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| Criterion |  Delivery Monte Carlo Forecasting |  Operations Bottleneck Analysis |  Agile Story Points |
|---|---|---|---|
Purposedifferent | 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. | When teams want to rate complexity rather than hours, it creates a shared, relative scale. It sorts work by value, risk, and delivery ability. The result is captured as Point Estimates, Reference Stories, and Velocity Data. |
Complexitydifferent | High | Medium | Medium |
Timedifferent | 30-90 min Setup, danach laufend | 1-3 h | laufend, 1-5 min je Item |
Participantsdifferent | 1-8 | 3-8 | 3-9 |
Formatsame | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Forecast Percentiles, Throughput Dataset, Risk Communication | Bottleneck Map, Flow Metrics, Improvement Options, Follow-up Measures | Point Estimates, Reference Stories, Velocity Data |
Tagsno overlap | ForecastingFlowDelivery | FlowMeasurementConstraints | EstimationAgileMeasurement |
Often compared together
Methods with strong topical overlap with the current selection, not yet in the comparison.
