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Criterion
Paper illustration for Planning Poker.
Agile
Planning Poker
Paper illustration of DIBB with its method-specific working model.
Product Strategy
DIBB
Paper illustration for Wideband Delphi.
Decision Making
Wideband Delphi
Paper illustration for Bucket System.
Agile
Bucket System
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.DIBB helps clarify target groups, value, goals, and priorities by making the logic behind a decision explicit. It captures results as a DIBB document, belief list, bet list, and learning report.A single opinion rarely holds up for planning when the future is genuinely uncertain. It separates options, evaluation criteria, and open risks. The result is captured as an Estimate Range, Assumption Log, and Expert Consensus Notes.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.
Complexitydifferent
LowLowHighMedium
Timedifferent
2-5 min je Item1-2 h1-4 h or multiple rounds30-90 min
Participantsdifferent
3-92-84-12 Experten3-12
Formatdifferent
Workshop + asyncWorkshop + asyncWorkshop + asyncWorkshop
Outputdifferent
Relative Estimates, Assumption Notes, Split CandidatesDIBB document, Belief list, Bet list, Learning reportEstimate Range, Assumption Log, Expert Consensus NotesBucketed Backlog, Relative Estimates, Split Candidates
Tagsno overlap
EstimationAgileRelative sizingTeam
StrategyDecisionAssumptionsHypothesis
EstimationExpertsForecasting
EstimationBacklogRelative sizing
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