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Criterion
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Value Stream Mapping workspace showing the question, observations, and next decision.
Delivery
Value Stream Mapping
Paper illustration of a calm four-quadrant Assumption Map with hypothesis cards and emphasis on important assumptions with little evidence.
Product Discovery
Assumption Mapping
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
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 delivery work dissolves into wait times, handoffs, and hidden effort, Value Stream Mapping makes the actual flow visible. The method exposes bottlenecks, idle time, and feedback loops so lead time and improvement levers become tangible.When assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first.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
HighMediumMediumHigh
Timedifferent
30-90 min Setup, danach laufend1-3 h45-60 min1-4 Wochen
Participantsdifferent
1-84-102-81-6
Formatdifferent
Workshop + asyncWorkshopWorkshop + asyncAsync
Outputdifferent
Forecast Percentiles, Throughput Dataset, Risk CommunicationCurrent-state map, Future-state map, Bottleneck listAssumption map, Test backlog, Risk rankingExperiment results, Decision log, Learning summary
Tagsno overlap
ForecastingFlowDelivery
LeanFlowWasteDelivery
AssumptionsRiskExperimentsValidation
ExperimentsGrowthAnalyticsValidation
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