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| Criterion |  Delivery Monte Carlo Forecasting |  Decision Making PERT Estimation |  Knowledge Modeling Concept Mapping |
|---|---|---|---|
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. | On complex initiatives, a plain average tends to understate just how uncertain the outcome really is. It separates options, evaluation criteria, and open risks. The result is captured as a PERT Estimate, Expected Value, and Risk Notes. | Concept Mapping arranges terms and relationships in a network that makes subject-matter connections tangible. It fits when a topic needs to be understood structurally rather than linearly. |
Complexitydifferent | High | Medium | Medium |
Timedifferent | 30-90 min Setup, danach laufend | 15-45 min | 1-2 h |
Participantssame | 1-8 | 1-8 | 1-8 |
Formatsame | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Forecast Percentiles, Throughput Dataset, Risk Communication | PERT Estimate, Expected Value, Risk Notes | Concept Map, Relationship Labels, Knowledge Gaps |
Tagsno overlap | ForecastingFlowDelivery | EstimationUncertaintyRisk | KnowledgeConceptsMappingSensemaking |
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