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David Berman Essay

David Berman reviewed the macroeconomic numbers on inventory turns as he prepared for his regular appearance on CNBC’s “Squawk Box” as a morning co-host. A leading expert on “consumer related” stocks, Berman and his colleagues including portfolio manager Steve Kernkraut, a seasoned retail executive and analyst, were frequent contributors to various TV shows. On April 4th 2005, Fortune magazine ran a story on Berman called “King of the Retail Jungle”, and on December 13th, 2004, Barron’s ran a story called “Smart Shopper” where Berman’s four stock picks as identified, appreciated 30% on average over the next quarter. “Off air” he was a fund manager as well as founder and president of Berman Capital (which managed proprietary funds) and founder of and general partner in New York-based Durban Capital, L.P. (which managed outside and proprietary capital). Glancing at his notes on macro trends in retail inventory turns, Berman wondered if he should talk about his impressions on the show.

Berman held a bachelors degree in finance and masters equivalency in accountancy from the University of Cape Town in South Africa. He had also passed the South African chartered accountant and the United States CPA examinations. Berman obtained his CPA qualification in California while an auditor for Arthur Andersen and Company where he examined the financial statements and operations of a number of retail clients. He had been the auditor of Bijan, the notable men’s upscale clothing store on Rodeo Drive and 5th Avenue. Prior to starting his own funds Berman worked as a portfolio manager and analyst primarily at two Wall Street firms. He evolved his investment style under the tutelage of Michael Steinhardt of Steinhardt Partners, which he joined shortly after graduating with distinction from Harvard Business School in 1991. From 1994 to 1997 Berman worked in consumer-related stocks at another large hedge fund. He subsequently launched Berman Capital in 1997 and Durban Capital in 2001.

Professor Ananth Raman of Harvard Business School, Professor Vishal Gaur of the Stern School of Business at New York University, and Harvard Business School Doctoral Candidate Saravanan Kesavan prepared this case. Certain details have been disguised. HBS cases are developed solely as the basis for class discussion. Cases are not intended to serve as endorsements, sources of primary data, or illustrations of effective or ineffective management.

Copyright © 2005 President and Fellows of Harvard College. To order copies or request permission to reproduce materials, call 1-800-545-7685, write Harvard Business School Publishing, Boston, MA 02163, or go to http://www.hbsp.harvard.edu. No part of this publication may be reproduced, stored in a retrieval system, used in a spreadsheet, or transmitted in any form or by any means—electronic, mechanical, photocopying, recording, or otherwise—without the permission of Harvard Business School.

Copying or posting is an infringement of copyright. [email protected] or 617-783-7860. 605-081David Berman

Berman believed that his training as an accountant together with his MBA and practices he developed over the years to refine accounting estimates enabled him to notice aspects of retail accounts that would be missed by most investors. The relationship between inventory and earnings and therefore share price, for example, while obvious to a retailer, was seldom recognized by analysts or investors. “This relationship,” Berman observed, “is ASTOUNDINGLY powerful, but surprisingly few understand why. Most think it’s just a function of inventory risk. It’s not. It’s primarily a function of how the operating margins can be manipulated by management in the short term by playing around with inventories”. “For example,” said Berman, “if a retailer’s inventories are growing much faster than sales, then gross margins would be higher than they ordinarily should be, as the retailer has not taken the mark-downs that a solid disciplined retailer should take.”

“Interestingly,” Berman beamed, “there is no law in GAAP that limits the number of days’ inventory to any “norm,” and as such, the practice of increasing inventories beyond any “norm” goes unfettered.” Berman continued “managements sign-off on the inventories as being fairly valued, and the auditors pretty much rely on their word.” Berman believed that “from an investor’s perspective, it’s a game of musical chairs; you don’t want to be the last person standing. In other words, you don’t want to be an investor when sales slow and when mark-downs of the bloated inventory finally need to be taken to move the goods”.

The relationship of inventories to sales was also an important one that Berman focused on. “In a period of rising inventories on a square foot basis”, Berman says “it is quite obvious that same store sales should rise as the offering to the customer is that much greater. Simply put, the more offerings you put in a store, ceteris paribus, the bigger sales should be.” “It is at this time,” Berman argued, “that the stock price rises, as investors place higher valuations on retailers with higher sales, despite that this higher valuation is achieved primarily due to the higher inventories”.

An excellent example of the inventory to sales relationship was Home Depot:

In 2001 and 2002 Home Depot’s new CEO, Bob Nardelli1, seemed to struggle in managing the transition from a cash-flow GE-type philosophy to a retailer Home Depot-type philosophy. In his DeeBee Report2 dated June 10th 2003, Berman stated: “Bob Nardelli learned the power of inventory the hard way. In focusing on cash flow improvement, he dramatically lowered inventories – and yes, increased cash balances – only to see a huge decline in same store sales, and in its stock price {the stock went from around $40 to $22}. And so, under immense pressure, Nardelli reversed course and focused intensely on increasing inventories. Since Q2 of last year, inventories had been building until they were up 25% year over year. And yes, same store sales did improve, as did the stock price.”

Recognizing this as potentially a short-fix, Berman continued “Now the cynical would view this increase in sales with skepticism, noting that it wasn’t of “high quality” as it was due, in part, to the massive inventory build. It is, however, pleasing to note that Home Depot simply got inventories back to “normal”, in that it now has turns similar to its’ competitors”. The stock, following the same store sales and earnings increases, which in essence followed the inventories increase, rose from $22 at the start of 2003 to $36 by the end of 2003. When asked about this “fix”, Berman responded “it will be more challenging for Nardelli to increase same store sales and margins going forward because his increasing inventories and therefore same store sales is arguably a one-time benefit and is essentially what caused the “fix”. Berman concluded by

1 Nardelli had worked at General Electric (GE) before taking over as CEO of the Home Depot.

2 A periodic report where Berman discusses his thoughts on retail, focusing on inventories.

Given his insights as articulated, Berman believed his fund could value firms more accurately through better valuation of inventory. This was pivotal to his investment strategy. “You see,” Berman elaborated, “Wall Street basically ignores inventory. It’s actually quite amazing to me! This gives us one of our edges.” Comparing recently gathered retailer numbers that examined total sales in the U.S. economy to total inventory, for almost 300 retailers, Berman remarked: “The total sales to total inventory numbers is also a crucial relationship over time, and it gives us a macro edge, if that’s possible to believe. Indeed, at the end of Q2, 2003 I knew there would be serious inventory rebuilding in the economy going forward, as overall sales had grown at a faster rate than inventories. Indeed, in Q3, 2003 we saw a rapid and unexpected increase in GDP from 2.3% to 3.5% thanks in part to inventory rebuilding. This increase continued through Q1, 2004 when GDP growth reached 5%.”

Berman loved to discuss investment opportunities he had spotted by looking carefully at firm inventory:

One of the clearest examples was Saucony (Nasdaq: SCNYA), a shoe company based near Boston, MA. Berman identified this company as a strong buy when he noticed in 2003 that even though sales were flattish, inventories had declined about 20% year over year. To Berman, this bode well for future gross margins. He started buying the stock at $14 in late 2003 due primarily to these lean inventories, despite that the stock was illiquid thus presenting greater risk, and despite that management was remarkably coy about sharing information. A year later, the stock had doubled. During this time period, sales rose, as did inventories, and of course, the gross margin expanded significantly, as expected.

Earnings per share rose from $0.85 in 2002 to $1.29 in 2004. Berman’s selling, which came shortly after management asked him to ring the Nasdaq bell with them, was again based on a function of his inventory analysis. This time it was the opposite scenario – inventories were now growing at the same pace as sales, so the trend of sales to inventories had deteriorated – and Berman was worried. To make matters worse, calls to management were not being returned. Sure enough, in March 2005, before Berman had gotten out of this illiquid position, Saucony announced it would miss earnings estimates and the stock cratered 20%.

Yet another clear example was Bombay (NYSE: BBA). In November 2003, Bombay Company, a fashionable home accessories, wall décor, and furniture retailer, announced that sales were up 19% with inventories up 50% year over year. While the retailer beat earnings estimates, the company spoke of early November sales weakness, and the stock declined 20% that day to $10. Despite the decline, and noticing that inventories were up way too much, Berman felt the “music had stopped.” “Going into Q4 it was clear they would have to miss numbers again unless the consumer saved them, which would be a shocker”, he said. Just over two weeks later they lowered earnings again and the stock crated another 20% to $8. Remarkably, just four weeks later, after Christmas, management lowered earnings yet again, and the stock declined yet another 20%. “It was so sweet” exclaimed Berman, “to see the classic inventory / earnings relationship at work so quickly.” In just one and a half months, the stock declined 50% primarily because of inventory mismanagement along with weaker sales.

As Berman prepared to leave for the studio, Christina Zinn, a young apprentice he had just hired from Harvard Business School, walked in and presented him with a stack of papers containing the valuation of John B. River (John B. River Clothiers, Inc. NASDAQ: JONR). “JONR is undervalued,” Zinn remarked, “and I think we should invest in this stock. Sales were up 24% in 2004 over the previous year, and gross margins, having risen for four straight years, seem to have peaked at 60% (one of the highest gross margins in all of US retail).

2005, the company’s price/earnings ratio is less than that of its primary competitor, Men’s Wearhouse, which is at 17.5 times estimated earnings. This is particularly strange given that John B. River has been growing faster than Men’s Wearhouse during the last few years.”

Inventory Productivity in the Retail Sector

Inventory turnover, the ratio of cost of goods sold to average inventory level, was commonly used to measure the performance of inventory managers, compare inventory productivity across retailers, and assess performance improvements over time.3 But wide variations in the annual inventory turnover of U.S. retailers year to year not only across, but also within, firms made it difficult to assess inventory productivity in practice, as evidenced by the following example and questions.

Between 1987 and 2000 annual inventory turnover at Best Buy Stores, Inc. (Best Buy), a consumer electronics retailer, ranged from 2.85 to 8.53. Annual inventory turnover at three peer retailers during the same period exhibited similar variation: at Circuit City Stores, Inc. from 3.97 to 5.60; at Radio Shack Corporation from 1.45 to 3.05; and at CompUSA, Inc. from 6.20 to 8.65. Given such variation how could inventory turnover be used to assess these retailers’ inventory productivity? Could these variations be correlated with better or worse performance? Could it be reasonably concluded from this example that Best Buy managed its inventory better than Radio Shack?

Inventory turnover could be correlated with other performance measures. Strong correlations, as between inventory turnover and gross margin, might have implications for the assessment of retailers’ inventory turnover performance. (Figure 1 plots the four consumer electronics retailers’ annual inventory turnover against their gross margins (the ratio of gross profit net of markdowns to net sales) for the period 1987-2000.)

Relationships among Management Measures

Relationships among inventory turns, gross margins, and capital intensity were central to deriving suitable benchmarks for assessing corporate performance. (Figure 2 presents a simplified view of an income statement and balance sheet. Table 1 presents mathematical definitions for inventory turnover, gross margin, capital intensity, return on assets, sales growth, and other management measures based on Figure 2 .)

Whereas return on assets, sales growth, return on equity, and financial leverage tended not to vary systematically from one retail segment to another, variation in the components of return on assets was observed between and within industry segments. (Table 2 lists retail segments4 and examples of firms.) Table 3 presents gross margins, inventory turns, GMROI5, and asset turns for supermarkets, drugstores, convenience stores, apparel retailers, jewelry retailers, and toy stores.) Retailers with stable, predictable demand and long product lifecycles such as grocery, drug, and convenience stores tended to have better “efficiency ratios” (asset turns and inventory turns) than other retailers, retailers of short lifecycle products such as apparel, shoes, electronics, jewelry, and

An alternative measure of inventory productivity, days of inventory, could be substituted for inventory turnover for the present analysis.

Classification of segments is based on S&P’s Compustat database.

GMROI is defined as gross margin return on inventory investment.

Variation in gross margins, inventory turns, and SG&A expenses within and between segments

ROE could be decomposed into gross margin and inventory turns, and further into the relationship between capital intensity and inventory turns (see below).Anticipating roughly similar ROE measures for different retailers, all else remaining equal, a change in any of the component metrics on the right side of the equation would be expected to result in a compensating change in some other component metric. For example, for ROE among retailers to be equivalent a retailer with higher gross margins would need to experience a compensating change in some other component, such as inventory turns.

Gross margin and inventory turns:

Gross margin and inventory turns were expected to be negatively correlated, that is, an increase in gross margin was expected to be accompanied by a decrease in inventory turnover. A retailer that carried a unit of product longer before selling it (i.e., a retailer with slower inventory turns) would expect to earn substantially more on its inventory investment than a retailer that carried the inventory item for a shorter period. For example, Radio Shack, which turned its inventory less frequently than twice a year, was expected to realize higher gross margins on each sale than retailers such as CompUSA, which turned its inventory more than eight times per year. Retailers such as Radio Shack were said to be following the “profit path” (i.e., earning high profit with each sale), retailers such as CompUSA the “turnover path” (i.e., earning quickly after making an inventory investment small profits with each sale).

Retailers within the same segment were expected to achieve equivalent inventory productivity. Inventory productivity could be estimated as the product of a firm’s gross margins and inventory turns, termed gross margin return on inventory investment or GMROI (pronounced “JIMROY”). If GMROI remained stable within a segment an inverse relationship between gross margin and inventory turns would be observed. (Figure 3 depicts the expected relationship.)

A correlation between gross margin and inventory turns, although expected, did not, however, imply a causal relationship between the two variables. That is, a firm that increased its gross margin by better managing its inventory turns would not necessarily decline commensurately. The correlation between gross margin and inventory turns could instead reflect mutual dependence on the characteristics of a retailer’s business.

Capital intensity and inventory turns:

Investments in warehouses, information technology, and inventory and
logistics management systems involved capital investment, which, being accounted for as fixed assets, was measured by an increase in capital intensity. Firms that made such capital investments often enjoyed higher inventory turns. Hence, inventory turns could be positively correlated with capital intensity.

That an increase in inventory turnover and concurrent decrease in gross margin was not necessarily indicative of improved inventory management capability suggested limits to the use of inventory turnover in performance analysis. If, however, two firms had similar inventory turnover and gross margin values but different capital intensities the firm with the lower capital intensity might possibly have better inventory management capability. It was thus desirable to incorporate changes in gross margin and capital intensity into evaluations of inventory productivity.

Zinn’s Analysis of John B. River

Berman fidgeted in his chair. He enjoyed opportunities to evangelize to and educate television audiences, but found the wait in the studio tedious. Until called to hold forth on various aspects of managerial performance and investment strategy he would, he decided, wade through the report Zinn had prepared for him.

Company Background

On November 8, 2004 John B. River Clothiers, Inc., a leading U.S. retailer of men’s tailored and casual clothing and accessories, opened its 250th store. The retailer employed, in addition to the physical store format, two other channels: catalogs, and the Internet. Production of John B. River’s designs according to its specifications was contracted to third party vendors and suppliers.

John B. River’s product suite, intended to dress a male career professional from head to toe, was identified with high quality and value. Its upscale, classic product offerings included tuxedos, blazers, shirts, ties, vests,
pants, and sports wear. Excepting branded shoes from other vendors, all products were marketed under the John B. River brand.

Trends in workplace clothing were an important determinant of John B. River sales growth. Thus, the early 1990s trend towards acceptability of informal clothing in the workplace was cause for concern to a retailer that emphasized men’s formal suits. But in the early 2000’s the pendulum seemed to swing back, with increasing numbers of employees preferring to dress more formally for the workplace.

The material in this section is from John B. River Clothiers, Inc’s 2004 10-K Statement

Retail stores were John B. River’s primary sales channel. Eighty percent of store space was dedicated to selling activities, the remaining 20% allocated to stockroom and tailoring and other support activities. Tailoring was a differentiating service highly valued by the retailer’s clientele. John B. River catered to high-end customers and so located its retail stores in areas with appropriate demographics. Its seven outlet stores provided a channel for liquidating excess merchandise.

John B. River’s catalog and Internet channels accounted for approximately 11% of net sales in fiscal 2003 and 12% of net sales in fiscal 2002. Approximately eight million catalogs were distributed over these two years. Catalog sales were supported by a toll-free number that provided access to sales associates.

The primary competitors of John B. River were Men’s Wearhouse Inc. (Ticker: MW) and Brooks Brothers (privately held). Apart from competing with these specialty retailers, John B. River competed with large department stores such as Macy’s and Filenes, which enjoyed substantially greater financial and marketing resources.

Supply Chain

John B. River’s merchandise buying and planning staff used sophisticated information systems to convey product designs and specifications to suppliers and third party contract manufacturers and manage the production process worldwide. Approximately 24% of product purchases in fiscal 2003 were sourced from U.S. suppliers. Mexico accounted for 15% and none of the other countries from which products were sourced accounted for more than 10% of purchases. An agent was employed to source products from countries located in or near Asia.

All inventory was received at a centralized distribution center (CDC), from which it was redistributed to warehouses or directly to stores. Store inventory was tracked using point-of-sale information and stock was replenished as necessary. John B. River expected to spend between $3 and $4 million in fiscal 2004 to increase the capacity of its CDC to accommodate 500 stores nationwide.

Growth Strategy and Risks

John B. River had developed a five-pronged strategy for achieving growth. First, it planned to further enhance product quality by elevating standards for design and manufacture. Second, it planned to expand catalog and internet operations. Third, it intended to introduce new products. Fourth, it was moving towards eliminating middlemen from the sourcing of products Fifth, it was committed to providing consistently high service levels by maintaining high inventory levels.

Anticipating that growth relied on opening new stores, John B. River planned to expand to 500 stores. Approximately 60 stores were opened in fiscal 2004, increasing store count to 273, and about 75 to 100 stores were planned from 2005-08. Upfront costs associated with opening a new store included approximately $225,000 for leasehold improvements, fixtures, point-of-sale equipment, and so forth and an inventory investment of approximately $350,000, with higher inventory levels during peak periods.

John B. River’s growth strategy was sensitive to consumer spending. John B. River relied on its emphasis on classic styles to retain a niche in men’s suits, a strategy that rendered it less vulnerable to changes in fashions but dependent on continued demand for classic styles.

Zinn’s Analysis of John B. River’s Financial Statements


John B. River used the first-in-first out method to value inventory. During price increases FIFO valuation generated higher net income than LIFO valuation. John B. River’s inventory had been growing rapidly over the past four years. Zinn was surprised by the inventory growth, especially that inventory had grown faster than sales. Although inventory grew by 54% in 2003, corresponding sales growth was only 23%. In 2004 however, sales grew 24% while inventory grew by only 4%. Inventory at the end of 2004 however continued to be high at 303 days. Further the days’ payables increased from 54 days in 1998 to 82 days in 2004. Payables as a percentage of inventory however had declined from roughly 33% in 1998 to roughly 27% in 2004. But Zinn was not sure these concerns had much impact on her valuation of the company.

Financial ratios:

Current ratio and quick ratio had been hovering around 2 and 0.2, respectively.10,11 The large difference between these two ratios reflected the fact that most of John B. River’s current assets were inventory. Obsolescence costs would consequently be fairly high and could place the retailer in financial distress.

The other financial ratios were indicative of a healthy company. ROE had increased from 15% to 27% since fiscal 2000. This increase had been largely fueled by an increasing profit margin (0.7% to 5.5% over the same period).

John B. River had enjoyed rapid growth in sales over the last few years. Annual Sales growth had increased from 9% in 1998 to 24% in 2004, fueled by sales growth in existing stores (approximately 8% per year) as well as the opening of new stores and increased sales from the retailer’s catalog and internet channels. John B. River enjoyed a healthy increase in gross margins from 51% to 60% over the same period. Tables 4 and 5 provide key operational metrics for John B. River and Men’s Wearhouse.

Prospective Analysis:

Zinn had taken the Business Analysis and Valuation (BAV) class at HBS and discovered the “BAV tool.”12 She had used this tool to create a simpler model (used in the present analysis) to capture key aspects of valuation. Table 6 provides some key historical operational metrics for John B. River that Zinn used for her prospective analysis.

Current ratio, defined as the ratio of current assets to current liabilities, was an indicator of a company’s ability to meet short-term debt obligations; the higher the ratio the more liquid the company.

Quick ratio (or acid-test ratio), defined as the ratio of (cash + accounts receivable) to current liabilities, measured a company’s liquidity.

The BAV tool was an Excel-based model developed by Harvard Business School faculty for valuing companies.

Key assumptions made by Zinn in performing the prospective analysis of John B. River included the following.

1) Time horizon: Zinn chose a five year time horizon from 2005 to 2009 based on expected sales growth (derived from management projections). Beyond 2009 Zinn assumed the company to have reached a steady state defined by terminal values.

2) Sales growth: Zinn assumed that management’s projections for new stores were reasonable and that the new stores would be equivalent in size and productivity with the retailer’s existing stores. Using growth assumptions about stores and same store sales, Zinn computed sales growth for fiscal years 2005-2008 to be 18% (based on 15% square footage growth and 3% same store sale growth), and 10% for 2009. Sales after 2010 in Zinn’s analysis were expected to grow at the 4% industry standard for retail apparel stores13.

3) Gross margin: Gross margin had been steadily increasing; Zinn expected it to hover around 60% for the next five years and then assumed gross margin to reach its terminal value to reflect increased competition.

4) Other assumptions about the income statement: Zinn assumed that SG&A to sales and other operating expenses to sales would continue at the 2004 levels for the near term (till 2008).

5) Assumptions about the balance sheet: Zinn assumed that current assets to sales, current liabilities to sales, and long term assets to sales would continue at their 2004 levels, that is, the company would maintain a similar capital structure and remain as productive with its long term assets as in 2003. Zinn obtained terminal values from industry norms for “Men’s and boys’ clothing stores”14. The market risk premium was assumed to be 5%, risk free rate 4.3%, marginal tax rate 42%, and cost of debt 4.5%. Based on these assumptions, the value of a JONR share was estimated to be $43.58. Given the current (April 11th, 2005) closing price of $34.37 (see Figure 4 for historical stock prices of JONR), Zinn rated the stock a “strong buy.”

You’re On the Air in Five Minutes!

Berman knew he had to return to thinking about the bigger questions that would be posed by the host of the TV show. Yet he could not take his mind off of Zinn’s analysis. Berman smiled, knowing that his apprentice’s results were diametrically opposed to his own intuition. He recollected his conversation with the CEO and CFO of John B. River during one of the quarterly earnings calls when he was trying to learn about the retailer. When questioned about the steep increase in inventory, the CEO had mentioned that John B. River was planning to grow inventory in certain basic items like white shirts, khaki pants etc. as well as increase product variety to enhance service levels to its customers. Berman was not sure about this strategy of John B. River and wondered if the company’s gross margins were temporarily inflated based on increased inventories over the years. On the other hand, inventory management had improved of late. As reported on the 4th April 2005, Q4, 2004 sales had increased 24% while inventories were up only 4% year over year.

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