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Criterion
Paper illustration for Three-Point Estimation.
Decision Making
Three-Point Estimation
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Purposedifferent
A single estimate for effort, time, or risk often looks too smooth for the real uncertainty behind it. It separates options, evaluation criteria, and open risks. The result is captured as a Three-Point Estimate, Risk Range, and Assumption 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.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.
Complexitydifferent
MediumHighHigh
Timedifferent
10-30 min je Item1-4 Wochen30-90 min Setup, danach laufend
Participantsdifferent
1-81-61-8
Formatdifferent
Workshop + asyncAsyncWorkshop + async
Outputdifferent
Three-Point Estimate, Risk Range, Assumption NotesExperiment results, Decision log, Learning summaryForecast Percentiles, Throughput Dataset, Risk Communication
Tagsno overlap
EstimationUncertaintyForecasting
ExperimentsGrowthAnalyticsValidation
ForecastingFlowDelivery
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Methods with strong topical overlap with the current selection, not yet in the comparison.

Paper illustration for Smoke Test.
Product Discovery
Smoke Test
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 of Experiment Canvas with a method-specific labelled workspace.
Product Discovery
Experiment Canvas