Neural networks and business modelling-an application of neural modelling techniques to prospect profiling in the telecommunications industry
C.B. Kappert, S.W.F. Omta · 2002
Organizations operate in turbulent environments. Frequent and unexpected changes in competition, customer demands and technology increase the need for a dynamic, adaptive and knowledge driven organization. Real time data collected from operational processes and market research can be integrated and enriched towards business information. To reduce the data overload produced by operational information systems, new data analysis methods have been proposed to recognize patterns or relationships. Neural networks have been recently introduced to support these data mining and decision support applications. The article describes a practical application of neural networks to a specific area of business modelling, ie. prospect profiling. It is shown that neural networks can be used in this area. The benefits and pitfalls of neural networks in such data mining applications are evaluated.