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| Criterion |  Systems Thinking Future Reality Tree |  Product Discovery Outcome-Driven Innovation |  Systems Thinking Leverage Points |  Innovation Design Thinking |
|---|---|---|---|---|
Purposedifferent | 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. | 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. | 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 | 2-4 h | Mehrere Wochen | Half day | 1 Tag bis mehrere Wochen |
Participantsdifferent | 3-8 | 2-6 researchers plus sample | 3-12 | 4-10 |
Formatdifferent | Workshop | Workshop + async | Workshop | Workshop |
Outputdifferent | Future Reality Tree, Negative Branches, Assumption List, Improved Injections | Desired outcome statements, Opportunity landscape, Segmentation by underserved needs, Innovation hypotheses | Leverage Map, Action Strategy | Problem Statement, Prototype, Test Learnings |
Tagsno overlap | Theory of ConstraintsSystems thinkingChange | OutcomesInnovationResearchQuantitative | Systems thinkingChangeStrategy | InnovationPrototypeResearch |