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Criterion
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 Trade-off Analysis.
Decision Making
Trade-off Analysis
Paper illustration of DIBB with its method-specific working model.
Product Strategy
DIBB
Purposedifferent
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.With limited resources, quality, speed, cost, and risk almost always compete with each other. Trade-off Analysis makes these tensions explicit and prevents decisions from producing hidden side effects.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
HighMediumMediumLow
Timedifferent
1-4 Wochen30-90 min45-120 min1-2 h
Participantsdifferent
6-30 Experten1-62-82-8
Formatdifferent
AsyncWorkshop + asyncWorkshop + asyncWorkshop + async
Outputdifferent
Expert Forecast, Consensus Range, Assumption NotesDecision Tree, Option Map, Assumption ListTrade-off Matrix, Criteria List, Decision Rationale, Accepted DownsidesDIBB document, Belief list, Bet list, Learning report
Tags1 shared
ForecastingExpertsDecisionStrategy
DecisionTreeOptions
TradeoffsDecisionCriteriaOptions
StrategyDecisionAssumptionsHypothesis
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