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| Criterion |  Operations PDCA Cycle |  Operations Gemba Walk |  Delivery Monte Carlo Forecasting |
|---|---|---|---|
Purposedifferent | For an improvement that still has to prove itself in everyday work, the method runs it through small learning loops. It connects planning, checking, and standardization into a repeatable learning mode. | When there is uncertainty about the real course of a process, the method brings observation to the place where work happens. It combines perception, follow-up questions, and process knowledge so decisions rest on actual workflows instead of assumptions. | 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. |
Complexitydifferent | Low | Low | High |
Timedifferent | 1 h bis mehrere Wochen | 30-120 min | 30-90 min Setup, danach laufend |
Participantsdifferent | 1-8 | 2-6 | 1-8 |
Formatdifferent | Workshop + async | Workshop | Workshop + async |
Outputdifferent | PDCA Log, Experiment Plan, Learning Outcome, Standard Change | Observation Notes, Improvement Ideas | Forecast Percentiles, Throughput Dataset, Risk Communication |
Tagsno overlap | Continuous improvementLeanExperiments | LeanObservationProcessOperations | ForecastingFlowDelivery |
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