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| Criterion |  Product Discovery Outcome-Driven Innovation |  Operations Root Cause Tree Analysis |  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 problem with several suspected causes, the method builds a causal structure instead of a mere list. It makes visible how causes connect and where the strongest points of leverage lie. | 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 | Medium | High |
Timedifferent | Mehrere Wochen | 1-3 h | 2-6 h |
Participantsdifferent | 2-6 researchers plus sample | 2-8 | 3-10 |
Formatdifferent | Workshop + async | Workshop | Workshop + async |
Outputdifferent | Desired outcome statements, Opportunity landscape, Segmentation by underserved needs, Innovation hypotheses | Cause Tree, Evidence Notes, Countermeasures | Event Timeline, Causal Factor Chart, Cause List, Corrective Actions |
Tagsno overlap | OutcomesInnovationResearchQuantitative | Root causeTreeIncidentQuality | CausalityIncidentRoot causeTimeline |
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