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| Criterion |  Agile Ideal Days |  Growth A/B Testing |  Decision Making Delphi Method |
|---|---|---|---|
Purposedifferent | When effort needs to be thought of as real working time, it offers a simple common denominator for comparison. It sorts work by value, risk, and delivery ability. The result is captured as Ideal Day Estimates, Assumption Notes, and Capacity Caveats. | 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 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. |
Complexitydifferent | Low | High | High |
Timedifferent | 15-60 min | 1-4 Wochen | 1-4 Wochen |
Participantsdifferent | 2-9 | 1-6 | 6-30 Experten |
Formatdifferent | Workshop + async | Async | Async |
Outputdifferent | Ideal Day Estimates, Assumption Notes, Capacity Caveats | Experiment results, Decision log, Learning summary | Expert Forecast, Consensus Range, Assumption Notes |
Tagsno overlap | EstimationEffortAgile | ExperimentsGrowthAnalyticsValidation | ForecastingExpertsDecisionStrategy |
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