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Criterion
Anonymous individual judgments pass through feedback loops to form a distribution.
Decision Making
Delphi Method
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration for Bucket System.
Agile
Bucket System
Paper illustration for Affinity Estimation.
Agile
Affinity Estimation
Purposedifferent
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.When two variants compete, discussions quickly decide by taste rather than effect. A/B Testing checks behavior under controlled conditions and separates real improvement from chance or expectation effects.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 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.
Complexitydifferent
HighHighMediumMedium
Timedifferent
1-4 Wochen1-4 Wochen30-90 min30-90 min
Participantsdifferent
6-30 Experten1-63-123-12
Formatdifferent
AsyncAsyncWorkshopWorkshop
Outputdifferent
Expert Forecast, Consensus Range, Assumption NotesExperiment results, Decision log, Learning summaryBucketed Backlog, Relative Estimates, Split CandidatesAffinity Size Map, Grouped Estimates, Unclear Items
Tagsno overlap
ForecastingExpertsDecisionStrategy
ExperimentsGrowthAnalyticsValidation
EstimationBacklogRelative sizing
EstimationBacklogRelative sizing
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