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| Criterion |  Product Discovery Outcome-Driven Innovation |  Operations Causal Factor Analysis |  UX Research Surveys |  Operations 5 Whys |
|---|---|---|---|---|
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 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. | 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 a single, hard-to-explain deviation, the method exposes the causal chain behind the visible symptom. It keeps the cause open until a controllable condition emerges instead of a mere description. |
Complexitydifferent | High | High | Medium | Low |
Timedifferent | Mehrere Wochen | 2-6 h | 3-14 Tage | 15-30 min |
Participantsdifferent | 2-6 researchers plus sample | 3-10 | 50+ | 2-6 |
Formatdifferent | Workshop + async | Workshop + async | Async | Workshop |
Outputdifferent | Desired outcome statements, Opportunity landscape, Segmentation by underserved needs, Innovation hypotheses | Event Timeline, Causal Factor Chart, Cause List, Corrective Actions | Survey Results, Charts, Segment Insights | Root cause notes, Countermeasures |
Tagsno overlap | OutcomesInnovationResearchQuantitative | CausalityIncidentRoot causeTimeline | QuantitativeResearchValidation | Root causeIncidentLeanProblem solving |