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| Criterion |  Agile Affinity Estimation |  Agile NoEstimates |  Product Strategy DIBB |  Decision Making Delphi Method |
|---|---|---|---|---|
Purposedifferent | 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 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. | 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. | 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 | Medium | Medium | Low | High |
Timedifferent | 30-90 min | laufend | 1-2 h | 1-4 Wochen |
Participantsdifferent | 3-12 | 2-12 | 2-8 | 6-30 Experten |
Formatdifferent | Workshop | Workshop + async | Workshop + async | Async |
Outputdifferent | Affinity Size Map, Grouped Estimates, Unclear Items | Throughput Data, Flow Forecast, Slicing Rules | DIBB document, Belief list, Bet list, Learning report | Expert Forecast, Consensus Range, Assumption Notes |
Tagsno overlap | EstimationBacklogRelative sizing | EstimationForecastingFlow | StrategyDecisionAssumptionsHypothesis | ForecastingExpertsDecisionStrategy |