View methods side by side.
Choose up to four methods. Add them using the search and share the comparison by copying its link.
| Criterion |  Engineering Failure Scenario Analysis |  Decision Making Decision Tree |  Growth A/B Testing |  Product Discovery MVP Test Matrix |
|---|---|---|---|---|
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. | For decisions with follow-on paths and dependencies, a linear comparison is often not enough. A Decision Tree shows how options branch under conditions and which consequences hang on each branch. | 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 several minimal variants compete to answer the same question, it makes comparing and choosing between them cleaner. It separates problem, assumption, solution, and evidence. The result is captured as a Test Matrix and a Test Plan. |
Complexitydifferent | Medium | Medium | High | Medium |
Timedifferent | 1-3 h | 30-90 min | 1-4 Wochen | 45-75 min |
Participantsdifferent | 3-8 | 1-6 | 1-6 | 2-8 |
Formatdifferent | Workshop | Workshop + async | Async | Workshop |
Outputdifferent | Failure Scenarios, Risk Notes, Control Gaps, Test and Response Actions | Decision Tree, Option Map, Assumption List | Experiment results, Decision log, Learning summary | Test Matrix, Test Plan |
Tagsno overlap | FailureResilienceRisk | DecisionTreeOptions | ExperimentsGrowthAnalyticsValidation | ExperimentsValidationDiscoveryOptions |