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Criterion
Scenario Planning method illustration showing its working structure
Business Strategy
Scenario Planning
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
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
Scenario Planning opens the view to several plausible futures instead of a single forecast. The method protects strategies from depending on too narrow an expected path.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 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
0.5-2 Tage30-90 min Setup, danach laufend1-4 Wochen1-2 h
Participantsdifferent
4-121-86-30 Experten2-8
Formatdifferent
WorkshopWorkshop + asyncAsyncWorkshop + async
Outputdifferent
Scenario Set, Strategic Implications, Robust OptionsForecast Percentiles, Throughput Dataset, Risk CommunicationExpert Forecast, Consensus Range, Assumption NotesDIBB document, Belief list, Bet list, Learning report
Tagsno overlap
StrategyUncertaintyPlanning
ForecastingFlowDelivery
ForecastingExpertsDecisionStrategy
StrategyDecisionAssumptionsHypothesis
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