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| Criterion |  Decision Making Delphi Method |  Agile NoEstimates |  Delivery Monte Carlo Forecasting |  Product Strategy DIBB |
|---|---|---|---|---|
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. | 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. | 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. | DIBB helps clarify target groups, value, goals, and priorities by making the logic behind a decision explicit. It captures results as a DIBB document, belief list, bet list, and learning report. |
Complexitydifferent | High | Medium | High | Low |
Timedifferent | 1-4 Wochen | laufend | 30-90 min Setup, danach laufend | 1-2 h |
Participantsdifferent | 6-30 Experten | 2-12 | 1-8 | 2-8 |
Formatdifferent | Async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Expert Forecast, Consensus Range, Assumption Notes | Throughput Data, Flow Forecast, Slicing Rules | Forecast Percentiles, Throughput Dataset, Risk Communication | DIBB document, Belief list, Bet list, Learning report |
Tagsno overlap | ForecastingExpertsDecisionStrategy | EstimationForecastingFlow | ForecastingFlowDelivery | StrategyDecisionAssumptionsHypothesis |