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| Criterion |  Delivery Monte Carlo Forecasting |  Agile NoEstimates |  Agile Example Mapping |
|---|---|---|---|
Purposedifferent | 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 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 a story carries business rules and exceptions, it brings clarity before implementation. It makes examples, open questions, and boundaries visible enough that the logic becomes jointly sound. |
Complexitydifferent | High | Medium | Low |
Timedifferent | 30-90 min Setup, danach laufend | laufend | 30-60 min |
Participantsdifferent | 1-8 | 2-12 | 3-7 |
Formatdifferent | Workshop + async | Workshop + async | Workshop |
Outputdifferent | Forecast Percentiles, Throughput Dataset, Risk Communication | Throughput Data, Flow Forecast, Slicing Rules | Example Map, Acceptance Criteria, Open Questions |
Tagsno overlap | ForecastingFlowDelivery | EstimationForecastingFlow | Behavior-Driven DevelopmentRequirementsExamplesRefinement |
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