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| Criterion |  Decision Making Constraint Analysis |  Architecture C4 Model |  Growth A/B Testing |  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. | The C4 Model makes a system legible across several resolution levels, from context down to code. It suits situations where different audiences need to understand the same architecture from different altitudes. | 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 | Low | Low | High | Medium |
Timedifferent | 30-90 min | 1-4 h | 1-4 Wochen | 45-75 min |
Participantsdifferent | 2-8 | 1-5 | 1-6 | 2-8 |
Formatdifferent | Workshop + async | Workshop + async | Async | Workshop |
Outputdifferent | Constraint List, Hard/Soft Classification, Option Impact Notes, Decision Boundaries | Context Diagram, Container Diagram, Component Diagram | Experiment results, Decision log, Learning summary | Test Matrix, Test Plan |
Tagsno overlap | ConstraintsDecisionPlanningOptions | ArchitectureCommunicationVisualization | ExperimentsGrowthAnalyticsValidation | ExperimentsValidationDiscoveryOptions |