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| Criterion |  Agile NoEstimates |  Operations Bottleneck Analysis |  Agile Affinity Estimation |  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. | 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 many tasks need to be classified quickly, it sorts them by perceived effort and similarity. It reduces the effort of fine-grained estimation for large volumes. | 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 | Medium | High |
Timedifferent | laufend | 1-3 h | 30-90 min | 30-90 min Setup, danach laufend |
Participantsdifferent | 2-12 | 3-8 | 3-12 | 1-8 |
Formatdifferent | Workshop + async | Workshop + async | Workshop | Workshop + async |
Outputdifferent | Throughput Data, Flow Forecast, Slicing Rules | Bottleneck Map, Flow Metrics, Improvement Options, Follow-up Measures | Affinity Size Map, Grouped Estimates, Unclear Items | Forecast Percentiles, Throughput Dataset, Risk Communication |
Tagsno overlap | EstimationForecastingFlow | FlowMeasurementConstraints | EstimationBacklogRelative sizing | ForecastingFlowDelivery |