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Criterion
Paper illustration for Future Reality Tree.
Systems Thinking
Future Reality Tree
Anonymous individual judgments pass through feedback loops to form a distribution.
Decision Making
Delphi Method
Paper illustration for Wideband Delphi.
Decision Making
Wideband Delphi
Paper illustration of DIBB with its method-specific working model.
Product Strategy
DIBB
Purposedifferent
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.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 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.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
2-4 h1-4 Wochen1-4 h or multiple rounds1-2 h
Participantsdifferent
3-86-30 Experten4-12 Experten2-8
Formatdifferent
WorkshopAsyncWorkshop + asyncWorkshop + async
Outputdifferent
Future Reality Tree, Negative Branches, Assumption List, Improved InjectionsExpert Forecast, Consensus Range, Assumption NotesEstimate Range, Assumption Log, Expert Consensus NotesDIBB document, Belief list, Bet list, Learning report
Tagsno overlap
Theory of ConstraintsSystems thinkingChange
ForecastingExpertsDecisionStrategy
EstimationExpertsForecasting
StrategyDecisionAssumptionsHypothesis
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