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Criterion
Paper illustration of DIBB with its method-specific working model.
Product Strategy
DIBB
Paper illustration for Bucket System.
Agile
Bucket System
Anonymous individual judgments pass through feedback loops to form a distribution.
Decision Making
Delphi Method
Purposedifferent
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.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 knowledge is distributed and direct dominance should be avoided, groups quickly fall under the sway of their opinion leaders. The Delphi Method gathers assessments iteratively and gradually brings expert judgments closer together.
Complexitydifferent
LowMediumHigh
Timedifferent
1-2 h30-90 min1-4 Wochen
Participantsdifferent
2-83-126-30 Experten
Formatdifferent
Workshop + asyncWorkshopAsync
Outputdifferent
DIBB document, Belief list, Bet list, Learning reportBucketed Backlog, Relative Estimates, Split CandidatesExpert Forecast, Consensus Range, Assumption Notes
Tagsno overlap
StrategyDecisionAssumptionsHypothesis
EstimationBacklogRelative sizing
ForecastingExpertsDecisionStrategy
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Methods with strong topical overlap with the current selection, not yet in the comparison.

Paper illustration for Affinity Estimation.
Agile
Affinity Estimation
Paper illustration for Wideband Delphi.
Decision Making
Wideband Delphi
Paper illustration of an assumption matrix with prioritized test cards
Decision Making
Assumption Surfacing
Paper illustration of the Force Field Analysis working structure.
Decision Making
Force Field Analysis