Assumption Prioritization

Prioritize assumptions to focus validation efforts on what matters most.

When to Use

After assumption mapping, to decide which assumptions to test first.

The Framework

Score each assumption on two dimensions:

Importance (1-5): Business impact if false

• 5 = Strategy fails, >20% revenue hit
• 4 = Major adoption/cost driver (10-20%)
• 3 = Moderate impact (5-10%)
• 2 = Minor impact (<5%)
• 1 = Negligible

Certainty (1-5): Evidence that it's true

• 1 = No evidence, conjecture
• 2 = Anecdotes, untested
• 3 = Early signals, small samples
• 4 = Strong directional data
• 5 = Robust evidence, production proof

Risk Score = Importance x (6 - Certainty)

Higher score = riskier assumption = test first

The Process

1. Score Each Assumption

Consider:

• Impact severity from "impact if wrong"
• Blast radius (users/systems affected)
• Irreversibility (cost to fix later)
• Dependencies (does it block others?)
• Evidence quality

2. Map to Quadrants

	Low Certainty	High Certainty
High Importance	TEST FIRST	Monitor
Low Importance	Deprioritize	Ignore

3. Rank by Risk Score

Focus validation on High Importance / Low Certainty assumptions.

Output

• 2x2 summary with counts per quadrant
• Top risks ranked by score with rationale
• Full ranked list of all assumptions

When Not to Use

Do not use this skill when the request is unrelated, low-stakes, or better handled by a simpler direct response.