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Criterion
Paper illustration for NoEstimates.
Agile
NoEstimates
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
Purposedifferent
When estimating slows a team down more than it helps, it shifts the focus to flow, small slices, and real lead time. It sorts work by value, risk, and delivery ability. The result is captured as Throughput Data, Flow Forecast, and Slicing Rules.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.
Complexitydifferent
MediumMediumHighHigh
Timedifferent
laufend45-60 min30-90 min Setup, danach laufend1-4 Wochen
Participantsdifferent
2-122-81-81-6
Formatdifferent
Workshop + asyncWorkshop + asyncWorkshop + asyncAsync
Outputdifferent
Throughput Data, Flow Forecast, Slicing RulesAssumption map, Test backlog, Risk rankingForecast Percentiles, Throughput Dataset, Risk CommunicationExperiment results, Decision log, Learning summary
Tagsno overlap
EstimationForecastingFlow
AssumptionsRiskExperimentsValidation
ForecastingFlowDelivery
ExperimentsGrowthAnalyticsValidation
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