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Criterion
Decision Tree method illustration showing its working structure
Decision Making
Decision Tree
A hypothetical failure makes concrete risks, signals, and fitting mitigations visible.
Decision Making
Pre-Mortem
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration of MVP Test Matrix with a method-specific labelled workspace.
Product Discovery
MVP Test Matrix
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.In early initiatives with many uncertainties, planning quickly turns too optimistic. A pre-mortem makes the expected failure visible in advance and sharpens the view of causes, gaps, and countermeasures.When two variants compete, discussions quickly decide by taste rather than effect. A/B Testing checks behavior under controlled conditions and separates real improvement from chance or expectation effects.When several minimal variants compete to answer the same question, it makes comparing and choosing between them cleaner. It separates problem, assumption, solution, and evidence. The result is captured as a Test Matrix and a Test Plan.
Complexitydifferent
MediumLowHighMedium
Timedifferent
30-90 min20–45 min1-4 Wochen45-75 min
Participantsdifferent
1-6Small cross-functional group1-62-8
Formatdifferent
Workshop + asyncWorkshopAsyncWorkshop
Outputdifferent
Decision Tree, Option Map, Assumption ListRisk list, Mitigation plan, Assumption logExperiment results, Decision log, Learning summaryTest Matrix, Test Plan
Tagsno overlap
DecisionTreeOptions
RiskDecisionFailurePlanning
ExperimentsGrowthAnalyticsValidation
ExperimentsValidationDiscoveryOptions
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