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Criterion
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Paper illustration of a calm four-quadrant Assumption Map with hypothesis cards and emphasis on important assumptions with little evidence.
Product Discovery
Assumption Mapping
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.When assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first.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 laufend45-60 min1-2 h1-4 Wochen
Participantsdifferent
1-82-82-86-30 Experten
Formatdifferent
Workshop + asyncWorkshop + asyncWorkshop + asyncAsync
Outputdifferent
Forecast Percentiles, Throughput Dataset, Risk CommunicationAssumption map, Test backlog, Risk rankingDIBB document, Belief list, Bet list, Learning reportExpert Forecast, Consensus Range, Assumption Notes
Tagsno overlap
ForecastingFlowDelivery
AssumptionsRiskExperimentsValidation
StrategyDecisionAssumptionsHypothesis
ForecastingExpertsDecisionStrategy
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