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| Criterion |  Product Discovery Outcome-Driven Innovation |  Operations ALPEN Method |  Product Discovery Opportunity Solution Tree |  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. | 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. | 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. | 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 | Low | Medium | High |
Timedifferent | Mehrere Wochen | 10-20 min daily | 1-2 h Setup, laufend | 1 Tag bis mehrere Wochen |
Participantsdifferent | 2-6 researchers plus sample | 1 | 2-6 | 4-10 |
Formatdifferent | Workshop + async | Async | Workshop + async | Workshop |
Outputdifferent | Desired outcome statements, Opportunity landscape, Segmentation by underserved needs, Innovation hypotheses | Daily Plan, Time Estimates, Review Notes | Opportunity Solution Tree, Experiment Backlog, Learning Log | Problem Statement, Prototype, Test Learnings |
Tagsno overlap | OutcomesInnovationResearchQuantitative | PlanningTime managementProductivityOperations | DiscoveryOutcomesExperimentsOpportunity | InnovationPrototypeResearch |