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| Criterion |  Operations Change Analysis |  Systems Thinking Causal Loop Diagram |  Growth A/B Testing |  Product Discovery Smoke Test |
|---|---|---|---|---|
Purposedifferent | For a deviation after a change, the method isolates the influence of the altered condition. It narrows down which differences are relevant and which are just accompanying noise. | A Causal Loop Diagram makes feedback, reinforcement, and balance in a system legible. It uncovers side effects and self-reinforcement that stay hidden in linear explanations. | 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 | Medium | Medium | High | Low |
Timedifferent | 45-120 min | 1-3 h | 1-4 Wochen | 1-5 Tage |
Participantsdifferent | 2-6 | 2-8 | 1-6 | Nutzertraffic |
Formatdifferent | Workshop + async | Workshop | Async | Async |
Outputdifferent | Change Matrix, Cause Hypotheses, Validation Questions, Action List | Causal Loop Diagram, Feedback Notes, Leverage Points | Experiment results, Decision log, Learning summary | Interest Metrics, Conversion Signal, Learning Note |
Tagsno overlap | ChangeRoot causeTroubleshootingComparison | FeedbackSystems thinkingCausalityDynamics | ExperimentsGrowthAnalyticsValidation | ValidationExperimentsDemandGrowth |