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| Criterion |  Agile Story Points |  Agile NoEstimates |  Delivery Monte Carlo Forecasting |  Agile Ideal Days |
|---|---|---|---|---|
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 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. | When effort needs to be thought of as real working time, it offers a simple common denominator for comparison. It sorts work by value, risk, and delivery ability. The result is captured as Ideal Day Estimates, Assumption Notes, and Capacity Caveats. |
Complexitydifferent | Medium | Medium | High | Low |
Timedifferent | laufend, 1-5 min je Item | laufend | 30-90 min Setup, danach laufend | 15-60 min |
Participantsdifferent | 3-9 | 2-12 | 1-8 | 2-9 |
Formatsame | Workshop + async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Point Estimates, Reference Stories, Velocity Data | Throughput Data, Flow Forecast, Slicing Rules | Forecast Percentiles, Throughput Dataset, Risk Communication | Ideal Day Estimates, Assumption Notes, Capacity Caveats |
Tagsno overlap | EstimationAgileMeasurement | EstimationForecastingFlow | ForecastingFlowDelivery | EstimationEffortAgile |