Diagnosing order planning performance at a navy maintenance and repair organization, using logistic regression

We present a tool to diagnose the behavior of planners in complex production processes and to establish improvement potential for the delivery performance by changing the planning behavior. Scientific literature on production control offers valuable knowledge, but the complexity of real-life processes makes it impossible to directly apply this knowledge in real-life. The presented tool identifies possible deficiencies in the current way of managing the business processes, by matching the scientific knowledge on order planning with data reflecting the real-life processes via logistic regression. A case study at a maintenance organization illustrates the diagnosis tool.