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| Criterion |  Operations Visual Management |  Growth Growth Experiment |  Operations Failure Mode and Effects Analysis |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | With high tempo and many parallel topics, the method makes status, deviations, and priorities visible at a glance. It reduces search effort and prevents what matters from getting lost in daily work. | When growth ideas surface quickly, the temptation to build immediately instead of learning is high. A Growth Experiment frames an assumption so target group, lever, and measurement are clear before the first deployment. | 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 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 | Low | Medium | High | High |
Timedifferent | Ongoing | 1-2 Wochen | 2-6 h | 1-4 Wochen |
Participantsdifferent | 1-20 | 1-6 | 3-10 | 1-6 |
Formatdifferent | Workshop + async | Workshop + async | Workshop | Async |
Outputdifferent | Visual Board, Status Indicators, Exception Cues | Experiment card, Result summary, Next bet | FMEA Table, Risk Priority, Mitigation Actions | Experiment results, Decision log, Learning summary |
Tagsno overlap | SignalsOperationsVisual management | MarketingGrowthExperimentsLearning | RiskQualityOperationsRoot cause | ExperimentsGrowthAnalyticsValidation |