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| Criterion |  Delivery Monte Carlo Forecasting |  Delivery Value Stream Mapping |  Agile Ideal Days |  Product Discovery Dual-Track Agile |
|---|---|---|---|---|
Purposedifferent | 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. | 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 effort needs to be thought of as real working time, it offers a simple common denominator for comparison. It sorts work by value, risk, and delivery ability. The result is captured as Ideal Day Estimates, Assumption Notes, and Capacity Caveats. | 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. |
Complexitydifferent | High | Medium | Low | Medium |
Timedifferent | 30-90 min Setup, danach laufend | 1-3 h | 15-60 min | Laufend, Wochen bis Monate |
Participantsdifferent | 1-8 | 4-10 | 2-9 | 4-10 |
Formatdifferent | Workshop + async | Workshop | Workshop + async | Workshop + async |
Outputdifferent | Forecast Percentiles, Throughput Dataset, Risk Communication | Current-state map, Future-state map, Bottleneck list | Ideal Day Estimates, Assumption Notes, Capacity Caveats | Discovery Backlog, Delivery Backlog, Experiment-Ergebnisse, Validierte Stories |
Tagsno overlap | ForecastingFlowDelivery | LeanFlowWasteDelivery | EstimationEffortAgile | AgileDiscoveryDelivery |