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| Criterion |  Product Discovery Outcome-Driven Innovation |  Decision Making Decision Tree |  Product Strategy DIBB |
|---|---|---|---|
Purposedifferent | Outcome-Driven Innovation clarifies customer problems, solution opportunities, and evidence. It separates jobs, desired outcomes, importance, satisfaction, and opportunity, and captures results as desired outcome statements, an opportunity landscape, and segments by underserved needs. | 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 | High | Medium | Low |
Timedifferent | Mehrere Wochen | 30-90 min | 1-2 h |
Participantsdifferent | 2-6 researchers plus sample | 1-6 | 2-8 |
Formatsame | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Desired outcome statements, Opportunity landscape, Segmentation by underserved needs, Innovation hypotheses | Decision Tree, Option Map, Assumption List | DIBB document, Belief list, Bet list, Learning report |
Tagsno overlap | OutcomesInnovationResearchQuantitative | DecisionTreeOptions | StrategyDecisionAssumptionsHypothesis |
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