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| Criterion |  Operations Change Analysis |  Growth Flywheel |  Product Strategy Counter Metrics |  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. | Growth often breaks down where a reinforcing mechanism builds up too much friction. A Flywheel shows the cycle of value, repetition, and reinforcement meant to sustain growth. | When a headline metric could mask side effects, it adds guardrail signals against unwanted outcomes. It connects customer value, product logic, and decision priorities. The result is captured as a counter-metric list and guardrail definitions. | 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 | 60-120 min | 30-60 min | 1-4 Wochen |
Participantsdifferent | 2-6 | 3-8 | 2-6 | 1-6 |
Formatdifferent | Workshop + async | Workshop | Workshop + async | Async |
Outputdifferent | Change Matrix, Cause Hypotheses, Validation Questions, Action List | Flywheel Map, Friction Points, Growth Levers, Experiment Backlog | Counter Metric List, Guardrail Definitions | Experiment results, Decision log, Learning summary |
Tagsno overlap | ChangeRoot causeTroubleshootingComparison | GrowthRetentionConversion | MetricsMeasurementStrategyExperiments | ExperimentsGrowthAnalyticsValidation |