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Criterion
Paper illustration of Outcome-Driven Innovation with its method-specific working model.
Product Discovery
Outcome-Driven Innovation
Paper illustration for Smoke Test.
Product Discovery
Smoke Test
Paper illustration of MORT Analysis with its method-specific working model.
Operations
MORT Analysis
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
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 demand only needs to be roughly verified, it tests interest with minimal effort. It measures whether people would take a next step at all.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 two variants compete, discussions quickly decide by taste rather than effect. A/B Testing checks behavior under controlled conditions and separates real improvement from chance or expectation effects.
Complexitydifferent
HighLowHighHigh
Timedifferent
Mehrere Wochen1-5 TageMehrere Tage bis Wochen1-4 Wochen
Participantsdifferent
2-6 researchers plus sampleNutzertraffic2-61-6
Formatdifferent
Workshop + asyncAsyncWorkshop + asyncAsync
Outputdifferent
Desired outcome statements, Opportunity landscape, Segmentation by underserved needs, Innovation hypothesesInterest Metrics, Conversion Signal, Learning NoteMORT Worksheets, Findings per Branch, Corrective Actions, Systemic RecommendationsExperiment results, Decision log, Learning summary
Tagsno overlap
OutcomesInnovationResearchQuantitative
ValidationExperimentsDemandGrowth
Root causeSafetySystemicIncident
ExperimentsGrowthAnalyticsValidation
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