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| Criterion |  Product Discovery Outcome-Driven Innovation |  Innovation Design Thinking |  Systems Thinking Future Reality Tree |  Innovation Design Sprint |
|---|---|---|---|---|
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. | 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. | 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. | When the product question is unclear and time pressure is high, the method takes a team from an open idea to a testable solution. It connects problem understanding, decision, and learning in one compact format, lowering the risk of spending a lot of energy on a mere guess. |
Complexitysame | High | High | High | High |
Timedifferent | Mehrere Wochen | 1 Tag bis mehrere Wochen | 2-4 h | 4-5 Tage |
Participantsdifferent | 2-6 researchers plus sample | 4-10 | 3-8 | 5-8 |
Formatdifferent | Workshop + async | Workshop | Workshop | Workshop |
Outputdifferent | Desired outcome statements, Opportunity landscape, Segmentation by underserved needs, Innovation hypotheses | Problem Statement, Prototype, Test Learnings | Future Reality Tree, Negative Branches, Assumption List, Improved Injections | Prototype, Test Findings, Decision Rationale |
Tagsno overlap | OutcomesInnovationResearchQuantitative | InnovationPrototypeResearch | Theory of ConstraintsSystems thinkingChange | Design sprintPrototypeValidationInnovation |