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| Criterion |  Operations ABC Analysis |  Agile Affinity Estimation |  Delivery Monte Carlo Forecasting |
|---|---|---|---|
Purposedifferent | With many similar objects of differing economic significance, the method prioritizes effort by effect. It separates what needs regular steering from what rarely needs attention. | 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. | 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 | Low | Medium | High |
Timedifferent | 30-60 min | 30-90 min | 30-90 min Setup, danach laufend |
Participantsdifferent | 1-5 | 3-12 | 1-8 |
Formatdifferent | Async | Workshop | Workshop + async |
Outputdifferent | ABC Classification, Focus Rules, Control List | Affinity Size Map, Grouped Estimates, Unclear Items | Forecast Percentiles, Throughput Dataset, Risk Communication |
Tagsno overlap | PrioritizationOperationsPortfolio | EstimationBacklogRelative sizing | ForecastingFlowDelivery |
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