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| Criterion |  Product Discovery Outcome-Driven Innovation |  Decision Making Delphi Method |  Product Strategy DIBB |  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 knowledge is distributed and direct dominance should be avoided, groups quickly fall under the sway of their opinion leaders. The Delphi Method gathers assessments iteratively and gradually brings expert judgments closer together. | 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. | 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 | High | Low | High |
Timedifferent | Mehrere Wochen | 1-4 Wochen | 1-2 h | 1 Tag bis mehrere Wochen |
Participantsdifferent | 2-6 researchers plus sample | 6-30 Experten | 2-8 | 4-10 |
Formatdifferent | Workshop + async | Async | Workshop + async | Workshop |
Outputdifferent | Desired outcome statements, Opportunity landscape, Segmentation by underserved needs, Innovation hypotheses | Expert Forecast, Consensus Range, Assumption Notes | DIBB document, Belief list, Bet list, Learning report | Problem Statement, Prototype, Test Learnings |
Tagsno overlap | OutcomesInnovationResearchQuantitative | ForecastingExpertsDecisionStrategy | StrategyDecisionAssumptionsHypothesis | InnovationPrototypeResearch |