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| Criterion |  Product Discovery Opportunity Scoring |  Decision Making Decision Tree |  Decision Making Delphi Method |  Product Strategy DIBB |
|---|---|---|---|---|
Purposedifferent | When opportunities need ranking by their effect, it makes importance and satisfaction directly comparable. It separates problem, assumption, solution, and evidence. The result is captured as an opportunity-score table and top outcomes. | 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. | 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. | 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 | Medium | Medium | High | Low |
Timedifferent | 60-120 min | 30-90 min | 1-4 Wochen | 1-2 h |
Participantsdifferent | 3-6 | 1-6 | 6-30 Experten | 2-8 |
Formatdifferent | Workshop + async | Workshop + async | Async | Workshop + async |
Outputdifferent | Opportunity Score Table, Top Outcomes | Decision Tree, Option Map, Assumption List | Expert Forecast, Consensus Range, Assumption Notes | DIBB document, Belief list, Bet list, Learning report |
Tagsno overlap | PrioritizationDiscoveryOutcomesNeeds | DecisionTreeOptions | ForecastingExpertsDecisionStrategy | StrategyDecisionAssumptionsHypothesis |