A dynamic approach to operations management: An alternative to static optimization

In today’s globally competitive manufacturing environment, many firms are compelled to rapidly improve and evolve their operations. But traditional formal analysis of operations management is ‘static’, emphasizing optimization in a steady state world. The authors propose an alternative ‘dynamic’ approach to analyzing operations management. The present approach deals explicitly with four elements not considered by most static approaches: knowledge, learning, contingencies, and problem solving. In studying each of these elements in detail, emphasis shifts from improving efficiency assuming complete technological knowledge, to deliberately enhancing rates of improvement and of adaptation to new situations. Robotic assembly of watches is discussed in detail as an example of a process that ought to fit the static approach, i.e., be managed for static efficiency. In fact, the authors find that the process is managed dynamically. They propose several ways of applying traditional modeling tools to dynamic issues. Considerable further research will be needed to develop models for dynamic situations that are as powerful as traditional models are for static situations.