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| Criterion |  Delivery Monte Carlo Forecasting |  Delivery Value Stream Mapping |  Agile Planning Poker |  Agile Affinity Estimation |
|---|---|---|---|---|
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 estimates within the team diverge too much, it puts differing expectations on a common test bench. It separates rough complexity from unspoken assumptions. | When many tasks need to be classified quickly, it sorts them by perceived effort and similarity. It reduces the effort of fine-grained estimation for large volumes. |
Complexitydifferent | High | Medium | Low | Medium |
Timedifferent | 30-90 min Setup, danach laufend | 1-3 h | 2-5 min je Item | 30-90 min |
Participantsdifferent | 1-8 | 4-10 | 3-9 | 3-12 |
Formatdifferent | Workshop + async | Workshop | Workshop + async | Workshop |
Outputdifferent | Forecast Percentiles, Throughput Dataset, Risk Communication | Current-state map, Future-state map, Bottleneck list | Relative Estimates, Assumption Notes, Split Candidates | Affinity Size Map, Grouped Estimates, Unclear Items |
Tagsno overlap | ForecastingFlowDelivery | LeanFlowWasteDelivery | EstimationAgileRelative sizingTeam | EstimationBacklogRelative sizing |