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Criterion
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
Decision Tree method illustration showing its working structure
Decision Making
Decision Tree
Paper illustration for OODA Loop.
Decision Making
OODA Loop
Purposedifferent
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.For decisions with follow-on paths and dependencies, a linear comparison is often not enough. A Decision Tree shows how options branch under conditions and which consequences hang on each branch.In dynamic situations, decisions become outdated faster than they can be prepared.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.
Complexitydifferent
LowHighMediumMedium
Timedifferent
1-2 h1-4 Wochen30-90 min15-60 min je Zyklus
Participantsdifferent
2-86-30 Experten1-61-8
Formatdifferent
Workshop + asyncAsyncWorkshop + asyncWorkshop + async
Outputdifferent
DIBB document, Belief list, Bet list, Learning reportExpert Forecast, Consensus Range, Assumption NotesDecision Tree, Option Map, Assumption ListSituation Assessment, Decision Loop, Action Updates
Tags1 shared
StrategyDecisionAssumptionsHypothesis
ForecastingExpertsDecisionStrategy
DecisionTreeOptions
DecisionChangeLearningStrategy
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