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| Criterion |  Innovation Design Thinking |  Decision Making Decision Matrix |  Decision Making Decision Tree |  Decision Making Constraint Analysis |
|---|---|---|---|---|
Purposedifferent | 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 several options collide with several criteria, comparison quickly becomes subjective. A Decision Matrix makes the trade-off visible and brings weighting, criteria, and options into a shared logic. | 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 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 | High | Medium | Medium | Low |
Timedifferent | 1 Tag bis mehrere Wochen | 45-90 min | 30-90 min | 30-90 min |
Participantsdifferent | 4-10 | 2-8 | 1-6 | 2-8 |
Formatdifferent | Workshop | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Problem Statement, Prototype, Test Learnings | Decision Matrix, Scoring Rationale, Selected Option | Decision Tree, Option Map, Assumption List | Constraint List, Hard/Soft Classification, Option Impact Notes, Decision Boundaries |
Tagsno overlap | InnovationPrototypeResearch | DecisionCriteriaScoringTradeoffs | DecisionTreeOptions | ConstraintsDecisionPlanningOptions |