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| Criterion |  Decision Making Decision Tree |  Product Discovery Assumption Mapping |  Knowledge Modeling Knowledge Mapping |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | For decisions with follow-on paths and dependencies, a linear comparison is often not enough. A Decision Tree shows how options branch under conditions and which consequences hang on each branch. | When assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first. | Knowledge Mapping makes knowledge, gaps, and transfer paths visible across a field. It fits when expertise should not just exist but also be findable and transferable. | 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 | Medium | Medium | Medium | High |
Timedifferent | 30-90 min | 45-60 min | 1-3 h | 1-4 Wochen |
Participantsdifferent | 1-6 | 2-8 | 3-12 | 1-6 |
Formatdifferent | Workshop + async | Workshop + async | Workshop | Async |
Outputdifferent | Decision Tree, Option Map, Assumption List | Assumption map, Test backlog, Risk ranking | Knowledge Map, Critical Knowledge Areas, Transfer Plan | Experiment results, Decision log, Learning summary |
Tagsno overlap | DecisionTreeOptions | AssumptionsRiskExperimentsValidation | KnowledgeMappingRisk | ExperimentsGrowthAnalyticsValidation |