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| Criterion |  Engineering Kanban |  Agile Bucket System |  Delivery Monte Carlo Forecasting |  Agile NoEstimates |
|---|---|---|---|---|
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 large batch of work needs a fast, rough estimate, it sorts items into predefined size buckets. It sorts work by value, risk, and delivery ability. The result is captured as a Bucketed Backlog, Relative Estimates, and Split Candidates. | 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 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. |
Complexitydifferent | Medium | Medium | High | Medium |
Timedifferent | Ongoing | 30-90 min | 30-90 min Setup, danach laufend | laufend |
Participantsdifferent | 2-12 | 3-12 | 1-8 | 2-12 |
Formatdifferent | Workshop + async | Workshop | Workshop + async | Workshop + async |
Outputdifferent | Kanban board, WIP policies, Flow metrics | Bucketed Backlog, Relative Estimates, Split Candidates | Forecast Percentiles, Throughput Dataset, Risk Communication | Throughput Data, Flow Forecast, Slicing Rules |
Tagsno overlap | FlowVisual managementDelivery | EstimationBacklogRelative sizing | ForecastingFlowDelivery | EstimationForecastingFlow |