“The best product decisions aren’t made by following frameworks blindly – they’re made by understanding the impact each decision has on your customers and business. Prioritization isn’t about checking boxes; it’s about making hard choices with incomplete information.” – Marty Cagan
Prioritization Made Simple: The Power of Impact, Confidence, and Effort (ICE)
As a product manager, one of the toughest decisions you’ll face is figuring out what to build next. With a never-ending stream of ideas, customer requests, and strategic initiatives, how do you choose where to focus your team’s energy?
Enter the ICE framework—a simple yet powerful way to bring structure to the chaos of prioritization. ICE helps you make informed decisions based on three key factors: Impact, Confidence, and Effort.
Breaking Down ICE
So how does ICE work? It’s simple:
- Impact – What’s the potential value this initiative could bring? This could mean revenue growth, improved customer satisfaction, or a strategic advantage.
- Confidence – How sure are we about the expected impact? This depends on research, past experiments, and user feedback.
- Effort – How much work will it take to execute? Consider not just engineering time, but design, operations, and other dependencies.
To score an idea, you rate each factor on a scale (typically from 1 to 10) and use this formula:
Higher scores indicate more attractive opportunities.
Applying ICE to Real-World Decisions
You can use ICE in many ways, but it’s especially useful for:
- Prioritizing feature requests – Instead of building whatever is loudest, rank features by value and feasibility.
- Deciding on experiments – Growth teams often need to test multiple ideas quickly; ICE helps them focus on the best bets.
- Balancing tech debt and new features – Teams often struggle with maintaining a healthy codebase while shipping new functionality. ICE helps make that trade-off clearer.
- Aligning stakeholders – When multiple teams and leaders have competing priorities, ICE provides a data-driven way to communicate what’s most valuable.
What Good Looks Like
A well-executed ICE process is:
✅ Consistent – Everyone understands how Impact, Confidence, and Effort are scored.
✅ Data-informed – Confidence is based on user insights, research, and past experiences rather than gut feeling.
✅ Flexible – Priorities shift as new data emerges, so ICE scores should be revisited regularly.
✅ Comprehensive – Effort includes not just development work, but design, operational costs, and other hidden factors.
Are There Better Alternatives?
While ICE is a great starting point, it’s not the only prioritization framework out there. Depending on your company’s needs, you might consider:
- RICE (Reach, Impact, Confidence, Effort) – Expands ICE by adding Reach, making it ideal for scaling products.
- MoSCoW (Must-have, Should-have, Could-have, Won’t-have) – A qualitative method that’s useful for high-level planning.
- Kano Model – Helps categorize features based on customer delight vs. necessity.
- Value vs. Effort Matrix – A simple 2×2 grid for visual decision-making.
How ICE Changes with Company Size & Maturity
Startups & Early-Stage Companies
ICE is perfect for rapid experimentation. Since early-stage startups have limited data, Confidence scores may be lower—but that’s okay. The key is to test and iterate quickly.
Growth-Stage Companies
At this stage, companies balance quick wins with long-term investments. Teams may evolve from ICE to RICE to factor in user reach.
Enterprises & Late-Stage Companies
Decision-making is more complex, involving multiple teams and stakeholders. Confidence scores tend to be higher due to data availability, but Effort scores may also rise due to organizational complexity. ICE is often used alongside OKRs and strategic bets.
Wrapping up…
ICE is a lightweight yet effective tool for prioritizing work in product management. While it’s not perfect, its simplicity makes it an excellent starting point. As teams and organizations grow, they can evolve to more sophisticated methods, but ICE remains a go-to framework for quick decision-making.
