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| Criterion |  Engineering Kanban |  Agile Scrum |  Delivery Monte Carlo Forecasting |
|---|---|---|---|
Purposedifferent | 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 team needs to work in a fixed delivery rhythm, it stabilizes cadence, responsibility, and feedback loops. It makes collaboration reliable across sprint boundaries. | 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 | Medium | Medium | High |
Timedifferent | Ongoing | 1-4 Wochen je Sprint, laufend | 30-90 min Setup, danach laufend |
Participantsdifferent | 2-12 | 3-10 (Scrum Team) | 1-8 |
Formatsame | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Kanban board, WIP policies, Flow metrics | Product Backlog, Sprint Backlog, Increment, Sprint Goal | Forecast Percentiles, Throughput Dataset, Risk Communication |
Tagsno overlap | FlowVisual managementDelivery | AgileIterationCadence | ForecastingFlowDelivery |
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Methods with strong topical overlap with the current selection, not yet in the comparison.
