Profit-oriented sales forecasting: a comparison of forecasting techniques from a business perspective
This work addresses forecasting technique selection for businesses, but it is incremental as it applies existing methods with a new profit-focused evaluation.
The paper tackled the problem of selecting the best forecasting technique for high-level tactical sales by comparing various methods on 35 time series, including Coca-Cola data, and introduced a profit-driven automated approach that incorporates expected profit during model building and evaluation. The results showed that simple seasonal time series models consistently outperformed other methodologies, and the profit-driven approach could lead to selecting different models.
Choosing the technique that is the best at forecasting your data, is a problem that arises in any forecasting application. Decades of research have resulted into an enormous amount of forecasting methods that stem from statistics, econometrics and machine learning (ML), which leads to a very difficult and elaborate choice to make in any forecasting exercise. This paper aims to facilitate this process for high-level tactical sales forecasts by comparing a large array of techniques for 35 times series that consist of both industry data from the Coca-Cola Company and publicly available datasets. However, instead of solely focusing on the accuracy of the resulting forecasts, this paper introduces a novel and completely automated profit-driven approach that takes into account the expected profit that a technique can create during both the model building and evaluation process. The expected profit function that is used for this purpose, is easy to understand and adaptable to any situation by combining forecasting accuracy with business expertise. Furthermore, we examine the added value of ML techniques, the inclusion of external factors and the use of seasonal models in order to ascertain which type of model works best in tactical sales forecasting. Our findings show that simple seasonal time series models consistently outperform other methodologies and that the profit-driven approach can lead to selecting a different forecasting model.