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Criterion
Value Stream Mapping workspace showing the question, observations, and next decision.
Delivery
Value Stream Mapping
Growth Experiment workspace showing the question, observations, and next decision.
Growth
Growth Experiment
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 growth ideas surface quickly, the temptation to build immediately instead of learning is high. A Growth Experiment frames an assumption so target group, lever, and measurement are clear before the first deployment.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
MediumMediumHigh
Timedifferent
1-3 h1-2 Wochen30-90 min Setup, danach laufend
Participantsdifferent
4-101-61-8
Formatdifferent
WorkshopWorkshop + asyncWorkshop + async
Outputdifferent
Current-state map, Future-state map, Bottleneck listExperiment card, Result summary, Next betForecast Percentiles, Throughput Dataset, Risk Communication
Tagsno overlap
LeanFlowWasteDelivery
MarketingGrowthExperimentsLearning
ForecastingFlowDelivery
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Methods with strong topical overlap with the current selection, not yet in the comparison.

Paper illustration of a Learning Card with four fields for hypothesis, observation, insight, and action.
Product Discovery
Learning Card