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Criterion
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Paper illustration for Three-Point Estimation.
Decision Making
Three-Point Estimation
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
Helps clarify scope, sequence, and delivery flow in concrete terms. It makes work, boundaries, and order steerable. The result is captured as Forecast Percentiles, Throughput Dataset, and Risk Communication.A single estimate for effort, time, or risk often looks too smooth for the real uncertainty behind it. It separates options, evaluation criteria, and open risks. The result is captured as a Three-Point Estimate, Risk Range, and Assumption 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 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
HighMediumLowHigh
Timedifferent
30-90 min Setup, danach laufend10-30 min je Item1-2 h1-4 Wochen
Participantsdifferent
1-81-82-86-30 Experten
Formatdifferent
Workshop + asyncWorkshop + asyncWorkshop + asyncAsync
Outputdifferent
Forecast Percentiles, Throughput Dataset, Risk CommunicationThree-Point Estimate, Risk Range, Assumption NotesDIBB document, Belief list, Bet list, Learning reportExpert Forecast, Consensus Range, Assumption Notes
Tagsno overlap
ForecastingFlowDelivery
EstimationUncertaintyForecasting
StrategyDecisionAssumptionsHypothesis
ForecastingExpertsDecisionStrategy
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