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| Criterion |  Product Discovery Solution Interview |  Systems Thinking Future Reality Tree |  Product Discovery Concierge MVP |  Innovation Design Sprint |
|---|---|---|---|---|
Purposedifferent | When a solution idea is already on the table, it checks how it is understood and evaluated. It looks for resonance, objections, and missing fit early in the conversation. | 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 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. | 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. |
Complexitydifferent | Medium | High | Medium | High |
Timedifferent | 30-60 min je Interview | 2-4 h | 1-4 Wochen | 4-5 Tage |
Participantsdifferent | 5-10 Interviews | 3-8 | 3-10 Kunden | 5-8 |
Formatdifferent | Workshop + async | Workshop | Workshop + async | Workshop |
Outputdifferent | Solution Feedback, Objection List, Validation Notes | Future Reality Tree, Negative Branches, Assumption List, Improved Injections | Concierge Learnings, Service Blueprint, MVP Risks | Prototype, Test Findings, Decision Rationale |
Tagsno overlap | ValidationInterviewsPrototype | Theory of ConstraintsSystems thinkingChange | MVPValidationServiceDiscovery | Design sprintPrototypeValidationInnovation |