Forecasting methods are being used during the planning phase in different departments in several companies, helping managers on their decision-making process. The aim of this paper is to analyze which forecast method fits better for the scrap rate of a tire industry based on historical data analysis. The scrap rate is a very important key performance indicator for the observed company, having a high weight on strategic decisions. Using past data, a comparison is made between trend-based methods: regression analysis and double exponential smoothing, and the currently in use by the company, a subjective method. By having a set KPI established for the tire scrap allows companies to allocate the proper funding and resources to this process. This also allows companies to have a standardized selection method on different factors that is accurate. In doing so there is no exact better or worse method to forecast the data however each company needs to evaluate which method is right for them.