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| Criterion |  Delivery Monte Carlo Forecasting |  Agile Specification by Example |  Agile Ideal Days |
|---|---|---|---|
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 business rules need to become precise, it ties language, example, and test together. It sorts work by value, risk, and delivery ability. The result is captured as an Example Table and Acceptance Tests. | 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 | High | Medium | Low |
Timedifferent | 30-90 min Setup, danach laufend | 60-90 min pro Feature | 15-60 min |
Participantsdifferent | 1-8 | 3-6 | 2-9 |
Formatdifferent | Workshop + async | Workshop | Workshop + async |
Outputdifferent | Forecast Percentiles, Throughput Dataset, Risk Communication | Example Table, Acceptance Tests | Ideal Day Estimates, Assumption Notes, Capacity Caveats |
Tagsno overlap | ForecastingFlowDelivery | AgileRequirementsExamplesBehavior-Driven Development | EstimationEffortAgile |
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