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| Criterion |  Operations Bottleneck Analysis |  Agile NoEstimates |  Agile T-Shirt Sizing |  Delivery Monte Carlo Forecasting |
|---|---|---|---|---|
Purposedifferent | 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 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 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 | 1-3 h | laufend | 15-45 min | 30-90 min Setup, danach laufend |
Participantsdifferent | 3-8 | 2-12 | 2-12 | 1-8 |
Formatsame | Workshop + async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Bottleneck Map, Flow Metrics, Improvement Options, Follow-up Measures | Throughput Data, Flow Forecast, Slicing Rules | Size Buckets, Rough Backlog Map, Split Candidates | Forecast Percentiles, Throughput Dataset, Risk Communication |
Tagsno overlap | FlowMeasurementConstraints | EstimationForecastingFlow | EstimationAgileRoadmap | ForecastingFlowDelivery |