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| Criterion |  Operations PDCA Cycle |  Decision Making Constraint Analysis |  Operations ALPEN Method |  Decision Making Decision Tree |
|---|---|---|---|---|
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 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. | 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. | 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. |
Complexitydifferent | Low | Low | Low | Medium |
Timedifferent | 1 h bis mehrere Wochen | 30-90 min | 10-20 min daily | 30-90 min |
Participantsdifferent | 1-8 | 2-8 | 1 | 1-6 |
Formatdifferent | Workshop + async | Workshop + async | Async | Workshop + async |
Outputdifferent | PDCA Log, Experiment Plan, Learning Outcome, Standard Change | Constraint List, Hard/Soft Classification, Option Impact Notes, Decision Boundaries | Daily Plan, Time Estimates, Review Notes | Decision Tree, Option Map, Assumption List |
Tagsno overlap | Continuous improvementLeanExperiments | ConstraintsDecisionPlanningOptions | PlanningTime managementProductivityOperations | DecisionTreeOptions |