How to Prioritize Features: 7 Frameworks Compared

Prioritization is the defining skill of product management. You will always have more ideas, requests, and problems than your team can handle. The ability to focus on the right things — and say "not now" to the rest — determines whether your product succeeds or becomes a feature factory.

This guide compares 7 frameworks side by side, with honest assessments of when each works and when it falls apart.

Table of Contents

Before You Pick a Framework

No prioritization framework will help you if you do not have these prerequisites:

1. A Clear Strategy

If you do not know what you are trying to achieve this quarter, no scoring model will save you. Prioritization is about ordering work against a goal. Without the goal, you are just sorting cards randomly. See our guide on what is product strategy.

2. A Realistic Capacity Estimate

You need a rough sense of how much your team can build. Without it, prioritization is academic — you cannot make trade-offs if you do not know the constraint.

3. Stakeholder Buy-In on the Process

If your CEO can override any prioritization decision at any time, frameworks are theater. Get agreement upfront: "Here is how we will decide what to build. If we want to change it, we revisit the framework — we do not just swap in a pet feature."

Not sure which framework fits your team? Take the prioritization quiz for a tailored recommendation.

RICE Scoring

Origin: Developed at Intercom by Sean McBride. One of the most widely used quantitative prioritization methods.

How It Works

Score each feature on four dimensions:

Formula: RICE Score = (Reach x Impact x Confidence) / Effort

Real Example

In this example, the onboarding flow wins decisively despite being the most effort — because it reaches 2,000 users with high impact.

Pros

Cons

Try it yourself with the RICE calculator or read the full framework guide on the RICE framework. For a comparison with similar methods, see RICE vs ICE vs MoSCoW.

ICE Scoring

Origin: Popularized by Sean Ellis (of GrowthHackers) for growth experiment prioritization.

How It Works

Score each feature on three dimensions (1-10 scale each):

Formula: ICE Score = Impact x Confidence x Ease

Real Example

Pros

Cons

Calculate scores with the ICE calculator. Read more about the method in the ICE scoring glossary entry.

MoSCoW

Origin: Created by Dai Clegg at Oracle in 1994 for rapid application development.

How It Works

Categorize each feature into one of four buckets:

Real Example — MVP for a Project Management Tool

Pros

Cons

Use the MoSCoW tool to categorize your features interactively. See our framework guide on MoSCoW prioritization and glossary entry on MoSCoW.

Kano Model

Origin: Developed by Professor Noriaki Kano in 1984. Originally a quality management concept.

How It Works

The Kano model classifies features based on how they affect customer satisfaction:

How to Classify

The standard Kano questionnaire asks two questions per feature:

Answer options: Like it, Expect it, Neutral, Can live with it, Dislike it. Cross-referencing the answers classifies the feature.

Real Example — Email Marketing Tool

Pros

Cons

Explore the framework in depth in our Kano model guide and try the Kano analyzer tool.

WSJF (Weighted Shortest Job First)

Origin: Part of the SAFe (Scaled Agile Framework). Designed for teams managing large backlogs with economic trade-offs.

How It Works

Score each feature on three value dimensions and one cost dimension:

Formula: WSJF = (Business Value + Time Criticality + Risk Reduction) / Job Size

The key insight of WSJF is cost of delay. A feature worth $100K that will lose relevance in 3 months should be prioritized over a feature worth $200K that will still be relevant in a year.

Real Example

In this example, API rate limiting and GDPR compliance score highest because of time criticality and risk reduction — even though the new dashboard has the highest raw business value.

Pros

Cons

Try the WSJF calculator to score your backlog.

Value vs Effort Matrix

Origin: A staple of product management and design thinking. No single creator — it has been used in various forms for decades.

How It Works

Plot features on a 2x2 matrix:

              HIGH VALUE
                  │
   ┌──────────────┼──────────────┐
   │              │              │
   │   BIG BETS   │  QUICK WINS  │
   │  (consider   │  (do these   │
   │   carefully)  │   first)     │
   │              │              │
HIGH├──────────────┼──────────────┤LOW
EFFORT            │              EFFORT
   │              │              │
   │  MONEY PIT   │  FILL-INS    │
   │  (avoid)     │  (do if time │
   │              │   permits)   │
   │              │              │
   └──────────────┼──────────────┘
                  │
              LOW VALUE

Execution Steps

Pros

Cons

Opportunity Scoring

Origin: Based on Anthony Ulwick's Outcome-Driven Innovation (ODI) methodology.

How It Works

For each customer job or need:

Formula: Opportunity Score = Importance + max(Importance - Satisfaction, 0)

Features that are high importance AND low satisfaction represent the biggest opportunities. Features that are high importance AND high satisfaction are table stakes — important but already well-served.

Real Example — Project Management Tool

"See all tasks in one view" is the top opportunity — customers care about it deeply but current solutions fail them.

Pros

Cons

Framework Comparison Table

How to Choose the Right Framework

Use RICE When:

Use ICE When:

Use MoSCoW When:

Use Kano When:

Use WSJF When:

Use Value vs Effort When:

Use Opportunity Scoring When:

Combine Frameworks

In practice, the best teams use multiple frameworks:

Key Takeaways