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| Criterion |  Innovation Design Sprint |  Systems Thinking Future Reality Tree |  Innovation Design Thinking |  Systems Thinking Leverage Points |
|---|---|---|---|---|
Purposedifferent | 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. | 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 | 4-5 Tage | 2-4 h | 1 Tag bis mehrere Wochen | Half day |
Participantsdifferent | 5-8 | 3-8 | 4-10 | 3-12 |
Formatsame | Workshop | Workshop | Workshop | Workshop |
Outputdifferent | Prototype, Test Findings, Decision Rationale | Future Reality Tree, Negative Branches, Assumption List, Improved Injections | Problem Statement, Prototype, Test Learnings | Leverage Map, Action Strategy |
Tagsno overlap | Design sprintPrototypeValidationInnovation | Theory of ConstraintsSystems thinkingChange | InnovationPrototypeResearch | Systems thinkingChangeStrategy |