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Criterion
Paper illustration of Dual Track Agile with its method-specific working model.
Product Discovery
Dual-Track Agile
Value Stream Mapping workspace showing the question, observations, and next decision.
Delivery
Value Stream Mapping
Gemba Walk workspace showing the question, observations, and next decision.
Operations
Gemba Walk
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Purposedifferent
When uncertainty and delivery run in parallel, it separates learning work from implementation while keeping both connected. It prevents unvalidated ideas from falling directly into the delivery stream.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 there is uncertainty about the real course of a process, the method brings observation to the place where work happens. It combines perception, follow-up questions, and process knowledge so decisions rest on actual workflows instead of assumptions.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
MediumMediumLowHigh
Timedifferent
Laufend, Wochen bis Monate1-3 h30-120 min30-90 min Setup, danach laufend
Participantsdifferent
4-104-102-61-8
Formatdifferent
Workshop + asyncWorkshopWorkshopWorkshop + async
Outputdifferent
Discovery Backlog, Delivery Backlog, Experiment-Ergebnisse, Validierte StoriesCurrent-state map, Future-state map, Bottleneck listObservation Notes, Improvement IdeasForecast Percentiles, Throughput Dataset, Risk Communication
Tagsno overlap
AgileDiscoveryDelivery
LeanFlowWasteDelivery
LeanObservationProcessOperations
ForecastingFlowDelivery
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