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| Criterion |  Decision Making Decision Tree |  Growth Hooked Model |  Decision Making Delphi Method |  Product Strategy DIBB |
|---|---|---|---|---|
Purposedifferent | 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. | The Hooked Model helps clarify engagement loops, user behavior, and experiments. It makes repeat behavior measurable and captures the result as a hooked loop, trigger map, and reward design. | 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 | 30-90 min | Multiple workshops over several weeks | 1-4 Wochen | 1-2 h |
Participantsdifferent | 1-6 | 2-8 | 6-30 Experten | 2-8 |
Formatdifferent | Workshop + async | Workshop + async | Async | Workshop + async |
Outputdifferent | Decision Tree, Option Map, Assumption List | Hooked loop, Trigger map, Reward design, Ethics check | Expert Forecast, Consensus Range, Assumption Notes | DIBB document, Belief list, Bet list, Learning report |
Tagsno overlap | DecisionTreeOptions | GrowthBehaviorRetention | ForecastingExpertsDecisionStrategy | StrategyDecisionAssumptionsHypothesis |