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| Criterion |  Operations Fault Tree Analysis |  Product Discovery Experiment Canvas |  Product Discovery Fake Door Test |  Product Discovery Hypothesis Prioritization Canvas |
|---|---|---|---|---|
Purposedifferent | For a critical top event with several possible triggers, the method logically models failure paths. It makes visible which combinations of conditions can lead to damage. | When experiments become unreadable after the fact, it arranges hypothesis, signal, and learning goal on a single canvas. It separates problem, assumption, solution, and evidence. The result is captured as a Completed Experiment Canvas and a Success Metric. | When demand is still unclear, it measures interest in a feature before it is built. It separates real behavior from polite agreement and deliberately keeps build effort small. | When many hypotheses compete for attention, it brings order to their learning sequence and importance. It separates problem, assumption, solution, and evidence. The result is captured as a prioritization canvas and a hypothesis backlog. |
Complexitydifferent | High | Low | Medium | Medium |
Timedifferent | 2-6 h | 30-60 min | 1-5 Tage | 60-90 min |
Participantsdifferent | 3-8 | 1-5 | Nutzertraffic | 3-8 |
Formatdifferent | Workshop + async | Workshop + async | Async | Workshop |
Outputdifferent | Fault Tree, Critical Paths, Cause Hypotheses, Control Actions | Completed Experiment Canvas, Success Metric | Click Data, Interest Signal, Learning Decision | Prioritization Canvas, Hypothesis Backlog |
Tagsno overlap | RiskRoot causeSafety | ExperimentsValidationDiscoveryHypothesis | ValidationExperimentsDemandDiscovery | ExperimentsPrioritizationDiscoveryHypothesis |