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