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| Criterion |  Delivery Value Stream Mapping |  Agile Story Points |  Product Discovery Dual-Track Agile |  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 teams want to rate complexity rather than hours, it creates a shared, relative scale. It sorts work by value, risk, and delivery ability. The result is captured as Point Estimates, Reference Stories, and Velocity Data. | 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. | 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 | Medium | Medium | Medium | High |
Timedifferent | 1-3 h | laufend, 1-5 min je Item | Laufend, Wochen bis Monate | 30-90 min Setup, danach laufend |
Participantsdifferent | 4-10 | 3-9 | 4-10 | 1-8 |
Formatdifferent | Workshop | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Current-state map, Future-state map, Bottleneck list | Point Estimates, Reference Stories, Velocity Data | Discovery Backlog, Delivery Backlog, Experiment-Ergebnisse, Validierte Stories | Forecast Percentiles, Throughput Dataset, Risk Communication |
Tagsno overlap | LeanFlowWasteDelivery | EstimationAgileMeasurement | AgileDiscoveryDelivery | ForecastingFlowDelivery |