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Criterion
Story Splitting method illustration showing its working structure
Agile
Story Splitting
Paper illustration for Bottleneck Analysis.
Operations
Bottleneck Analysis
Value Stream Mapping workspace showing the question, observations, and next decision.
Delivery
Value Stream Mapping
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Purposedifferent
When a story becomes too large for a clean flow, it breaks scope down along value and risk. It shapes the work into a form that ships earlier and is easier to verify.For a flow that backs up at one point, the method looks for the capacity limit with the greatest leverage. It explains why extra effort elsewhere barely improves throughput.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.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
MediumMediumMediumHigh
Timedifferent
30-60 min1-3 h1-3 h30-90 min Setup, danach laufend
Participantsdifferent
2-63-84-101-8
Formatdifferent
Workshop + asyncWorkshop + asyncWorkshopWorkshop + async
Outputdifferent
Smaller Stories, Acceptance Criteria, Split RationaleBottleneck Map, Flow Metrics, Improvement Options, Follow-up MeasuresCurrent-state map, Future-state map, Bottleneck listForecast Percentiles, Throughput Dataset, Risk Communication
Tagsno overlap
BacklogIterationDelivery
FlowMeasurementConstraints
LeanFlowWasteDelivery
ForecastingFlowDelivery
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