“For retailers that aggressively open new stores, the reported SSS metrics are helpful, but far from complete. Rather, an investor would want to know how the stores greater than four years old are doing from a sales and profit perspective and how much money is being invested in those stores. In addition, an investor would like to know what is being spent on the newer stores and how they are performing from both a sales and profit standpoint. Without that information, any interpretation of SSS performance lacks real meaning. But so often today, SSS figures are cited without providing that critical additional information – giving investors only part of the picture.”
—Edward S. Lampert, Chairman of the Board, Sears Holdings
Same-Store Sales: An Important (and Overrated?) Metric for Retail Performance
It’s Sunday today and outside my window the sun is actually shining. After getting some fresh air and sun in the face, it’s time to do the best to become a little wiser. Today we will dig into the topic of same-store sales.
First, we will read an excerpt about same-store sales from Eddie Lambert’s 2005 letter from the chairman. Lampert is the Chairman and CEO of Sears Holding Chairman, and he also is the Chairman and Chief Executive Officer of ESL Investments, Inc., which he founded in April 1988.
Second, we take a look at an excerpt from an article written by Howard Schilit, author of the great book Financial Shenanigans. In this article Schilit discusses same-stores sales and the potential pitfalls an investor should be aware of.
Let’s go. Enjoy (emphasis added).
The discussion of profitable growth brings me to the issue of same-store sales, and why I believe it is not always the best measure of a retailer’s performance. Many analysts and commentators focus on same-store sales (SSS) as the most important statistic in retail, almost to the exclusion of any other statistic (even above profit). I consider SSS to be an important metric for retail performance, but one that is vastly overrated. Like any single metric, SSS has significant limitations. Let me offer a framework to help explain my thinking on SSS and why we do not rely on it to judge our success at Sears Holdings to the degree others in our industry do.
If we take a simple example of a single store, then a comparison of SSS from year to year is fairly straightforward. If a store does $1 million in sales at a 10% operating margin this year, generating $100,000 in operating profit, and does $1.1 million in sales next year at the same operating margin of 10% generating $110,000 in operating profit, it will report a 10% increase in SSS. Now, let’s add another dimension. Imagine that this same store spent $500,000 to improve the store experience during that year. The 10% increase in SSS generated an additional $10,000 in profit. Whether the $500,000 investment makes sense or not in hindsight will depend on the future performance of the store. Obviously, if the store only improves by the $10,000 in profit, the $500,000 investment doesn’t make sense. I believe that companies that pursue SSS growth at any cost often fall victim to these traps.
In reality, the calculation of SSS becomes even more difficult. Individual retailers are opening, closing, and remodeling stores all the time. In this context, the simple comparison of a single store breaks down. Let me explain. Imagine that a new store opens on January 1, 2006. In the first year of operation, this store would be excluded from a company’s calculation of SSS because most calculations only include stores that have been open at least a year. A retail store matures over time and the first year of sales is often at a level that is a fraction of its potential. If we assume that a store opens at 60% of potential and matures to potential over four years, we know that this store will grow by 67% over that period of time (from $6 million to $10 million, let’s say). On that $10 million-in-sales store that opens at $6 million in year 1, the SSS increase over the next three years will average 18.6% per year, with the higher growth rates occurring in years 2 and 3 rather than year 4.
At the end of that period of time, the $10 million store may be at a relative steady-state, and let’s say it is earning at a 10% operating profit, or $1 million per year. The key question is not how well the store did from a SSS standpoint but rather how much money was invested to generate the $1 million profit. If the store cost $5 million to build, a $1 million profit represents a 20% pre-tax return on investment, which is attractive. However, if the store cost $20 million to build, the 5% return on that investment would not be attractive at all. Nevertheless, regardless of cost, the store would still have reported 18.6% compounded growth in SSS.
Complicating things further and bringing things even closer to reality, the more stores that are opened relative to the outstanding base of stores, the higher the SSS metric a company can produce, regardless of whether the new store openings make economic sense or not. If the mature stores (i.e., those that are over four years old) grow at a 1% rate and the new stores grow at the 18.6% per year rate (remember, it is likely that in years 2 and 3 the rates are materially higher than the 18.6%), then mathematically it is simple to show that the more new stores that are opened, the higher the SSS calculation. Only after a period of years will one know whether the new store investments actually made sense and actually contributed to the creation of value.
With Sears and Kmart, given that we have chosen not to open new stores at the pace of our competition, one can get a more accurate measurement of SSS performance. For retailers that aggressively open new stores, the reported SSS metrics are helpful, but far from complete. Rather, an investor would want to know how the stores greater than four years old are doing from a sales and profit perspective and how much money is being invested in those stores. In addition, an investor would like to know what is being spent on the newer stores and how they are performing from both a sales and profit standpoint. Without that information, any interpretation of SSS performance lacks real meaning. But so often today, SSS figures are cited without providing that critical additional information – giving investors only part of the picture.
In our case, starting with Kmart three years ago, we had many stores that were operating with low levels of profit or at a loss. If we had attempted to sustain our sales levels, it would have been difficult to improve our store and company profitability. By changing the objective from maintaining sales to growing profit, we were able to make a substantial improvement in our company’s profitability. No longer are we carrying excessive inventories, spending excessive amounts on marketing, and scheduling excessive labor dollars all in the pursuit of a given level of sales. Instead, our focus is on understanding our customers and figuring out how to provide them products and services that they value, so that we can build relationships with them and profitably serve them over the long term. While reducing sales is not a prescription for success on a base of healthy, profitable stores, it can be a prescription for success where profit was not the primary objective and where sales came from “giving product away” rather than from providing value to the customer. Improving our stores and our store experience will take time, and I am pleased with the progress that we have made to date.
(Source: Sears Holdings, Letter From the Chairman via Edgar – SEC.gov)
Next, some wisdom from Howard Schilit on the uses and misuses of same-store sales, a key metric for retailers (emphasis added).
Revenue growth at retailers and restaurants is often fueled by the opening of additional stores. Logically, companies that are in the middle of a rapid store expansion show tremendous revenue growth, since they have many more stores this year than they had the prior one. While total company revenue growth may give some perspective on a company’s size, it gives little information on whether the individual stores are performing well. Therefore, investors should focus more closely on a metric that measures how the company’s stores have actually been performing.
To provide investors with that insight, management often reports a metric called “same-store sales” (SSS) or “comparable-store sales.” This metric establishes a comparable base of stores (or “comp base” for short) for which to calculate revenue growth, allowing for more relevant analysis of true operating performance. For example, a company may present its revenue growth on stores that have been open for at least one year. Companies often prominently disclose SSS in their earnings releases, and investors use it as a key indicator of company performance. Many consider same-store sales to be the most important metric in analyzing a retailer or restaurant. We agree that if it is reported in a logical and consistent manner, same-store sales is extremely valuable for investors.
However, because same-store sales fall outside of GAAP coverage, no universally accepted definition exists, and calculations may vary from company to company. Worse, a company’s own calculation of same-store sales in one quarter may differ from the one used in the previous period. While most companies compute their same-store sales honestly and disclose them consistently, “bad apples” try to dress up their results by routinely adjusting their definition of same-store sales. Investors, therefore, should always be alert to the presentation of same-store sales to ensure that it fairly represents a company’s operating performance.
Compare same-store sales to the change in revenue per store. When a company experiences fairly consistent growth, same-store sales should be trending up consistently with the average revenue at each store. By comparing same-store sales with the change in revenue per store (i.e., total revenue divided by average total stores), investors can quickly spot positive or negative changes in the business. For example, assume that a company’s SSS growth has been consistently tracking well with its revenue per store growth. If a material divergence in this trend suddenly appears, with same-store sales accelerating and revenue per store shrinking, investors should be concerned. This divergence indicates one of these two problems: (1) the company’s new stores are beginning to struggle (driving down revenue per store, but not affecting same-store sales because they are not yet in the comp base), or (2) the company has changed its definition of same-store sales (which affects the SSS calculation but not total revenue per store).
This framework was used by the Center for Financial Research and Analysis (CFRA) to successfully identify problems at Krispy Kreme Doughnuts Inc. (KKD) in 2004 and Starbucks Corp. (SBUX) in 2007, and to warn investors before these companies unraveled. As shown in Figure 1, Krispy Kreme maintained its high SSS level in 2003 and 2004, despite a tremendous drop-off in total revenue per store.
Figure 1. Krispy Kreme’s Same-Store Sales Versus Revenue Per Store Growth
Watch for changes in the definition of same-store sales. Companies usually disclose how they define same-store sales. Once the definition is disclosed, investors should have little difficulty tracking it from period to period. Companies can manipulate same-store sales by adjusting the comp base in two possible ways. The first involves simply changing the length of time before a store enters the comp base (for example, requiring a store to be open for 18 months, versus 12 months previously). The second trick involves changing the types of stores included in the comp base (for example, excluding certain stores based on geography, size, businesses, remodeling, and so on).
Watch for bloated same-store sales resulting from company acquisitions. The comp base can also be influenced by unrelated company activities, such as acquisitions. For example, from 2004 to 2006, the universe of stores in the comp base of Starbucks kept changing each quarter as the company continuously bought up its regional licensees and put them into the comp base. As a result, Starbucks calculated same-store sales using a slightly different universe each quarter—hardly a comparable metric. If Starbucks had been purchasing its strongest licensees, this acquisition activity would have had a positive impact on SSS performance, thereby misleading investors about the company’s underlying sales growth.
As with Krispy Kreme, Starbucks’ 2006 same-store sales trend began diverging from its revenue per store trend. The gap widened in 2007, and in September 2007, Starbucks reported that U.S. traffic had fallen for the first time ever. When same-store sales in the United States turned negative in December, Starbucks announced that it would no longer disclose same-store sales, stating that it would “not be an effective indicator of the Company’s performance.”
Be wary when a company stops disclosing an important metric. Just as Starbucks stopped disclosing same-store sales when business went sour, Gateway stopped disclosing the number of computers sold when times were tough in late 2000. This metric had been an important data point provided to investors, and Gateway’s change in disclosure led the SEC to censure the company and label its actions “materially misleading” because it obscured the softening consumer demand for computers.
Look for strange definitions of organic growth. Affiliated Computer Systems (ACS) had an odd way of presenting its organic growth, or what it called “internal growth.” Rather than simply excluding all revenue from acquired businesses when calculating internal growth, ACS calculated a fixed amount to remove based on the acquired business’ revenue for the previous year. This meant that ACS was able to include in its own internal growth any large deals that the acquired company booked just before the acquisition.
(Source: AAII Journal, August 2010)