Supply chain risk mitigation through sales forecasting in a cosmetics company

Abstract

Demand forecasting has become a fundamental tool for companies' strategic planning. Represented by one of the highest growth rates in the country, the cosmetics industry faces numerous challenges in meeting the demand of consumers with a high level of service. Correctly identifying demand is critical to avoiding unnecessary extra costs for the business, such as stockout or stock over. The sales data of shampoo franchises are real values, covering the period from January 2013 to December 2018. After data organization, open-time and fixed-time time series techniques were analyzed in order to find the best forecasting technique for the type of product analyzed, i.e. the method with the smallest difference in absolute values between the actual demanded. and the estimated. The models were successfully applied, and we concluded that one of the analyzed methods could be applied in the company, because it presented smaller Mean Absolute Percentage Error.