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| Criterion |  Decision Making Delphi Method |  Delivery Monte Carlo Forecasting |  Agile Bucket System |  Agile NoEstimates |
|---|---|---|---|---|
Purposedifferent | 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. | 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 estimating slows a team down more than it helps, it shifts the focus to flow, small slices, and real lead time. It sorts work by value, risk, and delivery ability. The result is captured as Throughput Data, Flow Forecast, and Slicing Rules. |
Complexitydifferent | High | High | Medium | Medium |
Timedifferent | 1-4 Wochen | 30-90 min Setup, danach laufend | 30-90 min | laufend |
Participantsdifferent | 6-30 Experten | 1-8 | 3-12 | 2-12 |
Formatdifferent | Async | Workshop + async | Workshop | Workshop + async |
Outputdifferent | Expert Forecast, Consensus Range, Assumption Notes | Forecast Percentiles, Throughput Dataset, Risk Communication | Bucketed Backlog, Relative Estimates, Split Candidates | Throughput Data, Flow Forecast, Slicing Rules |
Tagsno overlap | ForecastingExpertsDecisionStrategy | ForecastingFlowDelivery | EstimationBacklogRelative sizing | EstimationForecastingFlow |