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| Criterion | ![]() Knowledge Modeling Knowledge Mapping | ![]() Agile NoEstimates | ![]() Knowledge Modeling Concept Mapping | ![]() Delivery Monte Carlo Forecasting |
|---|---|---|---|---|
Purposedifferent | Knowledge Mapping makes knowledge, gaps, and transfer paths visible across a field. It fits when expertise should not just exist but also be findable and transferable. | When estimating slows a team down more than it helps, it shifts the focus to flow, small slices, and real lead time. It sorts work by value, risk, and delivery ability. The result is captured as Throughput Data, Flow Forecast, and Slicing Rules. | 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. | 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. |
Complexitydifferent | Medium | Medium | Medium | High |
Timedifferent | 1-3 h | laufend | 1-2 h | 30-90 min Setup, danach laufend |
Participantsdifferent | 3-12 | 2-12 | 1-8 | 1-8 |
Formatdifferent | Workshop | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Knowledge Map, Critical Knowledge Areas, Transfer Plan | Throughput Data, Flow Forecast, Slicing Rules | Concept Map, Relationship Labels, Knowledge Gaps | Forecast Percentiles, Throughput Dataset, Risk Communication |
Tagsno overlap | KnowledgeMappingRisk | EstimationForecastingFlow | KnowledgeConceptsMappingSensemaking | ForecastingFlowDelivery |



