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| Criterion |  Decision Making Wideband Delphi |  Delivery Monte Carlo Forecasting |  Agile Bucket System |  Engineering Kanban |
|---|---|---|---|---|
Purposedifferent | 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. | 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 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 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 | High | Medium | Medium |
Timedifferent | 1-4 h or multiple rounds | 30-90 min Setup, danach laufend | 30-90 min | Ongoing |
Participantsdifferent | 4-12 Experten | 1-8 | 3-12 | 2-12 |
Formatdifferent | Workshop + async | Workshop + async | Workshop | Workshop + async |
Outputdifferent | Estimate Range, Assumption Log, Expert Consensus Notes | Forecast Percentiles, Throughput Dataset, Risk Communication | Bucketed Backlog, Relative Estimates, Split Candidates | Kanban board, WIP policies, Flow metrics |
Tagsno overlap | EstimationExpertsForecasting | ForecastingFlowDelivery | EstimationBacklogRelative sizing | FlowVisual managementDelivery |