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| Criterion |  Agile Story Points |  Agile T-Shirt Sizing |  Delivery Monte Carlo Forecasting |
|---|---|---|---|
Purposedifferent | 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. | When effort only needs to be classified roughly, it makes comparability more important than false precision. It helps sort work quickly into manageable sizes. | 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 | Medium | Low | High |
Timedifferent | laufend, 1-5 min je Item | 15-45 min | 30-90 min Setup, danach laufend |
Participantsdifferent | 3-9 | 2-12 | 1-8 |
Formatsame | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Point Estimates, Reference Stories, Velocity Data | Size Buckets, Rough Backlog Map, Split Candidates | Forecast Percentiles, Throughput Dataset, Risk Communication |
Tagsno overlap | EstimationAgileMeasurement | EstimationAgileRoadmap | ForecastingFlowDelivery |
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