ECR and grocery retailing: An exploratory financial statement analysis

Efficient Consumer Response (ECR) is a food industry strategy introduced in 1993 in which distributors and suppliers work together to increase value for the consumer (Bowersox et al. 1999, p. 5). "By jointly focusing on the efficiency of the total grocery supply system, rather than the efficiency of individual components, they are reducing total system costs, inventories, and physical assets while improving the consumer's choice of high quality... grocery products." (Salmon 1993, p. 1).

ECR uses four basic strategies to accomplish its goals: efficient store assortment, efficient replenishment, efficient promotion, and efficient product introductions. (The brief descriptions provided below are based on the extensive discussion of ECR by King and Phumpier 1996).

Efficient store assortment is based on modern category management techniques that focus on a limited number of broad product categories instead of many individual products. These categories are managed to meet the specific needs of a store's customers while allowing the retailer to improve efficiency in space utilization by eliminating duplicate products.

Efficient replenishment attempts to improve inventory control and ordering processes through automation. Product receipts and sales are tracked continuously and data on sales and inventory levels are transmitted via Electronic Data Interchange (EDI) from the retailer to the food manufacturer. This allows for lower order processing costs, fewer errors, and reduced inventory in relation to sales, but requires significant investment in information systems and expertise (King and Phumpier 1996, p. 1183-1185).

Efficient promotion is an attempt to change a selling strategy commonly used in the food industry. Typically, food manufacturers offer special low price, large volume deals to promote a product's sale. Retailers buy large quantities of the product and store it until it is eventually sold, thereby increasing inventories and holding costs. (This is called forward buying.) However, the buyer may keep only part of the purchase and re-sell the rest to others in different geographic areas (where the deal is not currently available) thus increasing transport costs. (This is called diverting.) Efficient promotion encourages establishment of somewhat lower manufacturer prices in return for a steady stream of purchases by retailers. This would reduce inventory, transport, and production costs.

Efficient product introduction is an effort to reduce unnecessary costs associated with the introduction of new products that eventually fail. By using consumer demographic data from retailers "Preferred Shopper" programs, it is easier to predict new product success or failure and the types of customers most likely to adopt a potential new product. By eliminating failures earlier in the new product development cycle, total new product development costs can be reduced.

In summary, the grocery supply chain under ECR would have manufacturers, wholesalers, and retailers tied to each other with information systems. Current data on consumer sales would flow from the point of sale back to wholesalers and/or manufacturers; product would flow forward in response. Such a system would allow an even flow of product from producer to consumer that minimizes inventory throughout the system while reducing out of stocks and increasing responsiveness to consumer demands. ECR advocates estimate an overall cost savings of 10.8% from ECR adoption (Salmon 1993, p. 4).

Implementing ECR is a challenging and time consuming task. Significant investment in information technology and expertise is often required. However, the major challenges have to do with people and organizational issues. Employees must be retrained and new organizational structures and measurement techniques adopted.

... organizational barriers are both cultural and functional. The traditional vertical, top-down organization structure, in which each function operates separately and is measured independently, is a major barrier because every ECR change crosses functional boundaries. The measurement systems commonly in use are another major impediment because everyone has been conditioned to focus on the efficiency of individual parts of the system, while no one looks at the whole system (Salmon 1993, p. 4).

Further complicating ECR implementation is the fact that its success requires adoption by a substantial number of firms in the food channel. A retailer or manufacturer must make investments in technology, expertise, and training. These investments will not pay dividends until critical mass, i.e., a large enough volume of business, is reached using ECR procedures. It is believed that the ECR critical mass occurs when about one-third of a firm's business is conducted using ECR procedures (Salmon 1996). No matter how thoroughly one firm in the supply chain adopts ECR, it will not get maximum benefit until enough of its business partners do likewise.

RESULTS TO DATE

A review of the literature on ECR results reveals early progress in implementing ECR (Salmon 1996) but growing disaffection in the trade press. (For a recent literature review, see Stank, Crum, and Arago 1999.) Additional material on ECR and other replenishment programs can be found in Collins 1997; Daugherty, Myers, and Autry 1999; Harris, Swatman, and Kurnia 1999; Hoban 1998; Pearce 1997; Vergin and Barr 1999; Whipple, Frankel, and Anselmi 1999; and Whiteoak 1999).

A recent article concluded that ECR could not achieve its promised savings because retailers and manufacturers would not abandon forward buying (Partch 2000, p. 138). This comment was consistent with other published work. It has been recently suggested "that traditional supply processes characterized by forward deployment of large inventory stockpiles dictated by anticipatory forecasts of consumer demand, have actually increased since 1992" (Stank, Crum, and Arago 1999, p. 21).

Another article, summarizing comments from a panel of six ECR executives, noted that most did not get the level of savings first promised. In response to a question of where ECR had fallen short of expectations, three executives indicated efficient promotion, while the others mentioned forecasting, activity based costing, and category management (Tosh 1998). (For additional critical reviews of ECR from the trade press, see DeSanta 1997; Knill 1997; and Mathews 1997.)

Finally, a 1999 study is the only work found which reports empirical results for food retailers (Bowersox et al. 1999). The study compared annual report data of nine retail grocery chains from 1992 (before ECR) through 1997. Some results are summarized below:

1. Average inventory turns (sales to average inventory) declined slightly.

2. Days inventory increased.

3. Cash to cash cycle was reduced by 5%.

4. Net profit margin increased by 22%.

5. Asset turnover fell 10%10.

6. Return on assets increased 7%.

In summary, the report concludes that food retailers' improved profits have probably come from buying practices (larger volume purchases which generate increased promotional money) rather than through better operating efficiency. It should be noted that the Bowersox et al. report does not specifically say that the nine retailers studied had adopted ECR. Thus, it is impossible to evaluate the results with respect to the efficacy of ECR for retailers.

In conclusion, there exists a wide gap between the promise of ECR that its proponents envision and the perceptions of industry analysts and writers. Why do these widely different perceptions exist? This question gains importance in light of the high visibility ECR has achieved, not just in industry publications but in textbooks and journals. ECR is often cited as a leading example of modern logistics strategy. Thus, research may help explain, or at least suggest possible reasons for the wide disparity in perceptions of ECR.

RESEARCH

The research objective is to determine whether food retailers that have adopted ECR (adopters) improved their operations (measured by financial and operating ratios) following adoption in comparison to grocers that have not adopted ECR (non-adopters). Comparing adopters' performance to non-adopters helps control for "other things," such as changes in the economy, consumer tastes, government regulations, etc. that could affect the outcomes. For example, if the adopters group improved performance by 2% over time, it would appear at first to be a positive outcome for ECR. However, if the non-adopters also improved by the same amount, it would put an entirely different perspective on the efficacy of ECR.

Unfortunately, this research approach is limited for two reasons: first, the firms cannot be assigned randomly beforehand to the two groups (adopters and non-adopters) and second, the project cannot be done "blind," i.e., the status of each firm as adopter or non-adopter is known to the researchers. The lack of random assignment is a weakness because it is possible that firms in one of the groups may have some characteristic or other attribute that determines or affects the outcome. Thus, the research could erroneously attribute the findings to one variable or cause when in fact they are due partially or wholly to others. To help counteract this possibility, the two groups used here will be studied in an attempt to identify systematic differences between them; however, it may be possible that another unknown variable exists that affects the outcome. Finally, the lack of a completely "blind" study is inherent in the situation and cannot be avoided. Sensitivity to the issues involved by the researchers and review by outside parties are probably the best alternatives available.

Financial data for the study (used to calculate financial and operating ratios) came from annual reports required of all publicly owned corporations. Two problems with this approach include data aggregation and sample size. First, the firm's annual reports may aggregate information from several different divisions or business units. If ECR brought about better performance in one division, this might be obscured by results from other divisions not involved with ECR. To help minimize this effect, all the firms in this study were reviewed to be sure they were primarily grocery retailers. Thus, the data reflect primarily retail grocery operations. (One firm was deleted from the study due to the significant volume of non-retail sales they experienced.) Yet the basic problem of aggregation in reporting cannot be eliminated. It is clearly a potential source of measurement error in the study.

A second problem involving annual report data is that it restricts the number and size of firms eligible for the study. Only larger grocers tend to be publicly owned while many food retailers are smaller, privately held firms. Forty grocers were publicly held in 1997, almost all of them among the largest one-third of all grocers (Ward's Business Directory 1998). In addition, some of these publicly held grocers had to be eliminated from the study because complete data (1992-1997) were not available, or they were primarily convenience store operations rather than conventional grocers, or they had a large proportion of sales from non-retail operations. This left twenty-nine firms eligible for the study.

Identifying the ECR status of the eligible retailers proved challenging for both practical and conceptual reasons. A short mail survey was sent to the President of all eligible firms asking openended questions concerning adoption of ECR, year of adoption, results to date, and other comments they wished to make. Follow-up telephone calls were made to non-respondents; in total, twenty-five grocers provided useful responses.

The study divided participating firms into two categories: adopters (firms reporting adopting ECR prior to 1995) and non-adopters (all others). This procedure can be criticized since it treats all adopters the same although they might differ. For example, some early adopters may be more experienced at ECR than later adopters. Also, some firms may have implemented more ECR principles (efficient replenishment, efficient assortment, etc.) than others. Undoubtedly, including more of this information would be interesting and may enhance accuracy, yet there is no reliable way to quantify these factors. In sum, treating all adopters the same is a simplification of reality, a measurement problem that should be eliminated when better information becomes available.

FINDINGS

For the 1992-1997 period, twenty-five firms were included in the study (13 adopters, 12 nonadopters); for the 1992-1998 period, twenty firms were included (11 adopters, 9 non-adopters). Annual report data were collected on inventory levels, sales, cash cycle, asset productivity, and profits. Analysis of the data indicates that adopters are different from non-adopters in two ways: they are generally larger and they grew faster during the 1992-1997 and 1998 time periods. (This finding will be discussed in greater detail later.)

Inventory

One major impact ECR should have is to reduce inventory in relation to sales. To gauge this effect, three inventory ratios (inventory turnover, days inventory, and inventory to sales) were calculated for each firm and for both groups for 1992, 1997, and-when possible-1998. (Formulas used are shown in Appendix A.) Comparing the two groups during 1992 showed no statistically significant differences in the three ratios (see Table 1, Panel 1). However, by 1997 adopters had statistically significantly worse ratios than non-adopters. In fact, during this period, adopters' average inventory turnover ratio fell from 10.2 to 9.7 while non-adopters rose from 11.9 to 12.3 (Table 1, Panel 2). These results continued for 1998. Not surprisingly, the results for days inventory and inventory to sales followed approximately the same pattern. They were not significantly different in 1992, but were significantly different in 1997. In both cases, adopters' ratios were worse than non-adopters, particularly in 1997 (see Table 1, Panels I and 2). To be accurate, from 1992-1997, adopters' days inventory and inventory to sales did improve very slightly in absolute terms, but their comparative position worsened.

Cash Cycle

The cash cycle should improve under ECR when inventory falls in relation to sales. Long cycle times are believed to hide waste and inefficiency much as excess inventory can hide operating problems and low quality in supply and manufacturing. Although it would be interesting to include analysis of other cycles, annual report data do not allow it. From 1992-1997 adopters' cash cycle on average worsened (from 19.1 to 20.9) while non-adopters improved from 18.3 to 11.9. These results (which are statistically significant) continued during 1998 (Table 1, Panels 1, 2, and 3).

Asset Turnover

The asset turnover ratio indicates how efficiently assets are being used in a firm. Adoption of ECR should have a positive effect on asset use and raise the asset turnover ratio. During 1992, there was no statistically significant difference in the ratio between the adopters and non-adopters, and this remained the same for 1997 and 1998 (Table 1, Panels 1, 2, and 3). It is interesting to note that inventory fell as a percent of assets for adopters. Non-inventory assets such as stores and land grew more rapidly than inventory; this is consistent with an aggressive growth strategy. (For ECR adopters, average year-end inventories were 23% greater in 1997 than in 1992, while total assets for the group increased by 41% over the same period. Thus, inventory as a percent of assets fell. The inventory to sales relationship discussed earlier is not correlated closely since sales and assets behaved differently over time.)

Return on Assets

Return on assets (ROA) is a measure of profitability-the higher the ratio, the more profitable. It is important to potential investors since a high ROA is often taken to indicate potential for future profits. No statistically significant differences were found in ROA between adopters and nonadopters during 1992, 1997, and 1998 (Table 1, Panels 1, 2, and 3).

Profit Margin and Gross Profit Percent

A firm's profit margin (Net Income/Net Sales) is a measure of how efficiently it operates. Firms using ECR should show increased operating efficiency due to reduced inventories and less assets. No significant differences were found between the profit margins of adopters and non-adopters during 1992, 1997, and 1998 (Table 1, Panels 1, 2 and 3).

The gross profit percent is a measure of the difference between the price paid for products and the price of those products when sold to customers. (A firm with "high mark-ups" would have a high gross profit percent.) Upon adoption of ECR, a firm's gross profit percent might well fall if it abandoned forward buying and purchased smaller quantities at somewhat higher prices. (Of course, this assumes prices to customers were unchanged.) The fact that there was no statistically significant change (it actually increased slightly) in adopters' gross profit percent over the study period and in relation to non-adopters is consistent with the possibility that adopters did not change their purchasing strategy over the study period.

In summary, the comparison of adopters and non-adopters shows that the adopters' performance worsened comparatively over the study period in terms of inventory and cash cycle. In addition, they have maintained the same relative positioning in terms of asset turnover, return on assets, profit margin, and gross profit percent. Such results are clearly not what ECR proponents originally forecasted.

Firm Size and Growth Rate

As noted earlier, adopter firms were typically larger than non-adopters and experienced faster growth during the study period. Adopters' 1992 sales averaged several times the corresponding figure for non-adopters providing clear evidence that ECR is basically a large firm phenomenon among food retailers. Why is this so? The answer is not clear, but two factors seem plausible. First, large firms have the access to capital needed to make the required investments. Second, large firms may benefit more than smaller grocers. For example, the savings from a new computer system may be much greater for a large volume grocer than a smaller firm even if the original cost of installation and operation is much the same.

Concerning growth, the average sales growth of adopters was statistically significantly higher than non-adopters from 1992-1997 and 1998 (Table 1, Panels 2 and 3). In fact, almost all adopters were growing in sales while half of non-adopters were not.

One important issue here is whether or not the size and/or growth rate of adopters has affected the research outcomes. To investigate the issue, multiple regression analysis was performed using a variety of dependent variables (such as ROA, cash cycle, inventory turnover, etc.) and several independent variables (including sales growth, asset size, asset growth, and ECR). Two statistically significant relationships are noteworthy.

First, size (measured by total assets) was positively correlated with gross profit percent and profit margin (see Table 2, Models 4 and 3). This suggests that large grocers may get lower prices from suppliers than smaller grocers and provides an opportunity and motivation for growth. From the data available, it is impossible to determine why larger grocers apparently get lower prices from suppliers. Certainly their size could give them the market power to gain lower prices through negotiations. (This is an example of what some have termed "pecuniary economies of scale" which are due to lower input prices rather than increased resource efficiency.) Conversely, the apparent lower prices could reflect real operating efficiencies such as transport discounts related to larger shipment sizes. For example, suppliers might reduce prices to large grocers with EDI and other systems in place because of cost savings. Here the lower prices might reflect real resource economies based on use of a more efficient technology by large firms. Finally, both factors could be at work simultaneously.

Concerning this research, we know of no reason to believe that differences in firm size would invalidate the comparison between adopters and non-adopters. In addition, the regression results provide no empirical reason to do so. Thus, firm size differences are assumed to be unimportant to the study findings.

A second relationship involves growth, which is significantly and inversely related to one measure of inventory efficiency. As shown in Table 2, Model 2, sales growth was found to be inversely related to inventory turnover (the more rapid the growth in sales, the lower the ratio). This relationship appeals to common sense in that new stores will often take more than a year to develop the sales levels that they will eventually enjoy.

In contrast, it should be noted that three adopters that grew rapidly from 1992-1997 showed improved cash cycle, better inventory efficiency, and higher gross margins. In other words, rapid growth is not necessarily related to poorer inventory turnover.

DISCUSSION AND CONCLUSIONS

As noted earlier, this research is limited by a number of factors including the small number of firms involved, lack of blind, random assignment to control and experimental groups, the inability to measure the degree of ECR adoption, and potential measurement problems due to aggregation of financial data. Because of these factors, we believe the results are tentative: perhaps best viewed as areas for future research rather than established conclusions. With this caveat in mind, six findings are worth noting.

First, most ECR adopters did not exhibit the positive results forecasted by ECR proponents. As a group, adopters' inventory efficiency, asset efficiency, and cash cycle generally deteriorated in relation to non-adopters. This outcome might help explain the different perspectives of those who believed ECR would work well, and industry journalists who looked for results and didn't find them.

Second, the gross profit percentage of the adopter group grew slightly during the study period. This may mean that adopters increased forward buying which would tend to negate or reduce the inventory and cash cycle benefits of ECR. This finding is consistent with the comments of some industry executives and might help explain why adopters experienced worse inventory and cash cycle efficiency during the study period.

Third, the adopter group tended to be much faster growing than the non-adopters and this might also help explain the reduced inventory and cash cycle efficiency adopters experienced during the study period. New stores often take a year or more to reach the inventory to sales ratios of established stores (Knight 2000).

Fourth, three of the adopters did experience improved inventory and cash cycle efficiency in spite of their fast growth and increased gross margins. Also, some adopters did not grow rapidly but still had worse inventory and cash cycle efficiency. Thus, the impact of growth in sales and gross margin on inventory and cash cycle efficiency is not clear. It might have an effect, but clearly does not determine the outcome completely. One other explanation is that implementation success may be critical to improved performance. Implementation in this sense refers to how effectively ECR initiatives were adopted as well as how many initiatives were adopted. (Note again that efficient promotion has not been widely implemented.) Further research will be necessary to clarify these relationships.

Fifth, gross margin (and net profit) are positively related to firm size; i.e., the larger the firm apparently the lower the price charged by suppliers. This phenomenon may tend to encourage mergers, and makes it difficult for small companies to compete on the basis of price. Thus, small grocers face a managerial challenge in finding ways to satisfy customers without offering the lowest prices.

Sixth, ECR was adopted more by large firms than by smaller grocers. This may reflect difficulties in attracting capital, greater advantages of technology for large firms, and/or other factors.

ACKNOWLEDGMENT

We would like to acknowledge the help of Dr. Robert K. Larson, CPA in the preparation of this work. Any mistakes or omissions are those of the authors alone.

NOTES

Bowersox, Donald J., David J. Closs, Theodore P. Stank, and Devin C. Shepard (1999), Supply Chain Management: Differentiating Through Effective Logistics, Washington, D.C.: Food Marketing Institute.

Collins, Richard (1997), "ECR-Breaking China in the US Supermarket Industry," Supply Chain Management, Vol. 2, No. 3, p. 92.

Daugherty, Patricia J., Matthew B. Myers, and Chad W. Autry (1999), "Automatic Replenishment Programs: An Empirical Examination," Journal of Business Logistics, Vol. 20, No. 2, pp. 63-82.

DeSanta, Richard (1997), "ECR Breakthroughs! A-a-a-a-ny Day Now," Supermarket Business, Vol. 52, July, pp. 7-10.

Harris, John, Paula M. Swatman, and Sherah Kurnia (1999), "Efficient Consumer Response (ECR): A Survey of the Australian Grocery Industry," Supply Chain Management, Vol. 4, No. 1, pp. 35-42.

Hoban, Thomas (1998), "Food Industry Innovation: Efficient Consumer Response," Agribusiness, Vol. 14, No. 3, pp. 235-245.

King, Robert P. and Paul F Phumpier (1996), "Reengineering the Food Supply Chain: The ECR Initiative in the Grocery Industry," American Journal of Agricultural Economics, Vol. 78, pp. 1181-1186.

Knight, Michael (2000), Interview, Senior Vice President, Non-Perishables, Giant Food LLC, Carlisle, PA.

Knill, Bernie (1997), "How Efficient Is Efficient Consumer Response?" Material Handling Engineering, Vol. 52, July, pp. 7-10.

Mathews, Ryan (1997), "ECR: More Promise than Performance?" Progressive Grocer, 64th Annual Report of the Grocery Industry, April, pp. 26-28.

Partch, Ken (2000), "Is the Supermarket ERA at an End?" Supermarket Business, Vol. 55, July 15, p. 138.

Pearce, Tony (1997), "Lessons Learned from the Birds Eye Wall's ECR Initiative," Supply Chain Management, Vol. 2, No. 3, pp. 99-106.

Salmon Associates, Inc., Kurt (1993), Efficient Consumer Response: Enhancing Consumer Value in the Grocery Industry, Washington, D.C.: Food Marketing Institute.

Salmon Associates, Inc., Kurt (1996), ECR 1995 Progress Report, Washington, D.C.: Grocery Manufacturers of America.

Stank, Theodore, Michael Crum, and Miren Arago (1999), "Benefits of Interfirm Coordination in Food Industry Supply Chains," Journal ofBusiness Logistics, Vol. 20, No. 2, pp. 21-25.

Tosh, Mark (1998), "What's Up With ECR?" Progressive Grocer, ECR '99 Supplement, December, pp. 8-24.

Vergin, Roger and Kevin Barr (1999), "Building Competitiveness in Grocery Supply Through Continuous Replenishment Planning: Insights from the Field," Industrial Marketing Management, Vol. 28, No. 2, pp. 145-153.

Ward's Business Directory of U.S. Private and Public Companies (1998), Detroit: Gale Research. Whipple, Judith, Robert Frankel, and Kenneth Anselmi (1999), "The Effect of Governance

Structure on Performance: A Case Study of Efficient Consumer Response," Journal of Business Logistics, Vol. 20, No. 2, pp. 43-62.

Whiteoak, Phil (1999), "The Realities of Quick Response in the Grocery Sector: A Supplier Viewpoint," International Journal of Physical Distribution and Logistics Management, Vol. 29, No. 7-8, p. 508.

Terence A. Brown

Pennsylvania State University

and

David M. Bukovinsky

Wright State University

ABOUT THE AUTHORS

Terence A. Brown is Associate Professor of Marketing and Logistics, Penn State University at Harrisburg. He received his DBA (Logistics) from the University of Maryland. His articles have appeared in Transportation Journal, Land Economics, Quarterly Review of Economics andBusiness, Journal of Transportation Management, and Traffic Quarterly.

David Bukovinsky is Assistant Professor of Accountancy at Wright State University, Dayton, Ohio. He received his Ph.D. (Accounting) from the University of Kentucky. He has published in a variety of journals in the field of management accounting.

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