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Criterion
Paper illustration for PERT Estimation.
Decision Making
PERT Estimation
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Paper illustration for Knowledge Mapping.
Knowledge Modeling
Knowledge Mapping
Purposedifferent
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.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.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
MediumHighMedium
Timedifferent
15-45 min30-90 min Setup, danach laufend1-3 h
Participantsdifferent
1-81-83-12
Formatdifferent
Workshop + asyncWorkshop + asyncWorkshop
Outputdifferent
PERT Estimate, Expected Value, Risk NotesForecast Percentiles, Throughput Dataset, Risk CommunicationKnowledge Map, Critical Knowledge Areas, Transfer Plan
Tagsno overlap
EstimationUncertaintyRisk
ForecastingFlowDelivery
KnowledgeMappingRisk
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Often compared together

Methods with strong topical overlap with the current selection, not yet in the comparison.

Paper illustration for Three-Point Estimation.
Decision Making
Three-Point Estimation
Paper illustration of a Concept Map with concepts and labelled links
Knowledge Modeling
Concept Mapping
Paper illustration for Dot Estimation.
Facilitation
Dot Estimation