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Criterion
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Paper illustration of DIBB with its method-specific working model.
Product Strategy
DIBB
Paper illustration for OODA Loop.
Decision Making
OODA Loop
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.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captures results as a DIBB document, belief list, bet list, and learning report.In dynamic situations, decisions become outdated faster than they can be prepared. The OODA Loop holds observing, orienting, deciding, and acting together as a recurring rhythm so reaction does not slide into inertia.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
HighLowMediumHigh
Timedifferent
30-90 min Setup, danach laufend1-2 h15-60 min je Zyklus1-4 Wochen
Participantsdifferent
1-82-81-86-30 Experten
Formatdifferent
Workshop + asyncWorkshop + asyncWorkshop + asyncAsync
Outputdifferent
Forecast Percentiles, Throughput Dataset, Risk CommunicationDIBB document, Belief list, Bet list, Learning reportSituation Assessment, Decision Loop, Action UpdatesExpert Forecast, Consensus Range, Assumption Notes
Tagsno overlap
ForecastingFlowDelivery
StrategyDecisionAssumptionsHypothesis
DecisionChangeLearningStrategy
ForecastingExpertsDecisionStrategy
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