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Criterion
Paper illustration of Leverage Points with its method-specific working model.
Systems Thinking
Leverage Points
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 of DIBB with its method-specific working model.
Product Strategy
DIBB
Purposedifferent
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.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.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
HighHighMediumLow
Timedifferent
Half day1-4 Wochen30-90 min1-2 h
Participantsdifferent
3-126-30 Experten1-62-8
Formatdifferent
WorkshopAsyncWorkshop + asyncWorkshop + async
Outputdifferent
Leverage Map, Action StrategyExpert Forecast, Consensus Range, Assumption NotesDecision Tree, Option Map, Assumption ListDIBB document, Belief list, Bet list, Learning report
Tagsno overlap
Systems thinkingChangeStrategy
ForecastingExpertsDecisionStrategy
DecisionTreeOptions
StrategyDecisionAssumptionsHypothesis
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