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Criterion
Anonymous individual judgments pass through feedback loops to form a distribution.
Decision Making
Delphi Method
Paper illustration for Current Reality Tree
Systems Thinking
Current Reality Tree
Paper illustration of DIBB with its method-specific working model.
Product Strategy
DIBB
Causal Loop Diagram workspace showing the question, observations, and next decision.
Systems Thinking
Causal Loop Diagram
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.A Current Reality Tree condenses many symptoms into a few causal chains. The method makes visible which core problems drive several negative effects at once.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.A Causal Loop Diagram makes feedback, reinforcement, and balance in a system legible. It uncovers side effects and self-reinforcement that stay hidden in linear explanations.
Complexitydifferent
HighHighLowMedium
Timedifferent
1-4 Wochen2-6 h1-2 h1-3 h
Participantsdifferent
6-30 Experten3-82-82-8
Formatdifferent
AsyncWorkshopWorkshop + asyncWorkshop
Outputdifferent
Expert Forecast, Consensus Range, Assumption NotesCurrent Reality Tree, Core Problems, Intervention IdeasDIBB document, Belief list, Bet list, Learning reportCausal Loop Diagram, Feedback Notes, Leverage Points
Tagsno overlap
ForecastingExpertsDecisionStrategy
Systems thinkingRoot causeConstraintsCausality
StrategyDecisionAssumptionsHypothesis
FeedbackSystems thinkingCausalityDynamics
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