decisions transparent and challengeable.
• Gaming scores: Inflating Confidence or Impact for pet projects. Show your inputs, not just final scores.
• Prioritizing solutions, not problems: "Build feature X" is a solution. Prioritize the underlying problem first.
• MoSCoW inflation: Every feature becomes "Must have." If everything is critical, nothing is.
• Single-framework dogma: No framework is right for all contexts. Match the framework to the decision type.