Abstract

Sales forecasting is a crucial aspect of business management, which involves predicting future sales based on historical data and market trends. Accurate sales forecasts are essential for effective decision-making, such as inventory management, production planning, and resource allocation. This study explores the application of mathematical modelling in sales forecasting. A case study approach was used to demonstrate how mathematical modelling can be deployed to develop accurate sales forecasts. Specifically, historical sales data and market trends were used to develop mathematical models, including regression analysis, and time series analysis, to predict future sales.

Keywords: Seasonal decomposition, Domain expertise, Exponential smoothing, SARIMA, ARIMA, LSTM, and STL