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Criterion
Paper illustration of Outcome-Driven Innovation with its method-specific working model.
Product Discovery
Outcome-Driven Innovation
Surveys method illustration showing its working structure
UX Research
Surveys
Paper illustration for Root Cause Analysis.
Operations
Root Cause Analysis
Paper illustration for Root Cause Tree Analysis
Operations
Root Cause Tree 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.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.When a problem keeps recurring and the cause stays unclear, the method exposes the underlying mechanism. It separates symptom, guess, and robust explanation from one another.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.
Complexitydifferent
HighMediumMediumMedium
Timedifferent
Mehrere Wochen3-14 Tage1-4 h1-3 h
Participantsdifferent
2-6 researchers plus sample50+3-82-8
Formatdifferent
Workshop + asyncAsyncWorkshop + asyncWorkshop
Outputdifferent
Desired outcome statements, Opportunity landscape, Segmentation by underserved needs, Innovation hypothesesSurvey Results, Charts, Segment InsightsProblem Statement, Cause Hypotheses, Confirmed Causes, Action PlanCause Tree, Evidence Notes, Countermeasures
Tagsno overlap
OutcomesInnovationResearchQuantitative
QuantitativeResearchValidation
Root causeProblem solvingQualityIncident
Root causeTreeIncidentQuality
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