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| Criterion |  Business Strategy Value Chain Analysis |  Product Strategy DIBB |  Growth A/B Testing |  Product Discovery Experiment Canvas |
|---|---|---|---|---|
Purposedifferent | Value Chain Analysis shows where value is created, costs accrue, and differentiation becomes possible along the process. It compares strengths, risks, market logic, and courses of action. The result is captured as a value-chain map and lever list. | DIBB helps clarify target groups, value, goals, and priorities by making the logic behind a decision explicit. It captures results as a DIBB document, belief list, bet list, and learning report. | 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 | High | Low | High | Low |
Timedifferent | Half day | 1-2 h | 1-4 Wochen | 30-60 min |
Participantsdifferent | 3-8 | 2-8 | 1-6 | 1-5 |
Formatdifferent | Workshop | Workshop + async | Async | Workshop + async |
Outputdifferent | Value Chain Map, Lever List | DIBB document, Belief list, Bet list, Learning report | Experiment results, Decision log, Learning summary | Completed Experiment Canvas, Success Metric |
Tagsno overlap | StrategyBusiness modelDiagnosisAnalysis | StrategyDecisionAssumptionsHypothesis | ExperimentsGrowthAnalyticsValidation | ExperimentsValidationDiscoveryHypothesis |