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| Criterion |  Growth A/B Testing |  Operations Failure Mode and Effects Analysis |  Product Discovery Experiment Canvas |  Operations Fishbone Diagram |
|---|---|---|---|---|
Purposedifferent | 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. | For a process, product, or service with noticeable failure risks, the method assesses possible failure modes in advance. It directs attention to combinations of occurrence, effect, and detectability. | 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 a problem has several possible contributing factors, the method sorts causes by cause areas. It prevents an initial hunch from blocking the view of other plausible drivers. |
Complexitydifferent | High | High | Low | Low |
Timedifferent | 1-4 Wochen | 2-6 h | 30-60 min | 30-60 min |
Participantsdifferent | 1-6 | 3-10 | 1-5 | 2-8 |
Formatdifferent | Async | Workshop | Workshop + async | Workshop |
Outputdifferent | Experiment results, Decision log, Learning summary | FMEA Table, Risk Priority, Mitigation Actions | Completed Experiment Canvas, Success Metric | Fishbone Diagram, Cause Categories, Investigation Backlog |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | RiskQualityOperationsRoot cause | ExperimentsValidationDiscoveryHypothesis | Root causeQualityOperations |