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| Criterion |  Systems Thinking Leverage Points |  Product Discovery Smoke Test |  Decision Making Force Field Analysis |  Growth A/B Testing |
|---|---|---|---|---|
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 demand only needs to be roughly verified, it tests interest with minimal effort. It measures whether people would take a next step at all. | In change initiatives, supporting and restraining forces sit at the table at the same time. Force Field Analysis makes these tensions explicit and shows where change can be pushed forward by strengthening or relieving. | 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. |
Complexitydifferent | High | Low | Low | High |
Timedifferent | Half day | 1-5 Tage | 45-90 min | 1-4 Wochen |
Participantsdifferent | 3-12 | Nutzertraffic | 3-12 | 1-6 |
Formatdifferent | Workshop | Async | Workshop | Async |
Outputdifferent | Leverage Map, Action Strategy | Interest Metrics, Conversion Signal, Learning Note | Force Field Map, Change Levers, Risk Notes | Experiment results, Decision log, Learning summary |
Tagsno overlap | Systems thinkingChangeStrategy | ValidationExperimentsDemandGrowth | ChangeDecisionStrategy | ExperimentsGrowthAnalyticsValidation |