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| Criterion |  Delivery Monte Carlo Forecasting |  Agile Affinity Estimation |  Decision Making Wideband Delphi |  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 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. | A single opinion rarely holds up for planning when the future is genuinely uncertain. It separates options, evaluation criteria, and open risks. The result is captured as an Estimate Range, Assumption Log, and Expert Consensus Notes. | 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 | High | Medium |
Timedifferent | 30-90 min Setup, danach laufend | 30-90 min | 1-4 h or multiple rounds | Ongoing |
Participantsdifferent | 1-8 | 3-12 | 4-12 Experten | 2-12 |
Formatdifferent | Workshop + async | Workshop | Workshop + async | Workshop + async |
Outputdifferent | Forecast Percentiles, Throughput Dataset, Risk Communication | Affinity Size Map, Grouped Estimates, Unclear Items | Estimate Range, Assumption Log, Expert Consensus Notes | Kanban board, WIP policies, Flow metrics |
Tagsno overlap | ForecastingFlowDelivery | EstimationBacklogRelative sizing | EstimationExpertsForecasting | FlowVisual managementDelivery |