Abstract
Conventional demand forecasting and inventory management models cannot be applied to replacement parts due to their intermittent and seasonal demand. Thus the aim of this study is to compare, in the case of the strategic stocking of high turnover replacement parts, the demand forecast model currently used by construction and agricultural machinery companies with the Box-Jenkins statistical model. The results show that it is important to use a methodology based on statistical techniques in inventory management, and that the proposed model adapts better to high turnover stock control.
Highlights
This paper is a case study from a worldwide company that manufactures construction and agricultural machines
The uncertainty principle is inherent in forecasting methods; and for many authors, uncertainty is accentuated in long-term demand estimates, as market conditions are subject to change [33]
The results were satisfactory for the two models used: the Box-Jenkins and exponential smoothing
Summary
This paper is a case study from a worldwide company that manufactures construction and agricultural machines. The paper uses only data from its Brazilian operation, where the company has about three thousand employees; the spare parts business employs about five hundred of them. As one of its products, to agricultural and construction machinery dealers, who are its direct customers. Dealers sell these spare parts to their end customers. A very interesting aspect of the dealerships is the percentage of profit-sharing based on the sales of spare parts, as this segment is increasingly generating positive results. Dealerships view the spare parts business not just as a complement to the sale of machinery, and as a highly profitable business with great development opportunities [1]
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