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| Criterion |  Operations PDCA Cycle |  Operations Kaizen Event |  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. | For a tightly scoped process segment with noticeable waste, the method bundles shared energy for change. It suits situations that call for fast learning loops and visible adjustments. | 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 | Medium | High |
Timedifferent | 1 h bis mehrere Wochen | 0.5-5 Tage | 30-90 min Setup, danach laufend |
Participantsdifferent | 1-8 | 4-10 | 1-8 |
Formatdifferent | Workshop + async | Workshop | Workshop + async |
Outputdifferent | PDCA Log, Experiment Plan, Learning Outcome, Standard Change | Kaizen Charter, Waste List, Improvement Experiments, Standard Work Update | Forecast Percentiles, Throughput Dataset, Risk Communication |
Tagsno overlap | Continuous improvementLeanExperiments | LeanContinuous improvementOperations | ForecastingFlowDelivery |
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Methods with strong topical overlap with the current selection, not yet in the comparison.
