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| Criterion |  Decision Making Constraint Analysis |  Systems Thinking System Dynamics Simulation |  Product Discovery MVP Test Matrix |  Product Discovery Experiment Canvas |
|---|---|---|---|---|
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. | System Dynamics Simulation makes assumptions about time, delay, and feedback testable through experiments. It draws relationships, patterns, and feedback loops. The result is captured as a simulation model and scenario reports. | 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 | Low | High | Medium | Low |
Timedifferent | 30-90 min | Mehrere Tage bis Wochen | 45-75 min | 30-60 min |
Participantsdifferent | 2-8 | 1-5 Modellierende, Stakeholder asynchron | 2-8 | 1-5 |
Formatdifferent | Workshop + async | Async | Workshop | Workshop + async |
Outputdifferent | Constraint List, Hard/Soft Classification, Option Impact Notes, Decision Boundaries | Simulation Model, Scenario Reports | Test Matrix, Test Plan | Completed Experiment Canvas, Success Metric |
Tagsno overlap | ConstraintsDecisionPlanningOptions | Systems thinkingDynamicsSimulationAnalysis | ExperimentsValidationDiscoveryOptions | ExperimentsValidationDiscoveryHypothesis |