On approach for the implementation of data mining to business process optimization in commercial companies

Abstract

Nowadays organizations aim to automate their business processes with the objectives of improving operational efficiency, reducing costs, improving the quality of service offered to customers and reducing human error. Business process intelligence aims to apply data warehousing, data analysis, and data mining techniques to process execution data, thus enabling the analysis, interpretation, and optimization of business processes. Data mining approaches are most effective in helping us extract the insights into customer behaviour, habits, potential needs and desires, credit associated risks, fraudulent transactions, etc. However, the integration of data mining into business processes still requires a lot of coordination and manual adjustment. This paper aims at reducing this effort by reusing successful data mining solutions. We propose an approach for the implementation of data mining into business process. The confirmation of the suggested approach is based on the results achieved in eight commercial companies, covering different industries, such as telecommunications, banking and retail.