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Criterion
Paper illustration of a calm four-quadrant Assumption Map with hypothesis cards and emphasis on important assumptions with little evidence.
Product Discovery
Assumption Mapping
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration of Riskiest Assumption Test with a method-specific labelled workspace.
Product Discovery
Riskiest Assumption Test
Purposedifferent
When assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first.Helps clarify scope, sequence, and delivery flow in concrete terms. It makes work, boundaries, and order steerable. The result is captured as Forecast Percentiles, Throughput Dataset, and Risk Communication.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 an idea hinges on one critical unknown, it prioritizes testing that exact piece of uncertainty first. It separates problem, assumption, solution, and evidence. The result is captured as a prioritized list of assumptions, a test plan, and a result report.
Complexitydifferent
MediumHighHighMedium
Timedifferent
45-60 min30-90 min Setup, danach laufend1-4 Wochen1-2 Wochen pro Iteration
Participantsdifferent
2-81-81-62-6
Formatdifferent
Workshop + asyncWorkshop + asyncAsyncWorkshop + async
Outputdifferent
Assumption map, Test backlog, Risk rankingForecast Percentiles, Throughput Dataset, Risk CommunicationExperiment results, Decision log, Learning summaryPrioritized Assumption List, Test Plan, Results Report
Tagsno overlap
AssumptionsRiskExperimentsValidation
ForecastingFlowDelivery
ExperimentsGrowthAnalyticsValidation
ExperimentsValidationDiscoveryAssumptions
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