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| Criterion |  Product Discovery Outcome-Driven Innovation |  Decision Making Decision Tree |  Decision Making Pre-Mortem |  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 early initiatives with many uncertainties, planning quickly turns too optimistic. A pre-mortem makes the expected failure visible in advance and sharpens the view of causes, gaps, and countermeasures. | 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 | Low | High |
Timedifferent | Mehrere Wochen | 30-90 min | 20–45 min | 1 Tag bis mehrere Wochen |
Participantsdifferent | 2-6 researchers plus sample | 1-6 | Small cross-functional group | 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 | Risk list, Mitigation plan, Assumption log | Problem Statement, Prototype, Test Learnings |
Tagsno overlap | OutcomesInnovationResearchQuantitative | DecisionTreeOptions | RiskDecisionFailurePlanning | InnovationPrototypeResearch |