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| Criterion |  Product Discovery Outcome-Driven Innovation |  Operations Fault Tree Analysis |  Product Discovery Assumption Mapping |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | Outcome-Driven Innovation clarifies customer problems, solution opportunities, and evidence. It separates jobs, desired outcomes, importance, satisfaction, and opportunity, and captures results as desired outcome statements, an opportunity landscape, and segments by underserved needs. | 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 assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first. | When two variants compete, discussions quickly decide by taste rather than effect. A/B Testing checks behavior under controlled conditions and separates real improvement from chance or expectation effects. |
Complexitydifferent | High | High | Medium | High |
Timedifferent | Mehrere Wochen | 2-6 h | 45-60 min | 1-4 Wochen |
Participantsdifferent | 2-6 researchers plus sample | 3-8 | 2-8 | 1-6 |
Formatdifferent | Workshop + async | Workshop + async | Workshop + async | Async |
Outputdifferent | Desired outcome statements, Opportunity landscape, Segmentation by underserved needs, Innovation hypotheses | Fault Tree, Critical Paths, Cause Hypotheses, Control Actions | Assumption map, Test backlog, Risk ranking | Experiment results, Decision log, Learning summary |
Tagsno overlap | OutcomesInnovationResearchQuantitative | RiskRoot causeSafety | AssumptionsRiskExperimentsValidation | ExperimentsGrowthAnalyticsValidation |