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Criterion
Anonymous individual judgments pass through feedback loops to form a distribution.
Decision Making
Delphi Method
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Paper illustration of ICE Scoring with its method-specific working model.
Product Strategy
ICE Scoring
Paper illustration of DIBB with its method-specific working model.
Product Strategy
DIBB
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.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 ideas need sorting quickly, it condenses impact, confidence, and effort into one compact score. It connects customer value, product logic, and decision priorities. The result is captured as an ICE table and top-ideas list.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
HighHighLowLow
Timedifferent
1-4 Wochen30-90 min Setup, danach laufend30-60 min1-2 h
Participantsdifferent
6-30 Experten1-82-82-8
Formatdifferent
AsyncWorkshop + asyncWorkshop + asyncWorkshop + async
Outputdifferent
Expert Forecast, Consensus Range, Assumption NotesForecast Percentiles, Throughput Dataset, Risk CommunicationICE Table, Top Idea ListDIBB document, Belief list, Bet list, Learning report
Tagsno overlap
ForecastingExpertsDecisionStrategy
ForecastingFlowDelivery
PrioritizationScoringGrowthDecision
StrategyDecisionAssumptionsHypothesis
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