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| Criterion |  Systems Thinking Future Reality Tree |  Product Discovery Problem Interview |  Innovation Design Thinking |  Product Discovery Concierge MVP |
|---|---|---|---|---|
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. | When the picture of the problem still needs to become solid, it asks about real situations and consequences. It separates genuine suffering from mere interest in a solution. | 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. | When an idea can first fail or grow through genuine hands-on support, it relies on manual work instead of automation. It shows whether user value holds up even under manual execution. |
Complexitydifferent | High | Medium | High | Medium |
Timedifferent | 2-4 h | 30-60 min je Interview | 1 Tag bis mehrere Wochen | 1-4 Wochen |
Participantsdifferent | 3-8 | 5-12 Interviews | 4-10 | 3-10 Kunden |
Formatdifferent | Workshop | Workshop + async | Workshop | Workshop + async |
Outputdifferent | Future Reality Tree, Negative Branches, Assumption List, Improved Injections | Problem Evidence, Risk Notes, Customer Segments | Problem Statement, Prototype, Test Learnings | Concierge Learnings, Service Blueprint, MVP Risks |
Tagsno overlap | Theory of ConstraintsSystems thinkingChange | DiscoveryInterviewsValidation | InnovationPrototypeResearch | MVPValidationServiceDiscovery |