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| Criterion |  Agile Example Mapping |  Agile NoEstimates |  Agile Specification by Example |  Delivery Monte Carlo Forecasting |
|---|---|---|---|---|
Purposedifferent | 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. | 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 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. | 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 | Low | Medium | Medium | High |
Timedifferent | 30-60 min | laufend | 60-90 min pro Feature | 30-90 min Setup, danach laufend |
Participantsdifferent | 3-7 | 2-12 | 3-6 | 1-8 |
Formatdifferent | Workshop | Workshop + async | Workshop | Workshop + async |
Outputdifferent | Example Map, Acceptance Criteria, Open Questions | Throughput Data, Flow Forecast, Slicing Rules | Example Table, Acceptance Tests | Forecast Percentiles, Throughput Dataset, Risk Communication |
Tagsno overlap | Behavior-Driven DevelopmentRequirementsExamplesRefinement | EstimationForecastingFlow | AgileRequirementsExamplesBehavior-Driven Development | ForecastingFlowDelivery |