Monthly Sales Forecast of Cigarettes under the Background of Business and Finance Integration

Abstract

Developing accurate and effective sales plans is of great value to every enterprise. This article takes the cigarette marketing line in L region as the research object, and develops a monthly sales model that matches the actual situation and has guiding value. The monthly sales forecast is constrained by annual sales and experience, resulting in two main problems: low planning accuracy and large fluctuations in actual monthly sales, making modeling difficult. Through research, it has been found that the fluctuations between different years and the same month are relatively small compared to the annual fluctuations. Therefore, it has been decided to adopt three types of exponential smoothing models: simple equilibrium, Hote linearity, and Brownian trend to predict monthly sales. By comparing three models, the Hote linear model predicts results more accurately.