Modelo de previsão de faturamento e quantidade vendida de uma empresa de laticínios da Zona da Mata Mineira: uma aplicação do método de amortecimento exponencial

Abstract

This study aimed to forecast the revenue and sales volume of a company in the dairy sector using the Exponential Smoothing Method (ESM). The data was obtained from an internal control database, covering observations from 2022 to September 2024. The proposed model was adjusted considering trends and seasonality in the time series of six products: cream, dulce de leche, butter, cheese, requeijão, and ricotta. Cream and requeijão showed continuous growth, with a significant increase in sales volume and projected revenue for 2025. In contrast, butter and dulce de leche exhibited fluctuations and potential challenges in demand stability. The model's error statistics demonstrated good predictive capability for most products, with an adjusted R2 exceeding 70% for some items. However, products such as dulce de leche and cheese showed greater forecasting difficulty, as evidenced by high MAPE values. The analysis highlights the importance of forecasting as a strategic tool for financial planning, enabling companies to adjust their operations, optimize resource allocation, and make data-driven decisions in a highly competitive market. As a contribution, this study presents a practical application of statistical methods tailored to the dairy sector.