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Criterion
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Paper illustration for Dot Estimation.
Facilitation
Dot Estimation
Paper illustration for Knowledge Mapping.
Knowledge Modeling
Knowledge 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.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.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.
Complexitydifferent
HighLowMedium
Timedifferent
30-90 min Setup, danach laufend5-20 min1-3 h
Participantsdifferent
1-83-203-12
Formatdifferent
Workshop + asyncWorkshopWorkshop
Outputdifferent
Forecast Percentiles, Throughput Dataset, Risk CommunicationEffort Heatmap, Risk Signals, Discussion TargetsKnowledge Map, Critical Knowledge Areas, Transfer Plan
Tagsno overlap
ForecastingFlowDelivery
EstimationEffortRisk
KnowledgeMappingRisk
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Paper illustration of a Concept Map with concepts and labelled links
Knowledge Modeling
Concept Mapping