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| Criterion |  Systems Thinking Leverage Points |  Innovation Design Sprint |  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 the product question is unclear and time pressure is high, the method takes a team from an open idea to a testable solution. It connects problem understanding, decision, and learning in one compact format, lowering the risk of spending a lot of energy on a mere guess. | 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 | High | High | Low |
Timedifferent | Half day | 4-5 Tage | 1-4 Wochen | 1-5 Tage |
Participantsdifferent | 3-12 | 5-8 | 1-6 | Nutzertraffic |
Formatdifferent | Workshop | Workshop | Async | Async |
Outputdifferent | Leverage Map, Action Strategy | Prototype, Test Findings, Decision Rationale | Experiment results, Decision log, Learning summary | Interest Metrics, Conversion Signal, Learning Note |
Tagsno overlap | Systems thinkingChangeStrategy | Design sprintPrototypeValidationInnovation | ExperimentsGrowthAnalyticsValidation | ValidationExperimentsDemandGrowth |