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Criterion
Paper illustration for Affinity Estimation.
Agile
Affinity Estimation
Paper illustration for Bucket System.
Agile
Bucket System
Paper illustration of DIBB with its method-specific working model.
Product Strategy
DIBB
Anonymous individual judgments pass through feedback loops to form a distribution.
Decision Making
Delphi Method
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.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 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
MediumMediumLowHigh
Timedifferent
30-90 min30-90 min1-2 h1-4 Wochen
Participantsdifferent
3-123-122-86-30 Experten
Formatdifferent
WorkshopWorkshopWorkshop + asyncAsync
Outputdifferent
Affinity Size Map, Grouped Estimates, Unclear ItemsBucketed Backlog, Relative Estimates, Split CandidatesDIBB document, Belief list, Bet list, Learning reportExpert Forecast, Consensus Range, Assumption Notes
Tagsno overlap
EstimationBacklogRelative sizing
EstimationBacklogRelative sizing
StrategyDecisionAssumptionsHypothesis
ForecastingExpertsDecisionStrategy
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