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| Criterion |  Product Discovery Outcome-Driven Innovation |  Product Discovery Opportunity Solution Tree |  Operations Causal Factor Analysis |  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. | 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 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. | 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 | Medium | High | Low |
Timedifferent | Mehrere Wochen | 1-2 h Setup, laufend | 2-6 h | 15-30 min |
Participantsdifferent | 2-6 researchers plus sample | 2-6 | 3-10 | 2-6 |
Formatdifferent | Workshop + async | Workshop + async | Workshop + async | Workshop |
Outputdifferent | Desired outcome statements, Opportunity landscape, Segmentation by underserved needs, Innovation hypotheses | Opportunity Solution Tree, Experiment Backlog, Learning Log | Event Timeline, Causal Factor Chart, Cause List, Corrective Actions | Root cause notes, Countermeasures |
Tagsno overlap | OutcomesInnovationResearchQuantitative | DiscoveryOutcomesExperimentsOpportunity | CausalityIncidentRoot causeTimeline | Root causeIncidentLeanProblem solving |