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| Criterion |  Delivery Monte Carlo Forecasting |  Agile Bucket System |  Decision Making Delphi Method |
|---|---|---|---|
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 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 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. |
Complexitydifferent | High | Medium | High |
Timedifferent | 30-90 min Setup, danach laufend | 30-90 min | 1-4 Wochen |
Participantsdifferent | 1-8 | 3-12 | 6-30 Experten |
Formatdifferent | Workshop + async | Workshop | Async |
Outputdifferent | Forecast Percentiles, Throughput Dataset, Risk Communication | Bucketed Backlog, Relative Estimates, Split Candidates | Expert Forecast, Consensus Range, Assumption Notes |
Tagsno overlap | ForecastingFlowDelivery | EstimationBacklogRelative sizing | ForecastingExpertsDecisionStrategy |
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