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Criterion
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Paper illustration of Riskiest Assumption Test with a method-specific labelled workspace.
Product Discovery
Riskiest Assumption Test
Paper illustration of a Learning Card with four fields for hypothesis, observation, insight, and action.
Product Discovery
Learning Card
Paper illustration of Experiment Canvas with a method-specific labelled workspace.
Product Discovery
Experiment Canvas
Purposedifferent
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 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.The Learning Card connects traceable test results to a reasoned next action while keeping the limits of the insight visible.When experiments become unreadable after the fact, it arranges hypothesis, signal, and learning goal on a single canvas. It separates problem, assumption, solution, and evidence. The result is captured as a Completed Experiment Canvas and a Success Metric.
Complexitydifferent
HighMediumLowLow
Timedifferent
30-90 min Setup, danach laufend1-2 Wochen pro Iteration25-40 min30-60 min
Participantsdifferent
1-82-61-51-5
Formatsame
Workshop + asyncWorkshop + asyncWorkshop + asyncWorkshop + async
Outputdifferent
Forecast Percentiles, Throughput Dataset, Risk CommunicationPrioritized Assumption List, Test Plan, Results ReportLearning Card with evidence and next actionCompleted Experiment Canvas, Success Metric
Tagsno overlap
ForecastingFlowDelivery
ExperimentsValidationDiscoveryAssumptions
ExperimentsValidationDiscoveryLearning
ExperimentsValidationDiscoveryHypothesis
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