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Criterion
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Paper illustration of a calibrated five-by-five risk matrix with response cards.
Decision Making
Risk Matrix
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.When a project faces many possible disruptions, it quickly becomes unclear which risks deserve attention first. It separates options, evaluation criteria, and open risks. The result is captured as a Risk Matrix and a Top Risk List.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
HighLowHighLow
Timedifferent
30-90 min Setup, danach laufend30-60 min1-4 Wochen1-2 h
Participantsdifferent
1-83-106-30 Experten2-8
Formatdifferent
Workshop + asyncWorkshop + asyncAsyncWorkshop + async
Outputdifferent
Forecast Percentiles, Throughput Dataset, Risk CommunicationRisk Matrix, Top Risk ListExpert Forecast, Consensus Range, Assumption NotesDIBB document, Belief list, Bet list, Learning report
Tagsno overlap
ForecastingFlowDelivery
RiskDecisionPrioritizationAssessment
ForecastingExpertsDecisionStrategy
StrategyDecisionAssumptionsHypothesis
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