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