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| Criterion |  Decision Making Delphi Method |  Engineering Goal Question Metric |  Growth A/B Testing |  Growth North Star Metric |
|---|---|---|---|---|
Purposedifferent | When knowledge is distributed and direct dominance should be avoided, groups quickly fall under the sway of their opinion leaders. The Delphi Method gathers assessments iteratively and gradually brings expert judgments closer together. | Helps clarify technical problems, hypotheses, and next steps in concrete terms. It breaks a technical problem into testable parts. The result is captured as a GQM table and metric briefs. | 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 product teams track many metrics, the view of the actual customer outcome easily gets lost. A North Star Metric bundles growth, usage, and value contribution into one signal that makes the system's direction visible. |
Complexitydifferent | High | Medium | High | Medium |
Timedifferent | 1-4 Wochen | 90-180 min | 1-4 Wochen | 1-2 h |
Participantsdifferent | 6-30 Experten | 3-6 | 1-6 | 3-8 |
Formatdifferent | Async | Workshop | Async | Workshop + async |
Outputdifferent | Expert Forecast, Consensus Range, Assumption Notes | GQM Table, Metric Profiles | Experiment results, Decision log, Learning summary | North Star metric, Input metric tree, Measurement cadence |
Tagsno overlap | ForecastingExpertsDecisionStrategy | MetricsMeasurementEngineeringAlignment | ExperimentsGrowthAnalyticsValidation | GrowthMetricsAlignmentRetention |