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| Criterion |  Product Discovery Outcome-Driven Innovation |  Decision Making Decision Tree |  Engineering Failure Scenario Analysis |  Innovation Design Thinking |
|---|---|---|---|---|
Purposedifferent | Outcome-Driven Innovation clarifies customer problems, solution opportunities, and evidence. It separates jobs, desired outcomes, importance, satisfaction, and opportunity, and captures results as desired outcome statements, an opportunity landscape, and segments by underserved needs. | 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. | 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 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 | High | Medium | Medium | High |
Timedifferent | Mehrere Wochen | 30-90 min | 1-3 h | 1 Tag bis mehrere Wochen |
Participantsdifferent | 2-6 researchers plus sample | 1-6 | 3-8 | 4-10 |
Formatdifferent | Workshop + async | Workshop + async | Workshop | Workshop |
Outputdifferent | Desired outcome statements, Opportunity landscape, Segmentation by underserved needs, Innovation hypotheses | Decision Tree, Option Map, Assumption List | Failure Scenarios, Risk Notes, Control Gaps, Test and Response Actions | Problem Statement, Prototype, Test Learnings |
Tagsno overlap | OutcomesInnovationResearchQuantitative | DecisionTreeOptions | FailureResilienceRisk | InnovationPrototypeResearch |