With the rapid development of economy, many enterprises are stepping into the era of scientific management. Sales forecasting is an indispensable link in the business activities of enterprises. The accuracy of forecasting is directly related to the success or failure of sales operations. Therefore, an improved BP neural network forecasting model based on the combination of traditional BP neural network and time series forecasting model is proposed. Through the forecasting of this model, the sales volume of enterprises in the future per unit time can be more reliably predicted. The improved neural network makes self-calibration referring to the prediction of synchronous time series, and uses genetic algorithm to achieve self-optimization through calibration, simplifies the network structure and improves the accuracy of prediction.