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| Criterion |  Delivery Monte Carlo Forecasting |  Agile NoEstimates |  Knowledge Modeling Knowledge Mapping |  Facilitation Dot Estimation |
|---|---|---|---|---|
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. | 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. | 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 size or effort can only be estimated roughly, Dot Estimation condenses the group's experience into a quick range. It turns individual contributions into a visible selection. The result is captured as an Effort Heatmap, Risk Signals, and Discussion Targets. |
Complexitydifferent | High | Medium | Medium | Low |
Timedifferent | 30-90 min Setup, danach laufend | laufend | 1-3 h | 5-20 min |
Participantsdifferent | 1-8 | 2-12 | 3-12 | 3-20 |
Formatdifferent | Workshop + async | Workshop + async | Workshop | Workshop |
Outputdifferent | Forecast Percentiles, Throughput Dataset, Risk Communication | Throughput Data, Flow Forecast, Slicing Rules | Knowledge Map, Critical Knowledge Areas, Transfer Plan | Effort Heatmap, Risk Signals, Discussion Targets |
Tagsno overlap | ForecastingFlowDelivery | EstimationForecastingFlow | KnowledgeMappingRisk | EstimationEffortRisk |