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| Criterion |  Product Discovery Outcome-Driven Innovation |  Product Discovery Opportunity Solution Tree |  Operations ALPEN Method |  Innovation Design Thinking |
|---|---|---|---|---|
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. | When discovery keeps swinging between goals, ideas, and learning loops, it creates clear steering logic. It connects the desired outcome, opportunities, and experiments into a legible structure. | With an overloaded day full of too many tasks, a realistic picture of the day emerges. The method connects estimating, deciding, and buffer thinking so planning fits available energy and time. | 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. |
Complexitydifferent | High | Medium | Low | High |
Timedifferent | Mehrere Wochen | 1-2 h Setup, laufend | 10-20 min daily | 1 Tag bis mehrere Wochen |
Participantsdifferent | 2-6 researchers plus sample | 2-6 | 1 | 4-10 |
Formatdifferent | Workshop + async | Workshop + async | Async | Workshop |
Outputdifferent | Desired outcome statements, Opportunity landscape, Segmentation by underserved needs, Innovation hypotheses | Opportunity Solution Tree, Experiment Backlog, Learning Log | Daily Plan, Time Estimates, Review Notes | Problem Statement, Prototype, Test Learnings |
Tagsno overlap | OutcomesInnovationResearchQuantitative | DiscoveryOutcomesExperimentsOpportunity | PlanningTime managementProductivityOperations | InnovationPrototypeResearch |