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| Criterion |  Delivery Monte Carlo Forecasting |  Delivery Value Stream Mapping |  Agile Bucket System |  Agile Affinity Estimation |
|---|---|---|---|---|
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 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. | 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. | When many tasks need to be classified quickly, it sorts them by perceived effort and similarity. It reduces the effort of fine-grained estimation for large volumes. |
Complexitydifferent | High | Medium | Medium | Medium |
Timedifferent | 30-90 min Setup, danach laufend | 1-3 h | 30-90 min | 30-90 min |
Participantsdifferent | 1-8 | 4-10 | 3-12 | 3-12 |
Formatdifferent | Workshop + async | Workshop | Workshop | Workshop |
Outputdifferent | Forecast Percentiles, Throughput Dataset, Risk Communication | Current-state map, Future-state map, Bottleneck list | Bucketed Backlog, Relative Estimates, Split Candidates | Affinity Size Map, Grouped Estimates, Unclear Items |
Tagsno overlap | ForecastingFlowDelivery | LeanFlowWasteDelivery | EstimationBacklogRelative sizing | EstimationBacklogRelative sizing |