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| Criterion |  Operations DMAIC |  Delivery Monte Carlo Forecasting |  Operations Bottleneck Analysis |
|---|---|---|---|
Purposedifferent | For a process problem with fluctuating performance, the method brings analysis and improvement into a disciplined sequence. It creates a framework in which numbers, causes, and control come together. | 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. | 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. |
Complexitydifferent | High | High | Medium |
Timedifferent | 2-12 Wochen | 30-90 min Setup, danach laufend | 1-3 h |
Participantsdifferent | 3-10 | 1-8 | 3-8 |
Formatsame | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Project Charter, Measurement Plan, Cause Analysis, Control Plan | Forecast Percentiles, Throughput Dataset, Risk Communication | Bottleneck Map, Flow Metrics, Improvement Options, Follow-up Measures |
Tagsno overlap | Continuous improvementQualityProcess improvement | ForecastingFlowDelivery | FlowMeasurementConstraints |
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