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Criterion
Paper illustration for Affinity Estimation.
Agile
Affinity Estimation
Paper illustration for Bucket System.
Agile
Bucket System
Decision Tree method illustration showing its working structure
Decision Making
Decision Tree
Paper illustration for Planning Poker.
Agile
Planning Poker
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.When a large batch of work needs a fast, rough estimate, it sorts items into predefined size buckets. It sorts work by value, risk, and delivery ability. The result is captured as a Bucketed Backlog, Relative Estimates, and Split Candidates.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 estimates within the team diverge too much, it puts differing expectations on a common test bench. It separates rough complexity from unspoken assumptions.
Complexitydifferent
MediumMediumMediumLow
Timedifferent
30-90 min30-90 min30-90 min2-5 min je Item
Participantsdifferent
3-123-121-63-9
Formatdifferent
WorkshopWorkshopWorkshop + asyncWorkshop + async
Outputdifferent
Affinity Size Map, Grouped Estimates, Unclear ItemsBucketed Backlog, Relative Estimates, Split CandidatesDecision Tree, Option Map, Assumption ListRelative Estimates, Assumption Notes, Split Candidates
Tagsno overlap
EstimationBacklogRelative sizing
EstimationBacklogRelative sizing
DecisionTreeOptions
EstimationAgileRelative sizingTeam
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