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| Criterion |  Product Discovery Outcome-Driven Innovation |  Operations Fault Tree Analysis |  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 a critical top event with several possible triggers, the method logically models failure paths. It makes visible which combinations of conditions can lead to damage. | 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 | High | Low |
Timedifferent | Mehrere Wochen | 2-6 h | 1-2 h |
Participantsdifferent | 2-6 researchers plus sample | 3-8 | 2-8 |
Formatsame | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Desired outcome statements, Opportunity landscape, Segmentation by underserved needs, Innovation hypotheses | Fault Tree, Critical Paths, Cause Hypotheses, Control Actions | DIBB document, Belief list, Bet list, Learning report |
Tagsno overlap | OutcomesInnovationResearchQuantitative | RiskRoot causeSafety | StrategyDecisionAssumptionsHypothesis |
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