What Can Be Learned from Classical Inventory Models? A Cross-Industry Exploratory Investigation

Abstract

Classical inventory models offer a variety of insights into the optimal way to manage inventories of individual products. However, top managers and industry analysts are often concerned with the aggregate macroscopic view of a firm's inventory rather than with the inventories of individual products. Given that classical inventory models often do not account for many practical considerations that a company's management faces (e.g., competition, industry dynamics, business cycles, the financial state of the company and of the economy, etc.) and that they are derived at the product level and not the firm level, can insights from these models be used to explain the inventory dynamics of entire companies? This exploratory study aims to address this issue using empirical data.We analyze absolute and relative inventories using a quarterly data panel that contains 722 public U.S. companies for the period 1992-2002. We have chosen companies that are not widely diversified and whose business in large part relies on inventory management to concentrate on empirically testing hypotheses derived from a variety of classical inventory models (economic order quantity (EOQ), [Q, r], newsvendor, periodic review, etc.). We find empirical evidence that firms operating with more uncertain demand, longer lead times, and higher gross margins have larger inventories. Furthermore, larger companies appear to benefit from economies of scale and therefore have relatively less inventory than smaller companies. We obtain mixed evidence on the relationship between inventory levels and inventory holding costs. We also analyze the breakdown of data into eight segments-oil and gas, electronics, wholesale, retail, machinery, hardware, food, and chemicals-and find that, with a few notable exceptions, our hypotheses are supported within the segments as well. Overall, our results demonstrate that many of the predictions from classical inventory models extend beyond individual products to the aggregate firm level; hence, these models can help with high-level strategic choices in addition to tactical decisions. Abstract: Classical inventory models offer a variety of insights into the optimal way to manage inventories of individual products. However, top managers and industry analysts are often concerned with the aggregate macroscopic view of a firm's inventory rather than with the inventories of individual products. Given that classical inventory models often do not account for many practical considerations that a company's management faces (e.g., competition, industry dynamics, business cycles, the financial state of the company and of the economy, etc.) and that they are derived at the product and not at the firm level, can insights from these models be used to explain the inventory dynamics of entire companies? This exploratory study aims to address this issue using empirical data.We analyze absolute and relative inventories using a quarterly data panel that contains 722 public US companies for the period 1992 to 2002. We have chosen compani...

OM Forum—Causal Inference Models in Operations Management

“…Other papers on inventory management employ single equation models, including those by Ton and Raman (2010), Randall et al (2006), Rumyantsev and Netessine (2007), and Jain et al (2013). Industry-specific papers include those by Olivares and Cachon (2009) and Cachon and Olivares (2010), which identify the key drivers that explain the variation in the finished goods inventory within the automotive distribution system.…”

Drivers of Finished-Goods Inventory in the U.S. Automobile Industry

“…We focus on finished-goods inventory performance over a larger section of the supply chain (assembly plant down to retailer/dealer), and because we concentrate on one product category (automobiles), we are able to obtain more detailed data on other factors that influence inventory performance. Rumyantsev and Netessine (2007) use aggregate inventory data of public U.S. companies to measure the relationship between demand uncertainty, lead times, gross margins, and firm size on inventory levels. We include similar covariates in our study.…”

Are Inventories Accretive? Lessons from Inventory and Earnings Relationship in the U.S. Capital Goods Sector

“…With a fixed numerator, a larger production reduces average fixed cost per unit. A lower average fixed cost may, in turn, increase the gross margin thereby increasing the attractiveness of higher inventory maintenance (Rumyantsev and Netessine 2007, Li, Min et al 2008, Kesavan, Gaur et al 2010, Kesavan and Mani 2013, Li, Lundholm et al 2013). …”