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| Criterion |  Innovation Design Thinking |  Engineering Failure Scenario Analysis |  Product Discovery Assumption Mapping |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | For complex user problems with an uncertain cause, the method connects observation, interpretation, and experiment into a learning cycle. It keeps the focus on real needs and avoids premature solution language. This produces robust decisions for product and service. | 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 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 | Medium | Medium | High |
Timedifferent | 1 Tag bis mehrere Wochen | 1-3 h | 45-60 min | 1-4 Wochen |
Participantsdifferent | 4-10 | 3-8 | 2-8 | 1-6 |
Formatdifferent | Workshop | Workshop | Workshop + async | Async |
Outputdifferent | Problem Statement, Prototype, Test Learnings | Failure Scenarios, Risk Notes, Control Gaps, Test and Response Actions | Assumption map, Test backlog, Risk ranking | Experiment results, Decision log, Learning summary |
Tagsno overlap | InnovationPrototypeResearch | FailureResilienceRisk | AssumptionsRiskExperimentsValidation | ExperimentsGrowthAnalyticsValidation |