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| Criterion |  Growth A/B Testing |  Operations 5 Whys |  Operations Causal Factor Analysis |  Product Discovery Smoke Test |
|---|---|---|---|---|
Purposedifferent | 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. | 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. | 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. | 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 | Low | High | Low |
Timedifferent | 1-4 Wochen | 15-30 min | 2-6 h | 1-5 Tage |
Participantsdifferent | 1-6 | 2-6 | 3-10 | Nutzertraffic |
Formatdifferent | Async | Workshop | Workshop + async | Async |
Outputdifferent | Experiment results, Decision log, Learning summary | Root cause notes, Countermeasures | Event Timeline, Causal Factor Chart, Cause List, Corrective Actions | Interest Metrics, Conversion Signal, Learning Note |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | Root causeIncidentLeanProblem solving | CausalityIncidentRoot causeTimeline | ValidationExperimentsDemandGrowth |