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| Criterion |  Innovation Design Thinking |  Systems Thinking Future Reality Tree |  Product Strategy DIBB |
|---|---|---|---|
Purposedifferent | 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. | DIBB helps clarify target groups, value, goals, and priorities by making the logic behind a decision explicit. It captures results as a DIBB document, belief list, bet list, and learning report. |
Complexitydifferent | High | High | Low |
Timedifferent | 1 Tag bis mehrere Wochen | 2-4 h | 1-2 h |
Participantsdifferent | 4-10 | 3-8 | 2-8 |
Formatdifferent | Workshop | Workshop | Workshop + async |
Outputdifferent | Problem Statement, Prototype, Test Learnings | Future Reality Tree, Negative Branches, Assumption List, Improved Injections | DIBB document, Belief list, Bet list, Learning report |
Tagsno overlap | InnovationPrototypeResearch | Theory of ConstraintsSystems thinkingChange | StrategyDecisionAssumptionsHypothesis |
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