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Criterion
Paper illustration for Planning Poker.
Agile
Planning Poker
Decision Tree method illustration showing its working structure
Decision Making
Decision Tree
Paper illustration for Constraint Analysis.
Decision Making
Constraint Analysis
Paper illustration for Affinity Estimation.
Agile
Affinity Estimation
Purposedifferent
When estimates within the team diverge too much, it puts differing expectations on a common test bench. It separates rough complexity from unspoken assumptions.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 an initiative stalls, the limit often lies not in the idea but in hard or soft boundary conditions. Constraint Analysis separates these limits and shows which of them can actually be shaped.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.
Complexitydifferent
LowMediumLowMedium
Timedifferent
2-5 min je Item30-90 min30-90 min30-90 min
Participantsdifferent
3-91-62-83-12
Formatdifferent
Workshop + asyncWorkshop + asyncWorkshop + asyncWorkshop
Outputdifferent
Relative Estimates, Assumption Notes, Split CandidatesDecision Tree, Option Map, Assumption ListConstraint List, Hard/Soft Classification, Option Impact Notes, Decision BoundariesAffinity Size Map, Grouped Estimates, Unclear Items
Tagsno overlap
EstimationAgileRelative sizingTeam
DecisionTreeOptions
ConstraintsDecisionPlanningOptions
EstimationBacklogRelative sizing
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