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| Criterion |  Delivery Monte Carlo Forecasting |  Agile Specification by Example |  Agile Example Mapping |  Engineering Kanban |
|---|---|---|---|---|
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 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 work sits in too many parallel streams, throughput suffers and no one sees the bottlenecks. Kanban makes the flow of work visible and limits overload so a system becomes calmer and more predictable. |
Complexitydifferent | High | Medium | Low | Medium |
Timedifferent | 30-90 min Setup, danach laufend | 60-90 min pro Feature | 30-60 min | Ongoing |
Participantsdifferent | 1-8 | 3-6 | 3-7 | 2-12 |
Formatdifferent | Workshop + async | Workshop | Workshop | Workshop + async |
Outputdifferent | Forecast Percentiles, Throughput Dataset, Risk Communication | Example Table, Acceptance Tests | Example Map, Acceptance Criteria, Open Questions | Kanban board, WIP policies, Flow metrics |
Tagsno overlap | ForecastingFlowDelivery | AgileRequirementsExamplesBehavior-Driven Development | Behavior-Driven DevelopmentRequirementsExamplesRefinement | FlowVisual managementDelivery |