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