Creating Knowledge for Business Decision Making
Shiraj Khan (University of South Florida (USF), USA), Auroop R. Ganguly (Oak Ridge National Laboratory, USA) and Amar Gupta (University of Arizona, Tucson, USA)
Copyright: © 2006
Business forecasts and predictive models are rarely perfect. A paraphrase of the Nobel winning physicist Neils Bohr is apt in this context: Prediction is difficult, especially if it is of the future. However, executives and managers in enterprises ranging from retail and consumer packaged goods to high tech and semiconductors have to resort to forecasting and planning about the future. Phenomenal growth and spectacular failures are associated with organizations depending on their ability to understand market directions and respond quickly to change. Relatively minor improvements in forecast accuracy and predictive modeling at detailed levels can translate to significant gains for the enterprise through better strategic decisions, continuous performance management, and rapid translation to tactical decisions. The key to these processes is the knowledge-based enterprise, which can effectively utilize information from multiple sources as well as the expertise of skilled human resources, to develop strategies and processes for creating, preserving, and utilizing knowledge. These efforts, spanning revenue-generation endeavors like promotion management or new product launch, to cost-cutting operations like inventory planning or demand management, have significant impacts on the top and bottom lines of an enterprise.