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| Criterion |  Operations PDCA Cycle |  UX Research User Interviews |  Domain Modeling EventStorming |  Product Discovery Experiment Canvas |
|---|---|---|---|---|
Purposedifferent | For an improvement that still has to prove itself in everyday work, the method runs it through small learning loops. It connects planning, checking, and standardization into a repeatable learning mode. | When teams derive needs only from assumptions and real motives are missing, user interviews give direct access to behavior and meaning. Conversations from the target group's everyday life make patterns, tensions, and open questions solidly visible. | When a domain consists of many events, rules, and states, it creates a shared modeling space for the team. It bundles language, flows, and boundaries before domain knowledge fragments into siloed views. | When experiments become unreadable after the fact, it arranges hypothesis, signal, and learning goal on a single canvas. It separates problem, assumption, solution, and evidence. The result is captured as a Completed Experiment Canvas and a Success Metric. |
Complexitydifferent | Low | Low | Medium | Low |
Timedifferent | 1 h bis mehrere Wochen | 30–60 min per interview | 2-8 h | 30-60 min |
Participantsdifferent | 1-8 | 1 participant per interview | 5-12 | 1-5 |
Formatdifferent | Workshop + async | Workshop + async | Workshop | Workshop + async |
Outputdifferent | PDCA Log, Experiment Plan, Learning Outcome, Standard Change | Interview Notes, Themes, Insight Summary | Event Timeline, Ubiquitous Language, Boundaries, Open Questions | Completed Experiment Canvas, Success Metric |
Tagsno overlap | Continuous improvementLeanExperiments | QualitativeResearchCustomerDiscovery | Domain-Driven DesignEventsDiscoveryWorkshop | ExperimentsValidationDiscoveryHypothesis |