Ananth Raman

Reducing the Cost of Demand Uncertainty Through Accurate Response to Early Sales

Traditionally, fashion products have incurred high losses due to stockouts and inventory obsolence because long lead times coupled with a concentrated selling season force all or at least most production to be committed before demand information is available. Under a Quick Response system, lead times are shortened sufficiently to allow a greater portion of production to be scheduled in response to initial demand. We model and analyze the decisions required under Quick Response and give a method for estimating the demand probability distributions needed in our model. We applied these procedures with a major fashion skiwear firm and found that cost relative to the current informal response system was reduced by enough to increase profits by 60%. Relative to the cost that would have been incurred if no response were used, optimized response reduces cost by enough to roughly quadruple profits.

Inventory Record Inaccuracy: An Empirical Analysis

Traditional inventory models, with a few exceptions, do not account for the existence of inventory record inaccuracy (IRI), and those that do treat IRI as random. This study explores IRI observed both within and across product categories and retail stores. Examining nearly 370,000 inventory records from 37 stores of one retailer, we find 65% to be inaccurate. We characterize the distribution of IRI and show, using hierarchical linear modeling (HLM), that 26.4% of the total variance in IRI lies between product categories and that 2.7% lies between stores. We identify several factors that mitigate record inaccuracy, such as inventory auditing practices, and several factors that exacerbate record inaccuracy, such as the complexity of the store environment and the distribution structure. Collectively, these covariates explain 67.6% and 69.0% of the variance in IRI across stores and product categories, respectively. Our findings underscore the need to design processes to reduce the occurrence of IRI and highlight factors that can be incorporated into inventory planning tools developed to account for its presence.

An Econometric Analysis of Inventory Turnover Performance in Retail Services

Inventory turnover varies widely across retailers and over time. This variation undermines the usefulness of inventory turnover in performance analysis, benchmarking, and working capital management. We develop an empirical model using financial data for 311 publicly listed retail firms for the years 1987-2000 to investigate the correlation of inventory turnover with gross margin, capital intensity, and sales surprise (the ratio of actual sales to expected sales for the year). The model explains 66.7% of the within-firm variation and 97.2% of the total variation (across and within firms) in inventory turnover. It yields an alternative metric of inventory productivity, adjusted inventory turnover, which empirically adjusts inventory turnover for changes in gross margin, capital intensity, and sales surprise, and can be applied in performance analysis and managerial decision making. We also compute time trends in inventory turnover and adjusted inventory turnover, and find that both have declined in retailing during the 1987-2000 period.

Optimizing Inventory Replenishment of Retail Fashion Products

We consider the problem of determining (for a short lifecycle) retail product initial and replenishment order quantities that minimize the cost of lost sales, back orders, and obsolete inventory. We model this problem as a two-stage stochastic dynamic program, propose a heuristic, establish conditions under which the heuristic finds an optimal solution, and report results of the application of our procedure at a catalog retailer. Our procedure improves on the existing method by enough to double profits. In addition, our method can be used to choose the optimal reorder time, to quantify the benefit of leadtime reduction, and to choose the best replenishment contract.

Do Inventory and Gross Margin Data Improve Sales Forecasts for U.S. Public Retailers

Firm-level sales forecasts for retailers can be improved if we incorporate cost of goods sold, inventory, and gross margin (defined by us as the ratio of sales to cost of goods sold) as three endogenous variables. We construct a simultaneous equations model, estimated using public financial and nonfinancial data, to provide joint forecasts of annual cost of goods sold, inventory, and gross margin for retailers using historical data. We show that sales forecasts from this model are more accurate than consensus forecasts from equity analysts. Further, the residuals from this model for one fiscal year are used to predict retailers for whom the relative advantage of model forecasts over consensus forecasts would be large in the next fiscal year. Our results show that historical inventory and gross margin contain information useful to forecast sales, and that equity analysts do not fully utilize this information in their sales forecasts.

Store Manager Incentive Design and Retail Performance: An Exploratory Investigation

Store managers perform multiple tasks within a store, and the way in which they are evaluated and rewarded for these tasks affects their behavior. Using empirical data from multiple stores of a consumer electronics retailer, Tweeter Home Entertainment Group, we highlight the extent to which store manager incentive design impacts store manager behavior and, consequently, retail performance. More specifically, we describe the shift in store manager behavior resulting from a change in incentives, which, in part, altered the importance of sales relative to inventory shrinkage in the store manager compensation plan. Store managers, following this change, directed less attention to the prevention of inventory shrinkage and more toward sales-generating activities and made different process choices within the store. We observed increases in the level of inventory shrinkage and sales within these stores. Controlling for alternative drivers of sales and inventory shrinkage, we find this change in incentive design to be associated with a profit improvement of 4.2% of sales. This work indicates that altering how store managers are compensated impacts retail performance. Moreover, our findings underscore the importance of balancing the rewards given for different types of activities in contexts where agents face multiple competing tasks.

Managing Inventory for Fashion Products

With lifecycles becoming shorter and demand more uncertain in growing numbers of product categories, more and more companies, in industries as diverse as personal computers, toys, and even agricultural chemicals, are being forced to deal with stockouts and markdowns, problems usually associated with businesses like apparel and footwear. These changes have been attended by increased attention by managers in these industries to fill rates, inventory turns, and product obsolescence, topics studied extensively in management science models that traditionally have focused on fashion products.1

Analysis of Distribution Strategies in the Industrial Paper and Plastics Industry

The costs, benefits and strategic role of intermediate echelons in distribution networks are not well understood in many industries. This paper describes a study of such multilevel systems in the industrial paper and plastics industry. We quantify the impact of redistributors, who buy products from manufacturers and sell them exclusively to other distributors. The methodology was applied to an industry-wide study. We derived statistics based on optimal distributor policies for channel choice and stock control. Based on our analysis, we found that effective use of redistribution, in conjunction with these policies, has the potential to generate savings of

Retail Inventory: Managing the Canary in the Coal Mine!

446 million for the industry.

Call for Papers---Proposal for an M&SOM Special Issue on Practice-Focused Research

Retail inventory is a statistic that is closely watched by retailers as well as their investors, lenders, and suppliers. Retailers not only benefit from inventory, but also bear the cost of excess inventory. Investors, lenders, and suppliers interpret this statistic for signs of the retailers health, future sales prospects, and impending costs. This article synthesizes the perspectives of investors, lenders, and suppliers on inventory. Moreover, the article shows that inventory turns, a commonly used metric to identify excess inventory, has important limitations that reduce its utility for all these stakeholders. It then presents a new metric, adjusted inventory turns, which can be effectively utilized by all stakeholders to assess whether a retailer is carrying too much or too little inventory.