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| Criterion |  Delivery Monte Carlo Forecasting |  Engineering Kanban |  Agile Story Splitting |  Delivery Value Stream 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 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. | When a story becomes too large for a clean flow, it breaks scope down along value and risk. It shapes the work into a form that ships earlier and is easier to verify. | When delivery work dissolves into wait times, handoffs, and hidden effort, Value Stream Mapping makes the actual flow visible. The method exposes bottlenecks, idle time, and feedback loops so lead time and improvement levers become tangible. |
Complexitydifferent | High | Medium | Medium | Medium |
Timedifferent | 30-90 min Setup, danach laufend | Ongoing | 30-60 min | 1-3 h |
Participantsdifferent | 1-8 | 2-12 | 2-6 | 4-10 |
Formatdifferent | Workshop + async | Workshop + async | Workshop + async | Workshop |
Outputdifferent | Forecast Percentiles, Throughput Dataset, Risk Communication | Kanban board, WIP policies, Flow metrics | Smaller Stories, Acceptance Criteria, Split Rationale | Current-state map, Future-state map, Bottleneck list |
Tags1 shared | ForecastingFlowDelivery | FlowVisual managementDelivery | BacklogIterationDelivery | LeanFlowWasteDelivery |