assumption-mapping

To find hidden assumptions in a product roadmap, you surface implicit beliefs from goals and metrics, convert them into falsifiable claims, and rate their importance against existing evidence. This exposes untested beliefs that can derail projects.

Assumption mapping reduces project risk by extracting untested beliefs from go-to-market plans, placing them on an importance versus evidence grid, and recommending minimum viable experiments to validate critical items before major investment.

You prioritize product assumptions to test by plotting them on an importance-evidence grid. This highlights critical items with high importance and low evidence, allowing teams to focus validation efforts and run cheap tests first.

Yes, you can audit a PRD for untested monetization and demand assumptions by extracting implicit beliefs from resourcing statements and strategy claims, then framing them as specific, testable claims to validate before scaling.

You convert vague strategy beliefs into testable claims for experiment design by framing them as specific, falsifiable statements that can be proven true or false, then generating minimum viable experiments to validate them.

You should run an assumption audit on research artifacts when preparing for major investment, ensuring embedded beliefs are rated and critical items are tested with minimal experiments to reduce project risk.