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| Criterion |  Product Discovery Dual-Track Agile |  Decision Making Decision Tree |  Product Discovery Fake Door Test |  Product Discovery MVP Test Matrix |
|---|---|---|---|---|
Purposedifferent | When uncertainty and delivery run in parallel, it separates learning work from implementation while keeping both connected. It prevents unvalidated ideas from falling directly into the delivery stream. | 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 demand is still unclear, it measures interest in a feature before it is built. It separates real behavior from polite agreement and deliberately keeps build effort small. | 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. |
Complexitysame | Medium | Medium | Medium | Medium |
Timedifferent | Laufend, Wochen bis Monate | 30-90 min | 1-5 Tage | 45-75 min |
Participantsdifferent | 4-10 | 1-6 | Nutzertraffic | 2-8 |
Formatdifferent | Workshop + async | Workshop + async | Async | Workshop |
Outputdifferent | Discovery Backlog, Delivery Backlog, Experiment-Ergebnisse, Validierte Stories | Decision Tree, Option Map, Assumption List | Click Data, Interest Signal, Learning Decision | Test Matrix, Test Plan |
Tagsno overlap | AgileDiscoveryDelivery | DecisionTreeOptions | ValidationExperimentsDemandDiscovery | ExperimentsValidationDiscoveryOptions |