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Criterion
Anonymous individual judgments pass through feedback loops to form a distribution.
Decision Making
Delphi Method
Paper illustration of Leverage Points with its method-specific working model.
Systems Thinking
Leverage Points
Paper illustration for Future Reality Tree.
Systems Thinking
Future Reality Tree
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.Leverage Points show exactly where interventions in a system produce a disproportionate effect. It draws relationships, patterns, and feedback loops. The result is captured as a leverage map and action strategy.A Future Reality Tree shows how desired actions are meant to lead to a better system state. The method checks whether a path of change holds together logically before time flows into implementation.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
HighHighHighLow
Timedifferent
1-4 WochenHalf day2-4 h1-2 h
Participantsdifferent
6-30 Experten3-123-82-8
Formatdifferent
AsyncWorkshopWorkshopWorkshop + async
Outputdifferent
Expert Forecast, Consensus Range, Assumption NotesLeverage Map, Action StrategyFuture Reality Tree, Negative Branches, Assumption List, Improved InjectionsDIBB document, Belief list, Bet list, Learning report
Tagsno overlap
ForecastingExpertsDecisionStrategy
Systems thinkingChangeStrategy
Theory of ConstraintsSystems thinkingChange
StrategyDecisionAssumptionsHypothesis
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