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| Criterion |  Decision Making Force Field Analysis |  Product Discovery Smoke Test |  Product Discovery Assumption Mapping |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | In change initiatives, supporting and restraining forces sit at the table at the same time. Force Field Analysis makes these tensions explicit and shows where change can be pushed forward by strengthening or relieving. | When demand only needs to be roughly verified, it tests interest with minimal effort. It measures whether people would take a next step at all. | 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 | Low | Low | Medium | High |
Timedifferent | 45-90 min | 1-5 Tage | 45-60 min | 1-4 Wochen |
Participantsdifferent | 3-12 | Nutzertraffic | 2-8 | 1-6 |
Formatdifferent | Workshop | Async | Workshop + async | Async |
Outputdifferent | Force Field Map, Change Levers, Risk Notes | Interest Metrics, Conversion Signal, Learning Note | Assumption map, Test backlog, Risk ranking | Experiment results, Decision log, Learning summary |
Tagsno overlap | ChangeDecisionStrategy | ValidationExperimentsDemandGrowth | AssumptionsRiskExperimentsValidation | ExperimentsGrowthAnalyticsValidation |