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Criterion
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Paper illustration for Wideband Delphi.
Decision Making
Wideband Delphi
Anonymous individual judgments pass through feedback loops to form a distribution.
Decision Making
Delphi Method
Paper illustration of DIBB with its method-specific working model.
Product Strategy
DIBB
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 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.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.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.
Complexitydifferent
HighHighHighLow
Timedifferent
30-90 min Setup, danach laufend1-4 h or multiple rounds1-4 Wochen1-2 h
Participantsdifferent
1-84-12 Experten6-30 Experten2-8
Formatdifferent
Workshop + asyncWorkshop + asyncAsyncWorkshop + async
Outputdifferent
Forecast Percentiles, Throughput Dataset, Risk CommunicationEstimate Range, Assumption Log, Expert Consensus NotesExpert Forecast, Consensus Range, Assumption NotesDIBB document, Belief list, Bet list, Learning report
Tagsno overlap
ForecastingFlowDelivery
EstimationExpertsForecasting
ForecastingExpertsDecisionStrategy
StrategyDecisionAssumptionsHypothesis
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