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Criterion
Value Stream Mapping workspace showing the question, observations, and next decision.
Delivery
Value Stream Mapping
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration for NoEstimates.
Agile
NoEstimates
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Purposedifferent
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 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 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.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
MediumHighMediumHigh
Timedifferent
1-3 h1-4 Wochenlaufend30-90 min Setup, danach laufend
Participantsdifferent
4-101-62-121-8
Formatdifferent
WorkshopAsyncWorkshop + asyncWorkshop + async
Outputdifferent
Current-state map, Future-state map, Bottleneck listExperiment results, Decision log, Learning summaryThroughput Data, Flow Forecast, Slicing RulesForecast Percentiles, Throughput Dataset, Risk Communication
Tagsno overlap
LeanFlowWasteDelivery
ExperimentsGrowthAnalyticsValidation
EstimationForecastingFlow
ForecastingFlowDelivery
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