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| Criterion |  Agile Bucket System |  Decision Making Pre-Mortem |  Growth A/B Testing |  Product Discovery Smoke Test |
|---|---|---|---|---|
Purposedifferent | When a large batch of work needs a fast, rough estimate, it sorts items into predefined size buckets. It sorts work by value, risk, and delivery ability. The result is captured as a Bucketed Backlog, Relative Estimates, and Split Candidates. | In early initiatives with many uncertainties, planning quickly turns too optimistic. A pre-mortem makes the expected failure visible in advance and sharpens the view of causes, gaps, and countermeasures. | 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 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 | Medium | Low | High | Low |
Timedifferent | 30-90 min | 20–45 min | 1-4 Wochen | 1-5 Tage |
Participantsdifferent | 3-12 | Small cross-functional group | 1-6 | Nutzertraffic |
Formatdifferent | Workshop | Workshop | Async | Async |
Outputdifferent | Bucketed Backlog, Relative Estimates, Split Candidates | Risk list, Mitigation plan, Assumption log | Experiment results, Decision log, Learning summary | Interest Metrics, Conversion Signal, Learning Note |
Tagsno overlap | EstimationBacklogRelative sizing | RiskDecisionFailurePlanning | ExperimentsGrowthAnalyticsValidation | ValidationExperimentsDemandGrowth |