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| Criterion |  Product Discovery Outcome-Driven Innovation |  Engineering Failure Scenario Analysis |  Growth A/B Testing |  Product Discovery Smoke Test |
|---|---|---|---|---|
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. | In critical processes, it is not enough to plan only for the normal case. Failure Scenario Analysis looks at the path into failure and shows which failures, chains, and control gaps cause the most damage. | 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. | 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. |
Complexitydifferent | High | Medium | High | Low |
Timedifferent | Mehrere Wochen | 1-3 h | 1-4 Wochen | 1-5 Tage |
Participantsdifferent | 2-6 researchers plus sample | 3-8 | 1-6 | Nutzertraffic |
Formatdifferent | Workshop + async | Workshop | Async | Async |
Outputdifferent | Desired outcome statements, Opportunity landscape, Segmentation by underserved needs, Innovation hypotheses | Failure Scenarios, Risk Notes, Control Gaps, Test and Response Actions | Experiment results, Decision log, Learning summary | Interest Metrics, Conversion Signal, Learning Note |
Tagsno overlap | OutcomesInnovationResearchQuantitative | FailureResilienceRisk | ExperimentsGrowthAnalyticsValidation | ValidationExperimentsDemandGrowth |