Saravanan Kesavan

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.

Effect of Traffic on Sales and Conversion Rates of Retail Stores

Attracting shoppers to stores and converting the incoming traffic into sales profitably are vital for the financial health of retailers. In this paper, we use proprietary data pertaining to an apparel retailer to study the relationship between store traffic, labor, and sales performance. We decompose sales volume into conversion rate (defined as the ratio of number of transactions to traffic) and basket value (defined as the ratio of sales volume to number of transactions) and analyze the impact of traffic on sales and its components. We find that store sales volume exhibits diminishing returns to scale with respect to traffic, and labor moderates the impact of traffic on sales. For example, we find that for values of traffic and labor corresponding to the mean, increasing average traffic per hour by one unit increases average sales volume per hour by

Volume Flexibility in Services: The Costs and Benefits of Flexible Labor Resources

9.97. Further, we find that the marginal returns to traffic increases from

The effects of firm size and sales growth rate on inventory turnover performance in the U.Sretail sector

10.00 to

Retail Inventory: Managing the Canary in the Coal Mine!

11.32 when labor increases by one standard deviation. In addition, we find that the conversion rate declines with increasing traffic and a lower conversion rate is associated with a decrease in future traffic growth. Our study underscores the importance of in-store operations in driving the financial performance of retailers.

The Predictive Power of Abnormal Inventory Growth: Application to Earnings Forecasting for Retailers

Organizations can create volume flexibility---the ability to increase capacity up or down to meet demand for a single service---through the use of flexible labor resources e.g., part-time and temporary workers, as compared to full-time workers. Although organizations are increasingly using these resources, the relationship between flexible labor resources and financial performance has not been examined empirically in the service setting. We use two years of archival data from 445 stores of a large retailer to study this relationship. We hypothesize and find that increasing the labor mix of temporary or part-time workers shows an inverted U-shaped relationship with sales and profit while temporary labor mix has a U-shaped relationship with expenses. Thus, although flexible labor resources can create volume flexibility for a firm along multiple dimensions, it is possible to have too much of a good thing. This paper was accepted by Serguei Netessine, operations management.

Do High and Low Inventory Turnover Retailers Respond Differently to Demand Shocks

Past research shows that inventory turnover varies substantially across firms as well as over time. Gaur et al. (2005) demonstrate that a significant portion of this variation can be explained by gross margin, capital intensity, and sales surprise (the ratio of actual sales to expected sales for the year). Using additional data, we confirm these previously published results. Extending the findings of Gaur et al. (2005), we investigate the effects of firm size and sales growth rate on inventory turnover using data for 353 public listed US retailers for the period 1985-2003. With respect to size, we find strong evidence of diminishing returns to scale. With respect to sales growth rate, we find that inventory turnover increases with sales growth rate, but its rate of increase depends on firm size and on whether sales growth rate is positive or negative. Our results are useful in (i) helping managers make aggregate-level inventory decisions by showing how inventory turnover changes with size and sales growth, (ii) employing inventory turnover in performance analysis, benchmarking and working capital management, and (iii) identifying the causes of performance differences among firms and over time. 1 Johnson Graduate School of Management, Cornell University, Sage Hall, Ithaca, NY 14853. Email: vg77@cornell.edu. 2 Kenan-Flagler Business School, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599. Email: skesavan@unc.edu. 1

An Overview of Industry Practice and Empirical Research in Retail Workforce Management

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.

Increasing Sales by Managing Congestion in Self-Service Environments: Evidence from a Field Experiment

In this paper we test the predictive power of abnormal inventory growth to forecast retailers’ earnings. We demonstrate an inverted-U relationship between abnormal inventory growth and one-year ahead earnings per share for retailers. We find this relationship to be robust to different measures of abnormal inventory growth obtained from operations management literature. Our results also show that equity analysts do not fully incorporate the information contained in abnormal inventory growth in their earnings forecasts resulting in systematic biases in their earnings’ forecasts. We show that incorporating this information in analysts’ forecasts would improve their forecast accuracy. This improvement can be as much as 15.08% for overinventoried retailers that are identified based on previous year’s abnormal inventory growth.

Estimating Demand Uncertainty Using Judgmental Forecasts

This paper examines the differences in the behaviors of high (HIT) and low inventory turnover (LIT) retailers in responding to demand shocks. We identify quantity and price responsiveness as two mediating mechanisms that distinguish how high and low inventory turnover retailers manage demand shocks. Using quarterly firm-level data of 183 U.S. retailers between 1985 and 2012, we find that HIT retailers are able to respond quickly by changing their purchase quantities in response to demand shocks, whereas LIT retailers primarily rely on price changes to manage demand shocks. In addition, we examine the differential implications of these mechanisms on the financial performance of HIT and LIT retailers. We find price responsiveness to be a less effective strategy, compared to quantity responsiveness, in reducing excesses and shortages of inventory. Finally, the negative financial impact of a given amount of excess and shortage of inventory is eight times more severe for LIT retailers compared to HIT retailers.