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| Criterion |  Product Discovery Outcome-Driven Innovation |  Innovation Design Thinking |  Engineering Failure Scenario Analysis |  UX Research Surveys |
|---|---|---|---|---|
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 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. | In critical processes, it is not enough to plan only for the normal case. Failure Scenario Analysis looks at the path into failure and shows which failures, chains, and control gaps cause the most damage. | When a topic needs to be validated broadly and many people can answer the same question, surveys gather structured feedback in a scalable form. Answers become comparable and segmentable instead of remaining merely anecdotal. |
Complexitydifferent | High | High | Medium | Medium |
Timedifferent | Mehrere Wochen | 1 Tag bis mehrere Wochen | 1-3 h | 3-14 Tage |
Participantsdifferent | 2-6 researchers plus sample | 4-10 | 3-8 | 50+ |
Formatdifferent | Workshop + async | Workshop | Workshop | Async |
Outputdifferent | Desired outcome statements, Opportunity landscape, Segmentation by underserved needs, Innovation hypotheses | Problem Statement, Prototype, Test Learnings | Failure Scenarios, Risk Notes, Control Gaps, Test and Response Actions | Survey Results, Charts, Segment Insights |
Tagsno overlap | OutcomesInnovationResearchQuantitative | InnovationPrototypeResearch | FailureResilienceRisk | QuantitativeResearchValidation |