Module
Module 3 of 6Lesson 1 of 2~18 min

One method per question: RICE, ICE, Kano, opportunity score

How to choose the prioritization method that fits the question you are asking, and know what each score leaves in the dark. You walk into the planning meeting with a reasoned ranking rather than a bare table of scores, and you can respond when someone challenges the method you used.

Take this lesson: your first course is freeSee the full syllabus

Lesson objective

By the end of this lesson, you will be able to choose the prioritization method that answers the question at hand (compare ideas, quickly sort experiments, compose an offering, find underserved needs), apply it to real data and say what it does not see.

Topics covered

  • RICE
  • ICE score
  • Kano model
  • opportunity score
  • product prioritization

Where it fits

Prioritize with method

Out of all the possible bets, which ones come first, and with which method?

Lessons in this module

  1. One method per question: RICE, ICE, Kano, opportunity score (this lesson)
  2. When time costs money: cost of delay, CD3 and WSJF

What you will learn in the course

This lesson is part of the course Prioritize and build an outcome-based roadmap

  • Tell outputs, product outcomes and business outcomes apart, and phrase a team's goal as a measurable change in behavior it can influence.
  • Write useful OKRs (a qualitative objective, measurable key results, guardrails) and spot their common failure modes.
  • Choose and apply a prioritization method suited to the question at hand (RICE, ICE, Kano, opportunity scoring, cost of delay, WSJF), taking its limits into account.
  • Handle requests from sales, support and leadership starting from the problem behind them, and say no or not now with reasons.
  • Build a Now, Next, Later or theme-based roadmap tied to measurable outcomes, with external commitments shown separately.
  • Communicate uncertainty and dates according to horizon and audience, and review the roadmap on a written rhythm and set of triggers.
  • Use AI to synthesize roadmap inputs (feedback, requests, data) while keeping evidence traceable and the decision human.

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