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Criterion
Decision Tree method illustration showing its working structure
Decision Making
Decision Tree
Paper illustration for PERT Estimation.
Decision Making
PERT Estimation
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration of a calm four-quadrant Assumption Map with hypothesis cards and emphasis on important assumptions with little evidence.
Product Discovery
Assumption Mapping
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.On complex initiatives, a plain average tends to understate just how uncertain the outcome really is. It separates options, evaluation criteria, and open risks. The result is captured as a PERT Estimate, Expected Value, and Risk Notes.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 assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first.
Complexitydifferent
MediumMediumHighMedium
Timedifferent
30-90 min15-45 min1-4 Wochen45-60 min
Participantsdifferent
1-61-81-62-8
Formatdifferent
Workshop + asyncWorkshop + asyncAsyncWorkshop + async
Outputdifferent
Decision Tree, Option Map, Assumption ListPERT Estimate, Expected Value, Risk NotesExperiment results, Decision log, Learning summaryAssumption map, Test backlog, Risk ranking
Tagsno overlap
DecisionTreeOptions
EstimationUncertaintyRisk
ExperimentsGrowthAnalyticsValidation
AssumptionsRiskExperimentsValidation
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