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| Criterion |  Operations PDCA Cycle |  Agile NoEstimates |  Delivery Monte Carlo Forecasting |  Operations Kaizen Event |
|---|---|---|---|---|
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 estimating slows a team down more than it helps, it shifts the focus to flow, small slices, and real lead time. It sorts work by value, risk, and delivery ability. The result is captured as Throughput Data, Flow Forecast, and Slicing Rules. | 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 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. |
Complexitydifferent | Low | Medium | High | Medium |
Timedifferent | 1 h bis mehrere Wochen | laufend | 30-90 min Setup, danach laufend | 0.5-5 Tage |
Participantsdifferent | 1-8 | 2-12 | 1-8 | 4-10 |
Formatdifferent | Workshop + async | Workshop + async | Workshop + async | Workshop |
Outputdifferent | PDCA Log, Experiment Plan, Learning Outcome, Standard Change | Throughput Data, Flow Forecast, Slicing Rules | Forecast Percentiles, Throughput Dataset, Risk Communication | Kaizen Charter, Waste List, Improvement Experiments, Standard Work Update |
Tagsno overlap | Continuous improvementLeanExperiments | EstimationForecastingFlow | ForecastingFlowDelivery | LeanContinuous improvementOperations |