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| Criterion |  Operations Fault Tree Analysis |  Innovation Design Sprint |  Growth A/B Testing |  Innovation Design Thinking |
|---|---|---|---|---|
Purposedifferent | For a critical top event with several possible triggers, the method logically models failure paths. It makes visible which combinations of conditions can lead to damage. | When the product question is unclear and time pressure is high, the method takes a team from an open idea to a testable solution. It connects problem understanding, decision, and learning in one compact format, lowering the risk of spending a lot of energy on a mere guess. | 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. | For complex user problems with an uncertain cause, the method connects observation, interpretation, and experiment into a learning cycle. It keeps the focus on real needs and avoids premature solution language. This produces robust decisions for product and service. |
Complexitysame | High | High | High | High |
Timedifferent | 2-6 h | 4-5 Tage | 1-4 Wochen | 1 Tag bis mehrere Wochen |
Participantsdifferent | 3-8 | 5-8 | 1-6 | 4-10 |
Formatdifferent | Workshop + async | Workshop | Async | Workshop |
Outputdifferent | Fault Tree, Critical Paths, Cause Hypotheses, Control Actions | Prototype, Test Findings, Decision Rationale | Experiment results, Decision log, Learning summary | Problem Statement, Prototype, Test Learnings |
Tagsno overlap | RiskRoot causeSafety | Design sprintPrototypeValidationInnovation | ExperimentsGrowthAnalyticsValidation | InnovationPrototypeResearch |