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| Criterion |  Product Discovery Outcome-Driven Innovation |  Systems Thinking Leverage Points |  Systems Thinking Future Reality Tree |  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. | Leverage Points show exactly where interventions in a system produce a disproportionate effect. It draws relationships, patterns, and feedback loops. The result is captured as a leverage map and action strategy. | A Future Reality Tree shows how desired actions are meant to lead to a better system state. The method checks whether a path of change holds together logically before time flows into implementation. | 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. |
Complexitysame | High | High | High | High |
Timedifferent | Mehrere Wochen | Half day | 2-4 h | 1 Tag bis mehrere Wochen |
Participantsdifferent | 2-6 researchers plus sample | 3-12 | 3-8 | 4-10 |
Formatdifferent | Workshop + async | Workshop | Workshop | Workshop |
Outputdifferent | Desired outcome statements, Opportunity landscape, Segmentation by underserved needs, Innovation hypotheses | Leverage Map, Action Strategy | Future Reality Tree, Negative Branches, Assumption List, Improved Injections | Problem Statement, Prototype, Test Learnings |
Tagsno overlap | OutcomesInnovationResearchQuantitative | Systems thinkingChangeStrategy | Theory of ConstraintsSystems thinkingChange | InnovationPrototypeResearch |