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| Criterion |  Delivery Monte Carlo Forecasting |  Agile Affinity Estimation |  Facilitation Dot Estimation |  Agile Bucket System |
|---|---|---|---|---|
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 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. | When size or effort can only be estimated roughly, Dot Estimation condenses the group's experience into a quick range. It turns individual contributions into a visible selection. The result is captured as an Effort Heatmap, Risk Signals, and Discussion Targets. | When a large batch of work needs a fast, rough estimate, it sorts items into predefined size buckets. It sorts work by value, risk, and delivery ability. The result is captured as a Bucketed Backlog, Relative Estimates, and Split Candidates. |
Complexitydifferent | High | Medium | Low | Medium |
Timedifferent | 30-90 min Setup, danach laufend | 30-90 min | 5-20 min | 30-90 min |
Participantsdifferent | 1-8 | 3-12 | 3-20 | 3-12 |
Formatdifferent | Workshop + async | Workshop | Workshop | Workshop |
Outputdifferent | Forecast Percentiles, Throughput Dataset, Risk Communication | Affinity Size Map, Grouped Estimates, Unclear Items | Effort Heatmap, Risk Signals, Discussion Targets | Bucketed Backlog, Relative Estimates, Split Candidates |
Tagsno overlap | ForecastingFlowDelivery | EstimationBacklogRelative sizing | EstimationEffortRisk | EstimationBacklogRelative sizing |