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| Criterion |  Growth A/B Testing |  Engineering Failure Scenario Analysis |  Product Discovery MVP Test Matrix |  Product Discovery Assumption Mapping |
|---|---|---|---|---|
Purposedifferent | 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. | In critical processes, it is not enough to plan only for the normal case. Failure Scenario Analysis looks at the path into failure and shows which failures, chains, and control gaps cause the most damage. | When several minimal variants compete to answer the same question, it makes comparing and choosing between them cleaner. It separates problem, assumption, solution, and evidence. The result is captured as a Test Matrix and a Test Plan. | When assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first. |
Complexitydifferent | High | Medium | Medium | Medium |
Timedifferent | 1-4 Wochen | 1-3 h | 45-75 min | 45-60 min |
Participantsdifferent | 1-6 | 3-8 | 2-8 | 2-8 |
Formatdifferent | Async | Workshop | Workshop | Workshop + async |
Outputdifferent | Experiment results, Decision log, Learning summary | Failure Scenarios, Risk Notes, Control Gaps, Test and Response Actions | Test Matrix, Test Plan | Assumption map, Test backlog, Risk ranking |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | FailureResilienceRisk | ExperimentsValidationDiscoveryOptions | AssumptionsRiskExperimentsValidation |