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| Criterion |  Engineering Failure Scenario Analysis |  Systems Thinking Leverage Points |  Product Discovery Smoke Test |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | In critical processes, it is not enough to plan only for the normal case. Failure Scenario Analysis looks at the path into failure and shows which failures, chains, and control gaps cause the most damage. | 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. | 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 | Medium | High | Low | High |
Timedifferent | 1-3 h | Half day | 1-5 Tage | 1-4 Wochen |
Participantsdifferent | 3-8 | 3-12 | Nutzertraffic | 1-6 |
Formatdifferent | Workshop | Workshop | Async | Async |
Outputdifferent | Failure Scenarios, Risk Notes, Control Gaps, Test and Response Actions | Leverage Map, Action Strategy | Interest Metrics, Conversion Signal, Learning Note | Experiment results, Decision log, Learning summary |
Tagsno overlap | FailureResilienceRisk | Systems thinkingChangeStrategy | ValidationExperimentsDemandGrowth | ExperimentsGrowthAnalyticsValidation |