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Criterion
Paper illustration for Constraint Analysis.
Decision Making
Constraint Analysis
Paper illustration for Bucket System.
Agile
Bucket System
Paper illustration for Planning Poker.
Agile
Planning Poker
Decision Tree method illustration showing its working structure
Decision Making
Decision Tree
Purposedifferent
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 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.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.
Complexitydifferent
LowMediumLowMedium
Timedifferent
30-90 min30-90 min2-5 min je Item30-90 min
Participantsdifferent
2-83-123-91-6
Formatdifferent
Workshop + asyncWorkshopWorkshop + asyncWorkshop + async
Outputdifferent
Constraint List, Hard/Soft Classification, Option Impact Notes, Decision BoundariesBucketed Backlog, Relative Estimates, Split CandidatesRelative Estimates, Assumption Notes, Split CandidatesDecision Tree, Option Map, Assumption List
Tagsno overlap
ConstraintsDecisionPlanningOptions
EstimationBacklogRelative sizing
EstimationAgileRelative sizingTeam
DecisionTreeOptions
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