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| Criterion |  Decision Making Decision Tree |  UX Research Surveys |  Innovation Design Thinking |  Decision Making Constraint Analysis |
|---|---|---|---|---|
Purposedifferent | 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 a topic needs to be validated broadly and many people can answer the same question, surveys gather structured feedback in a scalable form. Answers become comparable and segmentable instead of remaining merely anecdotal. | 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. | When an initiative stalls, the limit often lies not in the idea but in hard or soft boundary conditions. Constraint Analysis separates these limits and shows which of them can actually be shaped. |
Complexitydifferent | Medium | Medium | High | Low |
Timedifferent | 30-90 min | 3-14 Tage | 1 Tag bis mehrere Wochen | 30-90 min |
Participantsdifferent | 1-6 | 50+ | 4-10 | 2-8 |
Formatdifferent | Workshop + async | Async | Workshop | Workshop + async |
Outputdifferent | Decision Tree, Option Map, Assumption List | Survey Results, Charts, Segment Insights | Problem Statement, Prototype, Test Learnings | Constraint List, Hard/Soft Classification, Option Impact Notes, Decision Boundaries |
Tagsno overlap | DecisionTreeOptions | QuantitativeResearchValidation | InnovationPrototypeResearch | ConstraintsDecisionPlanningOptions |