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| Criterion |  Decision Making Decision Tree |  Product Discovery Outcome-Driven Innovation |  Decision Making Delphi Method |  Innovation Design Thinking |
|---|---|---|---|---|
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. | 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. | When knowledge is distributed and direct dominance should be avoided, groups quickly fall under the sway of their opinion leaders. The Delphi Method gathers assessments iteratively and gradually brings expert judgments closer together. | 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 | Medium | High | High | High |
Timedifferent | 30-90 min | Mehrere Wochen | 1-4 Wochen | 1 Tag bis mehrere Wochen |
Participantsdifferent | 1-6 | 2-6 researchers plus sample | 6-30 Experten | 4-10 |
Formatdifferent | Workshop + async | Workshop + async | Async | Workshop |
Outputdifferent | Decision Tree, Option Map, Assumption List | Desired outcome statements, Opportunity landscape, Segmentation by underserved needs, Innovation hypotheses | Expert Forecast, Consensus Range, Assumption Notes | Problem Statement, Prototype, Test Learnings |
Tagsno overlap | DecisionTreeOptions | OutcomesInnovationResearchQuantitative | ForecastingExpertsDecisionStrategy | InnovationPrototypeResearch |