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| Criterion |  Decision Making Wideband Delphi |  Delivery Monte Carlo Forecasting |  Product Discovery Dual-Track Agile |  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 uncertainty and delivery run in parallel, it separates learning work from implementation while keeping both connected. It prevents unvalidated ideas from falling directly into the delivery stream. | 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 | Laufend, Wochen bis Monate | Ongoing |
Participantsdifferent | 4-12 Experten | 1-8 | 4-10 | 2-12 |
Formatsame | Workshop + async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Estimate Range, Assumption Log, Expert Consensus Notes | Forecast Percentiles, Throughput Dataset, Risk Communication | Discovery Backlog, Delivery Backlog, Experiment-Ergebnisse, Validierte Stories | Kanban board, WIP policies, Flow metrics |
Tagsno overlap | EstimationExpertsForecasting | ForecastingFlowDelivery | AgileDiscoveryDelivery | FlowVisual managementDelivery |