新型ARIMA-BP组合模型在医药企业销售管理中的应用

Application of ARIMA-BP model in the sales management of the listed pharmaceutical companies

随着医药企业间的市场竞争加剧,企业销售管理的重要性逐渐凸显。医药销售预测是个复杂的非线性系统,为提高企业销售预测的准确性,本文选取医药上市企业处方药七叶皂苷钠历史销售数据,分别建立ARIMA线性模型和BP神经网络非线性模型并加以验证。证明了在销售预测上采用ARIMA-BP组合模型可以有效降低误差,为医药企业的销售管理和企业决策带来新的思路。

The importance of sales management in pharmaceutical enterprises has become increasingly prominent with the intensification of market competition among them. Since the forecast of pharmaceutical sales is a complex nonlinear system, the data of historical sales for sodium aescinate, a prescription drug from the listed pharmaceutical companies were selected, and an ARIMA linear model and a BP network nonlinear model were established and verified based on the theory of linear and nonlinear prediction in order to improve the accuracy of sales forecast. It is proved that adoption of a combination of two models can effectively reduce errors and bring in some new ideas for the sales management and policy decision of pharmaceutical enterprises.