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Criterion
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Paper illustration for OODA Loop.
Decision Making
OODA Loop
Paper illustration of DIBB with its method-specific working model.
Product Strategy
DIBB
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is captured as Forecast Percentiles, Throughput Dataset, and Risk Communication.In dynamic situations, decisions become outdated faster than they can be prepared.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.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
HighMediumLow
Timedifferent
30-90 min Setup, danach laufend15-60 min je Zyklus1-2 h
Participantsdifferent
1-81-82-8
Formatsame
Workshop + asyncWorkshop + asyncWorkshop + async
Outputdifferent
Forecast Percentiles, Throughput Dataset, Risk CommunicationSituation Assessment, Decision Loop, Action UpdatesDIBB document, Belief list, Bet list, Learning report
Tagsno overlap
ForecastingFlowDelivery
DecisionChangeLearningStrategy
StrategyDecisionAssumptionsHypothesis
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Anonymous individual judgments pass through feedback loops to form a distribution.
Decision Making
Delphi Method
Paper illustration of the Force Field Analysis working structure.
Decision Making
Force Field Analysis
Paper illustration of an assumption matrix with prioritized test cards
Decision Making
Assumption Surfacing
Paper illustration of Cost of Delay with its method-specific working model.
Delivery
Cost of Delay