Use of Data Mining to Optimize the Selection of Scenarios for Accepting Planned Decisions in Russian Companies

Abstract :

The authors offer a methodology for developing a model of dependence of key company performance indicators – sales profit and unit costs on different factors, which operate in competitive environment, as exemplified by a modern Russian company, and for determining the nature of correlations and the degree of factor influence with the use of Data Mining methods. The methodology is based on studying correlations between key factor features by means of pair correlation linear coefficient analysis based on statistical evaluation of input information on the Russian company performance indicators. The use of methods of Data Mining correlation and regression analysis, which take into consideration the factors of external and internal environment of the company, allows deriving a universal established model for calculation of sales profit and unit costs for the purpose of using it for development of scenarios for accepting planned decisions in the company.