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Criterion
Paper illustration for Affinity Estimation.
Agile
Affinity Estimation
Paper illustration for PERT Estimation.
Decision Making
PERT Estimation
Decision Tree method illustration showing its working structure
Decision Making
Decision Tree
Paper illustration for Dot Estimation.
Facilitation
Dot Estimation
Purposedifferent
When many tasks need to be classified quickly, it sorts them by perceived effort and similarity. It reduces the effort of fine-grained estimation for large volumes.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.For decisions with follow-on paths and dependencies, a linear comparison is often not enough. A Decision Tree shows how options branch under conditions and which consequences hang on each branch.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
MediumMediumMediumLow
Timedifferent
30-90 min15-45 min30-90 min5-20 min
Participantsdifferent
3-121-81-63-20
Formatdifferent
WorkshopWorkshop + asyncWorkshop + asyncWorkshop
Outputdifferent
Affinity Size Map, Grouped Estimates, Unclear ItemsPERT Estimate, Expected Value, Risk NotesDecision Tree, Option Map, Assumption ListEffort Heatmap, Risk Signals, Discussion Targets
Tagsno overlap
EstimationBacklogRelative sizing
EstimationUncertaintyRisk
DecisionTreeOptions
EstimationEffortRisk
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