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| Criterion |  Decision Making Decision Tree |  Decision Making PERT Estimation |  Growth A/B Testing |  Product Discovery MVP Test Matrix |
|---|---|---|---|---|
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. | On complex initiatives, a plain average tends to understate just how uncertain the outcome really is. It separates options, evaluation criteria, and open risks. The result is captured as a PERT Estimate, Expected Value, and Risk Notes. | 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. | 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. |
Complexitydifferent | Medium | Medium | High | Medium |
Timedifferent | 30-90 min | 15-45 min | 1-4 Wochen | 45-75 min |
Participantsdifferent | 1-6 | 1-8 | 1-6 | 2-8 |
Formatdifferent | Workshop + async | Workshop + async | Async | Workshop |
Outputdifferent | Decision Tree, Option Map, Assumption List | PERT Estimate, Expected Value, Risk Notes | Experiment results, Decision log, Learning summary | Test Matrix, Test Plan |
Tagsno overlap | DecisionTreeOptions | EstimationUncertaintyRisk | ExperimentsGrowthAnalyticsValidation | ExperimentsValidationDiscoveryOptions |