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Criterion
Paper illustration for Cynefin Workshop.
Decision Making
Cynefin Workshop
Decision Tree method illustration showing its working structure
Decision Making
Decision Tree
Anonymous individual judgments pass through feedback loops to form a distribution.
Decision Making
Delphi Method
Paper illustration of DIBB with its method-specific working model.
Product Strategy
DIBB
Purposedifferent
When problems are unclear, chaotic, or only seemingly familiar, standard recipes fall short. A Cynefin Workshop sorts situations by the nature of their problem and connects them with matching action logic.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.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.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
MediumMediumHighLow
Timedifferent
60-180 min30-90 min1-4 Wochen1-2 h
Participantsdifferent
4-201-66-30 Experten2-8
Formatdifferent
WorkshopWorkshop + asyncAsyncWorkshop + async
Outputdifferent
Cynefin Map, Domain-specific Actions, Sensemaking NotesDecision Tree, Option Map, Assumption ListExpert Forecast, Consensus Range, Assumption NotesDIBB document, Belief list, Bet list, Learning report
Tags1 shared
ComplexitySensemakingDecision
DecisionTreeOptions
ForecastingExpertsDecisionStrategy
StrategyDecisionAssumptionsHypothesis
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