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| Criterion |  Delivery Monte Carlo Forecasting |  Delivery Value Stream Mapping |  Operations Causal Factor Analysis |  Operations 5 Whys |
|---|---|---|---|---|
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. | For an event with a complicated course, the method breaks down the contributing factors along the timeline. It shows how conditions, decisions, and reactions together produce a course of events. | For a single, hard-to-explain deviation, the method exposes the causal chain behind the visible symptom. It keeps the cause open until a controllable condition emerges instead of a mere description. |
Complexitydifferent | High | Medium | High | Low |
Timedifferent | 30-90 min Setup, danach laufend | 1-3 h | 2-6 h | 15-30 min |
Participantsdifferent | 1-8 | 4-10 | 3-10 | 2-6 |
Formatdifferent | Workshop + async | Workshop | Workshop + async | Workshop |
Outputdifferent | Forecast Percentiles, Throughput Dataset, Risk Communication | Current-state map, Future-state map, Bottleneck list | Event Timeline, Causal Factor Chart, Cause List, Corrective Actions | Root cause notes, Countermeasures |
Tagsno overlap | ForecastingFlowDelivery | LeanFlowWasteDelivery | CausalityIncidentRoot causeTimeline | Root causeIncidentLeanProblem solving |