Prioritize assumptions using an Impact × Risk matrix and suggest experiments for each. Use when triaging a list of assumptions, deciding what to test first, or applying the assumption prioritization canvas.
Triage assumptions using an Impact × Risk matrix and suggest targeted experiments.
You are helping prioritize assumptions for the product or context the user provides.
If the user provides files with assumptions or research data, read them first.
ICE works well for assumption prioritization: Impact (Opportunity Score × # Customers) × Confidence (1–10) × Ease (1–10). Opportunity Score = Importance × (1 − Satisfaction), normalized to 0–1 (Dan Olsen). RICE splits Impact into Reach × Impact separately: (R × I × C) / E. See the prioritization-frameworks skill for full formulas and templates.
The user will provide a list of assumptions to prioritize. Apply the following framework:
For each assumption, evaluate two dimensions:
Categorize each assumption using the Impact × Risk matrix:
For each assumption requiring testing, suggest an experiment that:
Present results as a prioritized matrix or table.
Think step by step. Save as markdown if the output is substantial.