This chapter presents a study of forecasting methods applicable to the spare parts demand faced by an automotive company that maintains a share of nearly 25% of the automotive market and sells approximately 13,000 parts per year. These parts are characterized by having intermittent demand and, in some cases, low demand, which makes it difficult for such companies to perform well and to obtain accurate forecasts. Therefore, this chapter includes a study of methods such as the Croston, Syntetos and Boylan, and Teunter methods, which are known to resolve these issues. Furthermore, the rolling Grey method is included, which is usually used in environments with short historical series and great uncertainty. In this study, traditional methods of prognosis, such as moving averages, exponential smoothing, and exponential smoothing with tendency and seasonality, are not neglected.
TopResearch Problem
The sale of automobiles has experienced a sustained increase in the case of the company under study, thus escalating the sale of spare parts. For the company under study, the spare parts and accessories business is a key development area and is one of the important factors for maintaining the competitiveness of the current market share. Table 1 summarizes the main characteristics of the brand under study and the company, which markets various brands.
Table 1. Main characteristics of the brand and company under study
| Market share of the company under study | 20%–25% |
| Participation of the brand under study within the company | 15%–20% |
| Annual car sales | 10,000–13,000 units |
| Annual spare parts sales | 300,000–320,000 units |
| Total employees | 3,000–3,500 people |
| Software used | SAP |
Source: Own elaboration based on the company's database (Company under study, 2017).
The administration of these parts and accessories is becoming increasingly complex owing to the constant growth in the volume of automobile sales in our country Chile (Asociación Nacional Automotriz de Chile A.G., 2017). The large number of cars in circulation only escalates the demand volumes of a variety of spare parts. This must be addressed as efficiently as possible while maintaining high levels of service, as the sale of original spare parts and the ability to respond promptly to demand have a great strategic impact on customer loyalty. The studied brand marketed 2,808 spare parts in the year 2017, of which only 9 are selected for analyzing the performance of the forecasts for the different types of spare parts.
It is necessary to obtain forecasts that reduce the uncertainty of future demand and that facilitate the adjustment of inventory levels to realize greater efficiency, thus reducing the current forecast error while applying a moving average method.
Forecasts are vital for every company—whether they belong to the manufacturing, business, or financial fields—and are necessary in administrative and managerial decision making. In the field of accounting and finance, forecasts provide the basis for budget analysis and planning. Marketing strategies are involved in sales staff decisions and the introduction of new products, which vary according to the sales forecasts. In turn, the production area makes capacity, function distribution, and operator decisions based on periodic forecasts obtained from the organization's commercial area (Chase, Jacobs, & Aquilano, 2006).
Generally, the spare parts industry faces a common problem, namely, intermittent demand and its variability (Syntetos & Boylan, 2001).
Some important demand patterns are explained in Table 2.