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| Criterion |  Agile T-Shirt Sizing |  Decision Making Delphi Method |  Decision Making Decision Tree |  Product Strategy DIBB |
|---|---|---|---|---|
Purposedifferent | When effort only needs to be classified roughly, it makes comparability more important than false precision. It helps sort work quickly into manageable sizes. | 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. | For decisions with follow-on paths and dependencies, a linear comparison is often not enough. A Decision Tree shows how options branch under conditions and which consequences hang on each branch. | 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 | Low | High | Medium | Low |
Timedifferent | 15-45 min | 1-4 Wochen | 30-90 min | 1-2 h |
Participantsdifferent | 2-12 | 6-30 Experten | 1-6 | 2-8 |
Formatdifferent | Workshop + async | Async | Workshop + async | Workshop + async |
Outputdifferent | Size Buckets, Rough Backlog Map, Split Candidates | Expert Forecast, Consensus Range, Assumption Notes | Decision Tree, Option Map, Assumption List | DIBB document, Belief list, Bet list, Learning report |
Tagsno overlap | EstimationAgileRoadmap | ForecastingExpertsDecisionStrategy | DecisionTreeOptions | StrategyDecisionAssumptionsHypothesis |