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| Criterion |  Decision Making Decision Tree |  Decision Making Delphi Method |  Product Discovery MVP Test Matrix |  Product Discovery Experiment Canvas |
|---|---|---|---|---|
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 knowledge is distributed and direct dominance should be avoided, groups quickly fall under the sway of their opinion leaders. The Delphi Method gathers assessments iteratively and gradually brings expert judgments closer together. | 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. | When experiments become unreadable after the fact, it arranges hypothesis, signal, and learning goal on a single canvas. It separates problem, assumption, solution, and evidence. The result is captured as a Completed Experiment Canvas and a Success Metric. |
Complexitydifferent | Medium | High | Medium | Low |
Timedifferent | 30-90 min | 1-4 Wochen | 45-75 min | 30-60 min |
Participantsdifferent | 1-6 | 6-30 Experten | 2-8 | 1-5 |
Formatdifferent | Workshop + async | Async | Workshop | Workshop + async |
Outputdifferent | Decision Tree, Option Map, Assumption List | Expert Forecast, Consensus Range, Assumption Notes | Test Matrix, Test Plan | Completed Experiment Canvas, Success Metric |
Tagsno overlap | DecisionTreeOptions | ForecastingExpertsDecisionStrategy | ExperimentsValidationDiscoveryOptions | ExperimentsValidationDiscoveryHypothesis |