A novel finished-goods inventory management process for a tire manufacturer

Official URL: https://risc01.sabanciuniv.edu/record=b2767133_(Table of contents)

In this thesis, we develop processes to determine the finished goods inventory levels and associated production decisions for a tire manufacturer. Studying the business practices and the needs of the company in its different sales channels, we identified three cases for keeping inventory: Prebuild stock for products that face highly seasonal demand, cycle stock for the strategic mix products, and safety stock to guard against fluctuations in the automotive manufacturer orders. For each case, we used scoring and machine-learning based approaches to segmentize and prioritize the tire SKUs based on product dimensions that span finance, sales, marketing, production and planning functions of the firm. In doing so, we also developed a number of novel metrics to capture product characteristics such as demand seasonality and capacity insufficiency.