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| Criterion |  Engineering Failure Scenario Analysis |  Growth Flywheel |  Product Discovery Experiment Canvas |  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. | Growth often breaks down where a reinforcing mechanism builds up too much friction. A Flywheel shows the cycle of value, repetition, and reinforcement meant to sustain growth. | When experiments become unreadable after the fact, it arranges hypothesis, signal, and learning goal on a single canvas. It separates problem, assumption, solution, and evidence. The result is captured as a Completed Experiment Canvas and a Success Metric. | 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 | Medium | Low | High |
Timedifferent | 1-3 h | 60-120 min | 30-60 min | 1-4 Wochen |
Participantsdifferent | 3-8 | 3-8 | 1-5 | 1-6 |
Formatdifferent | Workshop | Workshop | Workshop + async | Async |
Outputdifferent | Failure Scenarios, Risk Notes, Control Gaps, Test and Response Actions | Flywheel Map, Friction Points, Growth Levers, Experiment Backlog | Completed Experiment Canvas, Success Metric | Experiment results, Decision log, Learning summary |
Tagsno overlap | FailureResilienceRisk | GrowthRetentionConversion | ExperimentsValidationDiscoveryHypothesis | ExperimentsGrowthAnalyticsValidation |