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| Criterion |  Operations Change Analysis |  Growth Funnel Analysis |  Operations 5 Whys |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | For a deviation after a change, the method isolates the influence of the altered condition. It narrows down which differences are relevant and which are just accompanying noise. | When many visitors or users drop off along the way, the reason behind the number often stays hidden. Funnel Analysis exposes these transitions and makes visible exactly where the path collapses. | 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. | 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 | Medium | Low | High |
Timedifferent | 45-120 min | 1-3 h | 15-30 min | 1-4 Wochen |
Participantsdifferent | 2-6 | 1-5 | 2-6 | 1-6 |
Formatdifferent | Workshop + async | Async | Workshop | Async |
Outputdifferent | Change Matrix, Cause Hypotheses, Validation Questions, Action List | Funnel report, Drop-off analysis, Optimization hypotheses | Root cause notes, Countermeasures | Experiment results, Decision log, Learning summary |
Tagsno overlap | ChangeRoot causeTroubleshootingComparison | AnalyticsConversionGrowth | Root causeIncidentLeanProblem solving | ExperimentsGrowthAnalyticsValidation |