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| Criterion |  Product Discovery Outcome-Driven Innovation |  Operations MORT Analysis |  UX Research Surveys |  Operations Causal Factor Analysis |
|---|---|---|---|---|
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 safety-relevant event or a system with high protection requirements, the method examines where controls failed. It exposes both technical and organizational gaps. | 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. | For an event with a complicated course, the method breaks down the contributing factors along the timeline. It shows how conditions, decisions, and reactions together produce a course of events. |
Complexitydifferent | High | High | Medium | High |
Timedifferent | Mehrere Wochen | Mehrere Tage bis Wochen | 3-14 Tage | 2-6 h |
Participantsdifferent | 2-6 researchers plus sample | 2-6 | 50+ | 3-10 |
Formatdifferent | Workshop + async | Workshop + async | Async | Workshop + async |
Outputdifferent | Desired outcome statements, Opportunity landscape, Segmentation by underserved needs, Innovation hypotheses | MORT Worksheets, Findings per Branch, Corrective Actions, Systemic Recommendations | Survey Results, Charts, Segment Insights | Event Timeline, Causal Factor Chart, Cause List, Corrective Actions |
Tagsno overlap | OutcomesInnovationResearchQuantitative | Root causeSafetySystemicIncident | QuantitativeResearchValidation | CausalityIncidentRoot causeTimeline |