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| Criterion |  Agile NoEstimates |  Growth Flywheel |  Growth A/B Testing |  Product Discovery Experiment Canvas |
|---|---|---|---|---|
Purposedifferent | When estimating slows a team down more than it helps, it shifts the focus to flow, small slices, and real lead time. It sorts work by value, risk, and delivery ability. The result is captured as Throughput Data, Flow Forecast, and Slicing Rules. | 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 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 experiments become unreadable after the fact, it arranges hypothesis, signal, and learning goal on a single canvas. It separates problem, assumption, solution, and evidence. The result is captured as a Completed Experiment Canvas and a Success Metric. |
Complexitydifferent | Medium | Medium | High | Low |
Timedifferent | laufend | 60-120 min | 1-4 Wochen | 30-60 min |
Participantsdifferent | 2-12 | 3-8 | 1-6 | 1-5 |
Formatdifferent | Workshop + async | Workshop | Async | Workshop + async |
Outputdifferent | Throughput Data, Flow Forecast, Slicing Rules | Flywheel Map, Friction Points, Growth Levers, Experiment Backlog | Experiment results, Decision log, Learning summary | Completed Experiment Canvas, Success Metric |
Tagsno overlap | EstimationForecastingFlow | GrowthRetentionConversion | ExperimentsGrowthAnalyticsValidation | ExperimentsValidationDiscoveryHypothesis |