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| Criterion |  Operations PDCA Cycle |  Operations Bottleneck Analysis |  Delivery Monte Carlo Forecasting |  Delivery Value Stream Mapping |
|---|---|---|---|---|
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. | For a flow that backs up at one point, the method looks for the capacity limit with the greatest leverage. It explains why extra effort elsewhere barely improves throughput. | 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 delivery work dissolves into wait times, handoffs, and hidden effort, Value Stream Mapping makes the actual flow visible. The method exposes bottlenecks, idle time, and feedback loops so lead time and improvement levers become tangible. |
Complexitydifferent | Low | Medium | High | Medium |
Timedifferent | 1 h bis mehrere Wochen | 1-3 h | 30-90 min Setup, danach laufend | 1-3 h |
Participantsdifferent | 1-8 | 3-8 | 1-8 | 4-10 |
Formatdifferent | Workshop + async | Workshop + async | Workshop + async | Workshop |
Outputdifferent | PDCA Log, Experiment Plan, Learning Outcome, Standard Change | Bottleneck Map, Flow Metrics, Improvement Options, Follow-up Measures | Forecast Percentiles, Throughput Dataset, Risk Communication | Current-state map, Future-state map, Bottleneck list |
Tagsno overlap | Continuous improvementLeanExperiments | FlowMeasurementConstraints | ForecastingFlowDelivery | LeanFlowWasteDelivery |