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| Criterion |  Operations PDCA Cycle |  Innovation Design Thinking |  Operations Causal Factor Analysis |  Operations 5 Whys |
|---|---|---|---|---|
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. | 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. | For an event with a complicated course, the method breaks down the contributing factors along the timeline. It shows how conditions, decisions, and reactions together produce a course of events. | For a single, hard-to-explain deviation, the method exposes the causal chain behind the visible symptom. It keeps the cause open until a controllable condition emerges instead of a mere description. |
Complexitydifferent | Low | High | High | Low |
Timedifferent | 1 h bis mehrere Wochen | 1 Tag bis mehrere Wochen | 2-6 h | 15-30 min |
Participantsdifferent | 1-8 | 4-10 | 3-10 | 2-6 |
Formatdifferent | Workshop + async | Workshop | Workshop + async | Workshop |
Outputdifferent | PDCA Log, Experiment Plan, Learning Outcome, Standard Change | Problem Statement, Prototype, Test Learnings | Event Timeline, Causal Factor Chart, Cause List, Corrective Actions | Root cause notes, Countermeasures |
Tagsno overlap | Continuous improvementLeanExperiments | InnovationPrototypeResearch | CausalityIncidentRoot causeTimeline | Root causeIncidentLeanProblem solving |