Data Mining using Statistical Analysis and Machine Learning Algorithms for Supply Chain Management

Abstract

Supply Chain Management (SCM) plays a very vital role in managing and organizing enterprise processes, increasing operational efficiency of the organization. Factors such as product success, customer satisfaction, organization’s growth depends upon successful execution of Supply Chain Management (SCM). Supply chain management is becoming a necessity to improve the foundation and infrastructure within societies which in turn increases the economic growth, living standard of society also. The research findings indicate that although it seems that SCM provides many services, but it has some issues too; which includes poor inventory management, bullwhip effect, High cost of logistics, technology usage and inadequate investments in IT. To overcome issues of SCM there is a need of an improved sales forecasting model which will build the reliable and efficient forecasting results. An improved Sales forecasting model is presented in this paper, which is based on kernel based support vector machine regression.