Management and forecast of dynamic customer needs: An artificial immune and neural system approach

The twenty-first century is marked by fast evolution of customer tastes and needs. Research has shown that customer requirements could vary in the temporal space between product conceptualization and market introduction. In such cases, the products generated might not fit the consumer needs as companies originally expected. This paper advocates the proactive management and forecast of the dynamic customer requirements in bid to lower the inherent risk in developing products for fast shifting markets. The research identified the principles of artificial immune and neural systems as a solution to the problem. A customer requirements analysis and forecast (CRAF) system is defined in this paper to address the issue. The system aims to support product development functions with quantitative and qualitative customer requirements information, in the pursuit of generating products for near future markets. A case study is presented in this article to illustrate the functions of the system.