Um modelo de previsão de vendas em uma empresa de médio porte na cidade de Manaus

Abstract

The sales forecasting process has been structured over time with new technologies and tools, for data consolidation and handling. The companies, which previously had no focus on the sales forecasting process, were not impacted by the lack of it, but currently, adjustments are necessary for its insertion, because there is consensus that only intuitivity, usually directed by past experiences or subjectivities, or optimized results or underestimated them. Walking in the above, this research aims to identify a sales forecast model appropriate to the portfolio of a medium-sized beverage company. In the study of this dissertation, the explanatory research technique was applied with exploratory and descriptive analyses, and minitab® and Excel software was also used® to perform the analyses through statistical abstracts, tables and figures, so that there was the assertive choice of the model to be applied to the business. Qualitative and quantitative forecastmodels, graphic analysis, residue scans and forecast error calculations were evaluated. The mean deviations and MAPEs (Mean Absolute Percent Error) of the models were compared: moving average, exponential smoothing, linear trend and holt winter and, as conclusion, the models with the lowest prediction errors were: moving average N=2 with MAPE=14.8%, exponential smoothing with MAPE=15.2% and linear trend with MAPE=15.4%. The choice was for the exponential smoothing model, although not the slightest error is easy to apply and weights the historical data.