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| Criterion |  Innovation Design Sprint |  Decision Making Decision Tree |  Growth A/B Testing |  Product Discovery MVP Test Matrix |
|---|---|---|---|---|
Purposedifferent | When the product question is unclear and time pressure is high, the method takes a team from an open idea to a testable solution. It connects problem understanding, decision, and learning in one compact format, lowering the risk of spending a lot of energy on a mere guess. | 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 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 | High | Medium | High | Medium |
Timedifferent | 4-5 Tage | 30-90 min | 1-4 Wochen | 45-75 min |
Participantsdifferent | 5-8 | 1-6 | 1-6 | 2-8 |
Formatdifferent | Workshop | Workshop + async | Async | Workshop |
Outputdifferent | Prototype, Test Findings, Decision Rationale | Decision Tree, Option Map, Assumption List | Experiment results, Decision log, Learning summary | Test Matrix, Test Plan |
Tagsno overlap | Design sprintPrototypeValidationInnovation | DecisionTreeOptions | ExperimentsGrowthAnalyticsValidation | ExperimentsValidationDiscoveryOptions |