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Criterion
Paper illustration for Wideband Delphi.
Decision Making
Wideband Delphi
Paper illustration for Future Reality Tree.
Systems Thinking
Future Reality Tree
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
Purposedifferent
A single opinion rarely holds up for planning when the future is genuinely uncertain. It separates options, evaluation criteria, and open risks. The result is captured as an Estimate Range, Assumption Log, and Expert Consensus Notes.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.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.
Complexitydifferent
HighHighLowHigh
Timedifferent
1-4 h or multiple rounds2-4 h1-2 h1-4 Wochen
Participantsdifferent
4-12 Experten3-82-86-30 Experten
Formatdifferent
Workshop + asyncWorkshopWorkshop + asyncAsync
Outputdifferent
Estimate Range, Assumption Log, Expert Consensus NotesFuture Reality Tree, Negative Branches, Assumption List, Improved InjectionsDIBB document, Belief list, Bet list, Learning reportExpert Forecast, Consensus Range, Assumption Notes
Tagsno overlap
EstimationExpertsForecasting
Theory of ConstraintsSystems thinkingChange
StrategyDecisionAssumptionsHypothesis
ForecastingExpertsDecisionStrategy
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