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| Criterion |  Agile NoEstimates |  Agile Story Points |  Agile T-Shirt Sizing |  Delivery Monte Carlo Forecasting |
|---|---|---|---|---|
Purposedifferent | 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. | 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 | Medium | Low | High |
Timedifferent | laufend | laufend, 1-5 min je Item | 15-45 min | 30-90 min Setup, danach laufend |
Participantsdifferent | 2-12 | 3-9 | 2-12 | 1-8 |
Formatsame | Workshop + async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Throughput Data, Flow Forecast, Slicing Rules | Point Estimates, Reference Stories, Velocity Data | Size Buckets, Rough Backlog Map, Split Candidates | Forecast Percentiles, Throughput Dataset, Risk Communication |
Tagsno overlap | EstimationForecastingFlow | EstimationAgileMeasurement | EstimationAgileRoadmap | ForecastingFlowDelivery |