Enterprises cannot accomplish all that they can envision, need, and want at the same time; therefore smart data strategy and the associated pursuit of enterprise performance optimization must be iterative. It must happen with a plan and schedule that is within the scope of capacity for change and improvement.
The enabling technology platform on which SOE and smart data is based permits individual organizations in the enterprise to make improvements as they are ready. Entities should not be placed in the position of doing nothing while waiting for another improvement. The goal is to promote change and improvement that can happen under local control.
However, the process must also make dependencies visible and consequences of change visible, such that higher levels of management can intervene as necessary to manage collaboration and to leverage for maximum improvement. Herein lies the opportunity to apply smart data with associated methods and algorithms.
The following case illustrates these points, in which we examine the performance of a genetic algorithm (GA) based artificial neural network (ANN) for different cross-over operators in order to provide a method for executives to exert local control while promoting change and improvement .
GA based ANNs are used in several classification and forecasting applications. Among several ...