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Criterion
Anonymous individual judgments pass through feedback loops to form a distribution.
Decision Making
Delphi Method
Paper illustration for Wideband Delphi.
Decision Making
Wideband Delphi
Paper illustration of DIBB with its method-specific working model.
Product Strategy
DIBB
Paper illustration for NoEstimates.
Agile
NoEstimates
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.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.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 estimating slows a team down more than it helps, it shifts the focus to flow, small slices, and real lead time. It sorts work by value, risk, and delivery ability. The result is captured as Throughput Data, Flow Forecast, and Slicing Rules.
Complexitydifferent
HighHighLowMedium
Timedifferent
1-4 Wochen1-4 h or multiple rounds1-2 hlaufend
Participantsdifferent
6-30 Experten4-12 Experten2-82-12
Formatdifferent
AsyncWorkshop + asyncWorkshop + asyncWorkshop + async
Outputdifferent
Expert Forecast, Consensus Range, Assumption NotesEstimate Range, Assumption Log, Expert Consensus NotesDIBB document, Belief list, Bet list, Learning reportThroughput Data, Flow Forecast, Slicing Rules
Tagsno overlap
ForecastingExpertsDecisionStrategy
EstimationExpertsForecasting
StrategyDecisionAssumptionsHypothesis
EstimationForecastingFlow
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