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| Criterion |  Delivery Monte Carlo Forecasting |  Decision Making Delphi Method |  Agile Bucket System |  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 knowledge is distributed and direct dominance should be avoided, groups quickly fall under the sway of their opinion leaders. The Delphi Method gathers assessments iteratively and gradually brings expert judgments closer together. | 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. | 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 | High | Medium | Medium |
Timedifferent | 30-90 min Setup, danach laufend | 1-4 Wochen | 30-90 min | 30-90 min |
Participantsdifferent | 1-8 | 6-30 Experten | 3-12 | 3-12 |
Formatdifferent | Workshop + async | Async | Workshop | Workshop |
Outputdifferent | Forecast Percentiles, Throughput Dataset, Risk Communication | Expert Forecast, Consensus Range, Assumption Notes | Bucketed Backlog, Relative Estimates, Split Candidates | Affinity Size Map, Grouped Estimates, Unclear Items |
Tagsno overlap | ForecastingFlowDelivery | ForecastingExpertsDecisionStrategy | EstimationBacklogRelative sizing | EstimationBacklogRelative sizing |