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Criterion
Decision Tree method illustration showing its working structure
Decision Making
Decision Tree
Paper illustration of an assumption matrix with prioritized test cards
Decision Making
Assumption Surfacing
Paper illustration of two people facing each other, speech bubbles and an open interview notebook.
UX Research
User Interviews
Paper illustration of DIBB with its method-specific working model.
Product Strategy
DIBB
Purposedifferent
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.Plans often contain assumptions that were never openly stated and remain dangerous precisely because of that. Assumption Surfacing makes these silent premises visible and prioritizes which of them carry the initiative or could sink it.When teams derive needs only from assumptions and real motives are missing, user interviews give direct access to behavior and meaning. Conversations from the target group's everyday life make patterns, tensions, and open questions solidly visible.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
MediumLowLowLow
Timedifferent
30-90 min45-90 min30–60 min per interview1-2 h
Participantsdifferent
1-62-81 participant per interview2-8
Formatsame
Workshop + asyncWorkshop + asyncWorkshop + asyncWorkshop + async
Outputdifferent
Decision Tree, Option Map, Assumption ListAssumption List, Critical Assumptions, Learning PlanInterview Notes, Themes, Insight SummaryDIBB document, Belief list, Bet list, Learning report
Tagsno overlap
DecisionTreeOptions
AssumptionsRiskDecisionDiscovery
QualitativeResearchCustomerDiscovery
StrategyDecisionAssumptionsHypothesis
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