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| Criterion |  Operations Visual Management |  Delivery Monte Carlo Forecasting |  Product Discovery Assumption Mapping |  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. | Helps clarify scope, sequence, and delivery flow in concrete terms. It makes work, boundaries, and order steerable. The result is captured as Forecast Percentiles, Throughput Dataset, and Risk Communication. | When assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first. | 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 | High | Medium | High |
Timedifferent | Ongoing | 30-90 min Setup, danach laufend | 45-60 min | 1-4 Wochen |
Participantsdifferent | 1-20 | 1-8 | 2-8 | 1-6 |
Formatdifferent | Workshop + async | Workshop + async | Workshop + async | Async |
Outputdifferent | Visual Board, Status Indicators, Exception Cues | Forecast Percentiles, Throughput Dataset, Risk Communication | Assumption map, Test backlog, Risk ranking | Experiment results, Decision log, Learning summary |
Tagsno overlap | SignalsOperationsVisual management | ForecastingFlowDelivery | AssumptionsRiskExperimentsValidation | ExperimentsGrowthAnalyticsValidation |