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| Criterion |  Decision Making Constraint Analysis |  Domain Modeling EventStorming |  Decision Making Decision Tree |  Product Discovery MVP Test Matrix |
|---|---|---|---|---|
Purposedifferent | 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. | When a domain consists of many events, rules, and states, it creates a shared modeling space for the team. It bundles language, flows, and boundaries before domain knowledge fragments into siloed views. | 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 | Low | Medium | Medium | Medium |
Timedifferent | 30-90 min | 2-8 h | 30-90 min | 45-75 min |
Participantsdifferent | 2-8 | 5-12 | 1-6 | 2-8 |
Formatdifferent | Workshop + async | Workshop | Workshop + async | Workshop |
Outputdifferent | Constraint List, Hard/Soft Classification, Option Impact Notes, Decision Boundaries | Event Timeline, Ubiquitous Language, Boundaries, Open Questions | Decision Tree, Option Map, Assumption List | Test Matrix, Test Plan |
Tagsno overlap | ConstraintsDecisionPlanningOptions | Domain-Driven DesignEventsDiscoveryWorkshop | DecisionTreeOptions | ExperimentsValidationDiscoveryOptions |