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| Criterion |  Product Discovery Outcome-Driven Innovation |  Operations Fault Tree Analysis |  Product Discovery Opportunity Solution Tree |  Innovation Design Thinking |
|---|---|---|---|---|
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. | When discovery keeps swinging between goals, ideas, and learning loops, it creates clear steering logic. It connects the desired outcome, opportunities, and experiments into a legible structure. | For complex user problems with an uncertain cause, the method connects observation, interpretation, and experiment into a learning cycle. It keeps the focus on real needs and avoids premature solution language. This produces robust decisions for product and service. |
Complexitydifferent | High | High | Medium | High |
Timedifferent | Mehrere Wochen | 2-6 h | 1-2 h Setup, laufend | 1 Tag bis mehrere Wochen |
Participantsdifferent | 2-6 researchers plus sample | 3-8 | 2-6 | 4-10 |
Formatdifferent | Workshop + async | Workshop + async | Workshop + async | Workshop |
Outputdifferent | Desired outcome statements, Opportunity landscape, Segmentation by underserved needs, Innovation hypotheses | Fault Tree, Critical Paths, Cause Hypotheses, Control Actions | Opportunity Solution Tree, Experiment Backlog, Learning Log | Problem Statement, Prototype, Test Learnings |
Tagsno overlap | OutcomesInnovationResearchQuantitative | RiskRoot causeSafety | DiscoveryOutcomesExperimentsOpportunity | InnovationPrototypeResearch |