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Criterion
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Paper illustration of a branching impact map with a Why goal at the root, actor circles, How behavior changes and What options.
Product Strategy
Impact 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 a goal needs to be connected to several possible paths, it shows chains of impact instead of feature lists. It connects business goal, behavior change, and measures.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 laufend45-90 min1-2 h1-4 Wochen
Participantsdifferent
1-83-82-86-30 Experten
Formatdifferent
Workshop + asyncWorkshopWorkshop + asyncAsync
Outputdifferent
Forecast Percentiles, Throughput Dataset, Risk CommunicationImpact Map, Outcome Hypotheses, Delivery OptionsDIBB document, Belief list, Bet list, Learning reportExpert Forecast, Consensus Range, Assumption Notes
Tagsno overlap
ForecastingFlowDelivery
OutcomesStrategyBehaviorPlanning
StrategyDecisionAssumptionsHypothesis
ForecastingExpertsDecisionStrategy
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