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| Criterion |  Knowledge Modeling PARA Method |  Decision Making Wideband Delphi |  Delivery Monte Carlo Forecasting |  Engineering Kanban |
|---|---|---|---|---|
Purposedifferent | The PARA Method organizes knowledge into Projects, Areas, Resources, and Archives. It creates order when digital notes, files, and tasks no longer cleanly fit current work. | 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 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 | Medium | High | High | Medium |
Timedifferent | 1-3 h Setup, laufend | 1-4 h or multiple rounds | 30-90 min Setup, danach laufend | Ongoing |
Participantsdifferent | 1 | 4-12 Experten | 1-8 | 2-12 |
Formatdifferent | Async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | PARA Structure, Project Notes, Knowledge Archive | Estimate Range, Assumption Log, Expert Consensus Notes | Forecast Percentiles, Throughput Dataset, Risk Communication | Kanban board, WIP policies, Flow metrics |
Tagsno overlap | KnowledgeProductivityOrganization | EstimationExpertsForecasting | ForecastingFlowDelivery | FlowVisual managementDelivery |