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| Criterion |  Product Discovery Concierge MVP |  Decision Making Constraint Analysis |  Decision Making Decision Tree |  Product Discovery MVP Test Matrix |
|---|---|---|---|---|
Purposedifferent | When an idea can first fail or grow through genuine hands-on support, it relies on manual work instead of automation. It shows whether user value holds up even under manual execution. | When an initiative stalls, the limit often lies not in the idea but in hard or soft boundary conditions. Constraint Analysis separates these limits and shows which of them can actually be shaped. | 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 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 | Low | Medium | Medium |
Timedifferent | 1-4 Wochen | 30-90 min | 30-90 min | 45-75 min |
Participantsdifferent | 3-10 Kunden | 2-8 | 1-6 | 2-8 |
Formatdifferent | Workshop + async | Workshop + async | Workshop + async | Workshop |
Outputdifferent | Concierge Learnings, Service Blueprint, MVP Risks | Constraint List, Hard/Soft Classification, Option Impact Notes, Decision Boundaries | Decision Tree, Option Map, Assumption List | Test Matrix, Test Plan |
Tagsno overlap | MVPValidationServiceDiscovery | ConstraintsDecisionPlanningOptions | DecisionTreeOptions | ExperimentsValidationDiscoveryOptions |