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| Criterion |  Operations PDCA Cycle |  Decision Making Decision Tree |  Operations Gemba Walk |  Decision Making Constraint Analysis |
|---|---|---|---|---|
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 decisions with follow-on paths and dependencies, a linear comparison is often not enough. A Decision Tree shows how options branch under conditions and which consequences hang on each branch. | When there is uncertainty about the real course of a process, the method brings observation to the place where work happens. It combines perception, follow-up questions, and process knowledge so decisions rest on actual workflows instead of assumptions. | When an initiative stalls, the limit often lies not in the idea but in hard or soft boundary conditions. Constraint Analysis separates these limits and shows which of them can actually be shaped. |
Complexitydifferent | Low | Medium | Low | Low |
Timedifferent | 1 h bis mehrere Wochen | 30-90 min | 30-120 min | 30-90 min |
Participantsdifferent | 1-8 | 1-6 | 2-6 | 2-8 |
Formatdifferent | Workshop + async | Workshop + async | Workshop | Workshop + async |
Outputdifferent | PDCA Log, Experiment Plan, Learning Outcome, Standard Change | Decision Tree, Option Map, Assumption List | Observation Notes, Improvement Ideas | Constraint List, Hard/Soft Classification, Option Impact Notes, Decision Boundaries |
Tagsno overlap | Continuous improvementLeanExperiments | DecisionTreeOptions | LeanObservationProcessOperations | ConstraintsDecisionPlanningOptions |