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| Criterion |  Delivery Cost of Delay |  Decision Making Decision Matrix |  Product Discovery Smoke Test |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | Helps clarify scope, order, and delivery flow in concrete terms. It makes work, constraints, and sequence manageable. The result is captured as a Cost of Delay table and prioritization sequence. | When several options collide with several criteria, comparison quickly becomes subjective. A Decision Matrix makes the trade-off visible and brings weighting, criteria, and options into a shared logic. | 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. | 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 | High | Medium | Low | High |
Timedifferent | 90-180 min | 45-90 min | 1-5 Tage | 1-4 Wochen |
Participantsdifferent | 3-8 | 2-8 | Nutzertraffic | 1-6 |
Formatdifferent | Workshop | Workshop + async | Async | Async |
Outputdifferent | CoD Table, Prioritization Sequence | Decision Matrix, Scoring Rationale, Selected Option | Interest Metrics, Conversion Signal, Learning Note | Experiment results, Decision log, Learning summary |
Tagsno overlap | PrioritizationDeliveryEconomicsDecision | DecisionCriteriaScoringTradeoffs | ValidationExperimentsDemandGrowth | ExperimentsGrowthAnalyticsValidation |