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| Criterion |  Decision Making PERT Estimation |  Engineering Failure Scenario Analysis |  Growth A/B Testing |  Product Discovery Experiment Canvas |
|---|---|---|---|---|
Purposedifferent | On complex initiatives, a plain average tends to understate just how uncertain the outcome really is. It separates options, evaluation criteria, and open risks. The result is captured as a PERT Estimate, Expected Value, and Risk Notes. | 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. | 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 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. |
Complexitydifferent | Medium | Medium | High | Low |
Timedifferent | 15-45 min | 1-3 h | 1-4 Wochen | 30-60 min |
Participantsdifferent | 1-8 | 3-8 | 1-6 | 1-5 |
Formatdifferent | Workshop + async | Workshop | Async | Workshop + async |
Outputdifferent | PERT Estimate, Expected Value, Risk Notes | Failure Scenarios, Risk Notes, Control Gaps, Test and Response Actions | Experiment results, Decision log, Learning summary | Completed Experiment Canvas, Success Metric |
Tagsno overlap | EstimationUncertaintyRisk | FailureResilienceRisk | ExperimentsGrowthAnalyticsValidation | ExperimentsValidationDiscoveryHypothesis |