View methods side by side.
Choose up to four methods. Add them using the search and share the comparison by copying its link.
| Criterion |  Engineering Failure Scenario Analysis |  Product Discovery Outcome-Driven Innovation |  Product Discovery Smoke Test |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | 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. | 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. | 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 | Medium | High | Low | High |
Timedifferent | 1-3 h | Mehrere Wochen | 1-5 Tage | 1-4 Wochen |
Participantsdifferent | 3-8 | 2-6 researchers plus sample | Nutzertraffic | 1-6 |
Formatdifferent | Workshop | Workshop + async | Async | Async |
Outputdifferent | Failure Scenarios, Risk Notes, Control Gaps, Test and Response Actions | Desired outcome statements, Opportunity landscape, Segmentation by underserved needs, Innovation hypotheses | Interest Metrics, Conversion Signal, Learning Note | Experiment results, Decision log, Learning summary |
Tagsno overlap | FailureResilienceRisk | OutcomesInnovationResearchQuantitative | ValidationExperimentsDemandGrowth | ExperimentsGrowthAnalyticsValidation |