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| Criterion |  Systems Thinking Leverage Points |  Domain Modeling Bounded Context Canvas |  Growth A/B Testing |  Product Discovery Smoke Test |
|---|---|---|---|---|
Purposedifferent | Leverage Points show exactly where interventions in a system produce a disproportionate effect. It draws relationships, patterns, and feedback loops. The result is captured as a leverage map and action strategy. | When a business context is still loosely outlined, it shapes language, responsibility, and integration space. It clarifies what belongs together and where a boundary needs to hold. | 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 demand only needs to be roughly verified, it tests interest with minimal effort. It measures whether people would take a next step at all. |
Complexitydifferent | High | Medium | High | Low |
Timedifferent | Half day | 1-3 h | 1-4 Wochen | 1-5 Tage |
Participantsdifferent | 3-12 | 3-8 | 1-6 | Nutzertraffic |
Formatdifferent | Workshop | Workshop + async | Async | Async |
Outputdifferent | Leverage Map, Action Strategy | Context Canvas, Glossary, Integration Notes | Experiment results, Decision log, Learning summary | Interest Metrics, Conversion Signal, Learning Note |
Tagsno overlap | Systems thinkingChangeStrategy | Domain-Driven DesignBoundariesModeling | ExperimentsGrowthAnalyticsValidation | ValidationExperimentsDemandGrowth |