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Criterion
Decision Tree method illustration showing its working structure
Decision Making
Decision Tree
Paper illustration of a calibrated five-by-five risk matrix with response cards.
Decision Making
Risk Matrix
Paper illustration of a calm four-quadrant Assumption Map with hypothesis cards and emphasis on important assumptions with little evidence.
Product Discovery
Assumption Mapping
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
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.When a project faces many possible disruptions, it quickly becomes unclear which risks deserve attention first. It separates options, evaluation criteria, and open risks. The result is captured as a Risk Matrix and a Top Risk List.When assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first.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.
Complexitydifferent
MediumLowMediumHigh
Timedifferent
30-90 min30-60 min45-60 min1-4 Wochen
Participantsdifferent
1-63-102-81-6
Formatdifferent
Workshop + asyncWorkshop + asyncWorkshop + asyncAsync
Outputdifferent
Decision Tree, Option Map, Assumption ListRisk Matrix, Top Risk ListAssumption map, Test backlog, Risk rankingExperiment results, Decision log, Learning summary
Tagsno overlap
DecisionTreeOptions
RiskDecisionPrioritizationAssessment
AssumptionsRiskExperimentsValidation
ExperimentsGrowthAnalyticsValidation
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