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Criterion
A paper-based illustration representing Domain Storytelling with its core stages and visible working result.
Knowledge Modeling
Domain Storytelling
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 DIBB with its method-specific working model.
Product Strategy
DIBB
Purposedifferent
Domain Storytelling translates domain knowledge into a shared narrative of actors, objects, and workflows. It is especially useful when language, rules, and process understanding must be tightly connected.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.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
LowMediumLowLow
Timedifferent
1-2 h30-90 min45-90 min1-2 h
Participantsdifferent
2-81-62-82-8
Formatdifferent
WorkshopWorkshop + asyncWorkshop + asyncWorkshop + async
Outputdifferent
Domain Story, Glossary Notes, Process NarrativeDecision Tree, Option Map, Assumption ListAssumption List, Critical Assumptions, Learning PlanDIBB document, Belief list, Bet list, Learning report
Tagsno overlap
KnowledgeDomain-Driven DesignProcess
DecisionTreeOptions
AssumptionsRiskDecisionDiscovery
StrategyDecisionAssumptionsHypothesis
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