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| Criterion |  Engineering Failure Scenario Analysis |  Innovation Design Sprint |  Growth A/B Testing |  Innovation Design Thinking |
|---|---|---|---|---|
Purposedifferent | In critical processes, it is not enough to plan only for the normal case. Failure Scenario Analysis looks at the path into failure and shows which failures, chains, and control gaps cause the most 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. |
Complexitydifferent | Medium | High | High | High |
Timedifferent | 1-3 h | 4-5 Tage | 1-4 Wochen | 1 Tag bis mehrere Wochen |
Participantsdifferent | 3-8 | 5-8 | 1-6 | 4-10 |
Formatdifferent | Workshop | Workshop | Async | Workshop |
Outputdifferent | Failure Scenarios, Risk Notes, Control Gaps, Test and Response Actions | Prototype, Test Findings, Decision Rationale | Experiment results, Decision log, Learning summary | Problem Statement, Prototype, Test Learnings |
Tagsno overlap | FailureResilienceRisk | Design sprintPrototypeValidationInnovation | ExperimentsGrowthAnalyticsValidation | InnovationPrototypeResearch |