Q Uarterly E xecutive

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1 Measuring the Impact of RFID on Out of Stocks at Wal-Mart MIS Q Uarterly E xecutive Me a s u r i n g t h e Im pa c t o f RFID o n Ou t o f St o c k s at Wa l-ma r t 1 Bill C. Hardgrave University of Arkansas (U.S.) Simon Langford Wal-Mart Stores, Inc. (U.S.) Matthew Waller University of Arkansas (U.S.) Robert Miller Ashland University (U.S.) Executive Summary Interest in, and subsequent use of, passive radio frequency identification (RFID) in the retail supply chain has grown rapidly in the past few years. Several major retailers have launched RFID initiatives, with Wal-Mart leading the way both in the number of deployments (stores and distribution centers) and the number of suppliers involved. At this early stage of adoption, one nagging question for retailers and suppliers is: what is the business case for RFID? In examining this question, a potential area for improvement is the number of products out of stock on the shelves. Any reduction in out of stocks provides benefits for the retailer, the supplier, and the consumer. To explore the out-of-stock business case for RFID, Wal-Mart commissioned a study to measure the impact of the technology on out of stocks. For 29 weeks in 2005, out of stocks were examined daily in 24 Wal-Mart stores (12 RFID-enabled stores, 12 control stores) representing all store formats. The results of that study are presented in this article. They show that RFID makes a significant difference: within the test stores, out of stocks were reduced by 21% more than in the control stores, and in the test stores RFID-tagged items experienced fewer stock outs than non-tagged items. THE out-of-stock reduction BUSINESS CASE FOR RFID In January 2005, Wal-Mart s top 100 suppliers began using radio frequency identification (RFID) tags on pallets and cases shipped to stores in the Dallas, Texas, region. Wal-Mart s RFID initiative jump-started a 50-year-old technology that, until then, had found limited (but successful) use in a variety of niche areas. Since then, the RFID industry has blossomed. The Department of Defense followed Wal-Mart s lead and mandated that its suppliers use RFID; Target, Albertson s, and Best Buy, among others, followed suit. Initial efforts focused on the largest suppliers in the retail supply chain (e.g., Procter & Gamble, Gillette, Kimberly-Clark, Kraft) but have now spread to include smaller retail suppliers as Wal-Mart and other retailers continue to deploy RFID technology. MISQE is Sponsored by RFID is part of a family of auto-identification technologies that also includes the ubiquitous barcode. Introduced in the mid-1970s, barcodes have been used as the primary form of auto-identification in the retail supply chain (and by many other industries). Given the success of barcodes, why should retailers move to RFID? The answer lies in the numerous advantages of RFID relative to barcodes, which include: 2 RFID technology does not require line of sight Hundreds of tags can be identified at one time Hundreds of tags can be read per second RFID tags can store more data 1 Jeanne Ross is the accepting senior editor for this article. 2 Delen, D., Hardgrave, B., and Sharda, R. RFID for Better Supply-Chain Management Through Enhanced Information Visibility, Production and Operations Management (16:5), September-October 2007, pp University of Minnesota MIS Quarterly Executive Vol. 7 No. 4 / Dec

2 Hardgrave et al. / Measuring the Impact of RFID on Out of Stocks at Wal-Mart The data on RFID tags can be manipulated. Although an important driver of the take-up of RFID has been major retailers mandating that their suppliers use RFID tags, it is not the main reason for businesses planning to deploy the technology. A survey of 510 companies by Frost & Sullivan found that the No. 1 reason was improved process efficiencies. 3 RFID has the potential to improve processes on the manufacturing floor, in distribution centers, and in the backrooms of retail stores. One area in particular has the potential to benefit suppliers, retailers, and consumers: reducing out of stocks. Empty shelves are the bane of retailers lives. In the U.S., the average out-of-stock rate is approximately 8%, 4 which means that about one in every 12 items on a consumer s shopping list is not on the shelf. The result is lost sales and unhappy customers. The estimated potential lost sales are about 3.4% for retailers and 2.6% for suppliers. 5 The percentages may be low, but the implications are significant: a $1 billion supplier may lose as much as $26 million in annual sales; a $100 billon retailer may lose $3.4 billion in sales. Thus reducing out of stocks by even a small amount can quickly translate into real dollars. Reducing out of stocks is a very attractive potential business case for deploying RFID. In 2005, German retailer Metro announced that RFID had reduced out of stocks by 11% but provided no details about the study (e.g., number of items, time period, stores, etc.). 6 In fact, very little has been done to date to examine the impact of RFID on out of stocks. This article aims to fill that void by reporting the results of a study that measured the impact of RFID on reducing out of stocks in Wal-Mart stores. The study showed that RFID significantly reduced out of stocks, providing benefits both to Wal-Mart and its suppliers. First, though, we provide a brief tutorial on the causes of stock outs and consumer responses to them, and describe in generic form how RFID can be applied in the retail supply chain. 3 O Connor, M. C. Efficiencies Drive RFID Adoption, RFID Journal, Available at: rfidjournal.com/article/ articleview/1833/1/1/. 4 Corsten, D., and Gruen, T. Desperately Seeking Shelf Availability: An Examination of the Extent, the Causes, and the Efforts to Address Retail Out-of-Stocks, International Journal of Retail & Distribution Management, (31:11/12), 2003, pp Ibid. 6 Johnson, J. R. Metro Reduces Out of Stocks with RFID; is Wal-Mart Next?, DC Velocity, August 3, Available at: CAUSES of OUT OF STOCKS AND CONSUMER RESPONSES In general, the causes of out of stocks fall into six categories: (1) store forecasting, (2) store ordering, (3) shelf replenishment (item in the store but not on the shelf), (4) distribution center issues, (5) retail headquarters or manufacturer issues, (6) other. 7 Figure 1 shows the average percentages for each cause in U.S. retailers. The incidences of these causes may vary due to events (e.g., a hurricane), by category (e.g., some products may be out of stock because of shelfreplenishment problems rather than store ordering), by sales velocity (e.g., slow-moving items may be out of stock due to store forecasting), and by global region (e.g., in Europe, 38% of out of stocks are due to shelfreplenishment issues). As explained later, Wal-Mart s current use of RFID addresses one of the root causes of out of stocks: shelfreplenishment issues (i.e., a product is in the store but not on the shelf). When a product is out of stock, a consumer generally Decides the product is not needed (does not purchase) Decides the product is not needed immediately (delays the purchase) Buys the same brand, but a different size, style, flavor, color, etc. (same brand substitute) Buys the same product but a different brand (different brand substitute) Goes to another store to buy the desired product. Figure 2 shows the average percentages for each response in the U.S. 8 Although these five responses are common, the exact reaction will vary by region and product category. For example, Europeans have much less brand loyalty than Americans and are more likely to substitute a different brand. And consumers are very loyal, for example, to diaper brands compared to paper towels and are thus more likely to go to another store to buy the diapers they want rather than switch to a different brand. The different responses to out of stocks have different affects on retailers and suppliers: 7 Corsten, D., and Gruen, T., op. cit., Corsten, D., and Gruen, T., op. cit., MIS Quarterly Executive Vol. 7 No 4 / Dec University of Minnesota

3 Measuring the Impact of RFID on Out of Stocks at Wal-Mart Figure 1: Out of Stock Causes in the U.S. Distribution Center (11%) Other (3%) Retail HQ or Manufacturer (13%) Store Forecasting (18%) Shelf Replenishment (22%) Store Ordering (33%) (Source: Corsten and Gruen, 2003) Figure 2: Consumer Responses to Out-of-Stock Occurrences (U.S.) Buys at Another Store (31%) Does Not Purchase (11%) Delays Purchase (16%) Different Brand Substitute (22%) Same Brand Subsitute (21%) (Source: Corsten and Gruen, 2003) 2008 University of Minnesota MIS Quarterly Executive Vol. 7 No. 4 / Dec

4 Hardgrave et al. / Measuring the Impact of RFID on Out of Stocks at Wal-Mart Deciding not to purchase directly affects both the retailer and supplier Delaying the purchase does not affect either in the long term The direct affects of same brand substitution are hard to determine because a purchase was made Different brand substitution directly affects the supplier Buying the product at a different store directly affects the retailer. The data in Figure 2 shows that retailers absorb about 42% of the impact of out of stocks (11%+31%) while suppliers absorb about 33% (11%+22%). This means the estimated potential lost sales for a store with an average of 8% of products out of stock is 3.4% (8%x42%) and for the suppliers it s 2.6% (8%x33%). 9 In other words, if a retailer could eliminate all out of stocks, it would potentially increase sales by 3.4% and its suppliers would potentially increase sales by 2.6%. applying rfid in the retail supply chain The advantages of RFID have persuaded Wal-Mart and many other companies to aggressively deploy the technology as a way of improving the supply chain (thus reducing costs and increasing sales). In its simplest form, an RFID system consists of a tag attached to the product to be identified, an interrogator (i.e., a reader), one or more antennae attached to the reader, and a computer (to control the reader and capture the data). At present, the focus of applying RFID in the retail supply chain is mainly on passive RFID tags, which are powered by radio waves created by a reader and transmitted via its antennae. A passive tag remains powered only while it is within the read field and responds to the reader by reporting the data stored on it. As an RFID-tagged case moves from the supplier to the retail distribution center and then on to the retail outlet, 10 it passes through several RFID read fields. The readers capture and record the case s tag data 9 Note: these calculations do not include the hard-to-determine effects of purchasing a different size, the cumulative effects of several out of stocks (i.e., the point at which a consumer decides to leave the entire shopping cart and go to another store and never comes back!), and the risk of losing brand loyalty if a consumer substitutes a different brand. 10 Currently, RFID is being used in an abbreviated supply chain, from the point of departure from the supplier s facility to the backroom of a retail outlet. as it passes through these points. Figure 3 provides an overview of the key read points in a generic distribution center. As products are delivered to the distribution center, read portals (created by stationary readers and antennae on each side of the delivery door) capture the pallet and case data. The product is stored in the distribution center for an indeterminate time, then individual cases are put on the conveyor system to begin the sorting process; the conveyor system may contain multiple read points. Finally, the individual cases are sorted and shipped out of the shipping doors, which contain read portals similar to the receiving doors. Figure 3 shows the RFID read points most cases pass through as they move through a general merchandise distribution center. The actual number of reads for a specific case may vary depending on the type of product and distribution center. For example, bagged pet foods are not placed on conveyors. And a refrigerated/grocery distribution center is different from a general merchandise center a grocery distribution center has stretch wrap machines where readers can be placed but may not have conveyors. In retail stores themselves, readers are confined to the backroom area no readers are presently on the sales floor (see Figure 4). Receiving doors have read portals similar to those at the distribution center and capture data from individual cases as they are unloaded from the truck. The product then moves to the sales floor (with readers placed next to the doors going to the sales floor) or onto backroom shelving. Eventually, all products should be moved to the sales floor and when the cartons are empty, they are returned through the sales floor doors (a second read is captured at this point) and placed into the box crusher for disposal (the last read point). Figure 5 traces the movements of a single case of product from its arrival at the distribution center to its end of life at the box crusher. The data in the table was captured by readers in the distribution center and the store, which read the case s unique electronic product code 11 stored in its RFID tag. This particular case of product arrived at distribution center 123 on August 4, was put on the conveyor system on August 9, and departed shortly thereafter. It arrived at store 987 about 12 hours after leaving the distribution center and went almost immediately to the backroom. The case stayed there for two days, when it went to the sales 11 EPC is the identifier used in the retail supply chain. It is similar to the UPC but adds a unit serial number for each tagged unit. For more information about EPC, visit: MIS Quarterly Executive Vol. 7 No 4 / Dec University of Minnesota

5 Figure 3: Generic Retail Distribution Center RFID Read Points Measuring the Impact of RFID on Out of Stocks at Wal-Mart Figure 4: Generic Retail Store RFID Read Points 2008 University of Minnesota MIS Quarterly Executive Vol. 7 No. 4 / Dec

6 Hardgrave et al. / Measuring the Impact of RFID on Out of Stocks at Wal-Mart Figure 5: Sample RFID Data Tracing the Movements of a Single Case Location Date/Time Reader DC :15 Inbound is located elsewhere on the sales floor). As indicated earlier, about 22% of out of stocks in the U.S. are attributed to in-store replenishment problems (i.e., the product is available in the backroom but is not on the shelf). 12 DC :54 Conveyor DC :23 Outbound ST :31 Inbound ST :48 Backroom ST :01 Sales Floor ST :47 Sales Floor ST :49 Box Crusher floor, returned empty about 45 minutes later, and then went to the box crusher for ultimate disposal. WAL-MART USes RFID data TO automatically create picklists Wal-Mart uses two basic methods to replenish stock on its shelves: Stock shelves directly from delivery trucks (i.e., product moves directly from trucks to the sales floor to be stocked) Create a picklist of products stored in the backroom for associates to take to the sales floor. In a non-rfid environment, picklists are created by visually inspecting the shelves for out-of-stock (or near out-of-stock) items and using a handheld barcode scanner to add those items to a picklist (if the system shows product availability in the store s backroom). Picklists can also be created by using a handheld device to scan barcodes on product cases stored in the backroom (known as a reverse picklist ). The system then identifies, via an indication of existing store level inventory, whether the case will fit on the shelf. If it can, the associate picks the case (i.e., places it on a cart) and takes it to the sales floor to be put on the shelf (many cases are placed on a cart before going to the sales floor). Both these methods of creating picklists are laborious and rely on the accuracy of the system to suggest availability in the backroom (e.g., sometimes the product is not available in the backroom instead, it With RFID-enabled stores, Wal-Mart knows what cases have been delivered to a store, stocked in the backroom, or taken to the sales floor. Combined with point-of-sale data, this information enables the store to have a much more accurate view of inventory both on the shelf and in the backroom. 13 As product is sold, picklists can be generated based on information about items on the shelf (from point-of-sale data) and RFIDgenerated information of product in the backroom (from tag reads in the backroom). In essence, the picklist process is changed from reactive (looking at the shelf or backroom to determine what needs to go to the shelf) to proactive creating the list in real time based on sales. Wal-Mart s automated picklists are enabled by the RFID data and are currently the principal driver in reducing out of stocks. Note, however, that the process for stocking shelves has not changed the store associate receives a list of items (the picklist) and then has to find these items and place them on the shelves. But the way in which the items are added to the picklist has greatly improved. In this way, RFIDgenerated picklists help address one of the main causes of out of stocks product in the store s backroom but not on the shelf. Measuring the impact of wal-mart s rfid APPLICATION ON out of stocks To test the impact of RFID on out of stocks, 12 Wal- Mart stores were chosen at random from among the 104 RFID-enabled stores at the time. A matching set of 12 control stores was then chosen based on geographic location, size of stores (square footage), and annual sales. For 29 weeks, from February to September 2005, the shelves in the test and control stores were scanned daily. An out of stock was defined as any empty shelf space. The daily scanning of a particular store started at approximately the same time each day and the associates doing the scanning followed the same route each day. Thus the same areas in each store 12 Corsten, D., and Gruen, T., op. cit., RFID is currently used only at the case level; individual items are not tagged. RFID information, combined with currently available point-of-sale data, is expected to provide much more accurate inventory counts. 186 MIS Quarterly Executive Vol. 7 No 4 / Dec University of Minnesota

7 were scanned at approximately the same time each day to eliminate any out-of-stock fluctuations due to the time of day. At the beginning of the study, 4,554 products had RFID tags. This set of products, from almost all departments, was used throughout the study (in both the test and control stores). All out-of-stock items were scanned regardless of whether they were tagged. 14 To establish a baseline, out of stocks at each store were scanned for eight weeks before the RFID-generated picklist application was enabled in the test stores. The initial picklist process (termed partial picklist ) was capped at 10 items per day, per department, per store. In mid-april, automated partial picklists went live in the test stores. In late June, the cap was removed from the partial picklist. Thus the test stores had three treatments: no RFID, partial RFID (capped picklist), and full RFID (uncapped picklist). results of the test The results of the test were analyzed by treatment (no RFID, partial picklists, full picklists), by trends over time, and by tagged vs. non-tagged items. The study Measuring the Impact of RFID on Out of Stocks at Wal-Mart also analyzed the contribution that autopicklists made to reducing out of stocks. By Treatment To determine the effect of RFID in the test stores, weekly out-of-stock averages were calculated for treatment 1 (no RFID), treatment 2 (partial RFID), and treatment 3 (full RFID). As shown in Figure 6, test stores (across all store formats) had an average of 474 out of stocks per week in the eight weeks before the RFID test began, 399 for the partial RFID period, and 352 for the full RFID period. Thus out of stocks reduced by 16% from no RFID to partial RFID, by 12% from partial to full RFID, and by 26% from no RFID to full RFID. Remember that each treatment period covered several weeks. Although a 26% improvement from no RFID to full RFID is impressive, it does not take account of any improvement that may have occurred without the introduction of RFID hence the need for the control group of stores. As also shown in Figure 3, average out of stocks in the control stores declined slightly, from 408 units during the treatment 1 period to 406 during treatment 2 to 387 during treatment 3. Thus over the Figure 6: Average Weekly Out of Stock by Treatment, Test vs. Control Average Weekly Out of Stock test control No RFID Partial RFID Full RFID 14 In fact, the scanning crews and stores had no idea which items were tagged. Only those directly involved in the study had knowledge of the tagged items. This was done to ensure that the stores and the scanning crews did nothing special for the tagged items University of Minnesota MIS Quarterly Executive Vol. 7 No. 4 / Dec

8 Hardgrave et al. / Measuring the Impact of RFID on Out of Stocks at Wal-Mart entire test period, the overall reduction in out of stocks in the stores that did not have RFID-generated picklists was 5%, compared with 26% for the test stores. The reason the control group experienced a decrease in out of stocks is due to a series of initiatives unrelated to RFID technology. These initiatives are ongoing and consistent across all Wal-Mart stores thus all stores would feel the effect of these initiatives. The reduction could also be due to the well-known Hawthorne Effect, which suggests that people will alter their behavior when they know they are being observed. In this case, both sets of stores may have improved simply because people were in the stores scanning the shelves daily. It is reasonable to assume that out of stocks at the test stores would also have declined by 5% without the introduction of RFID-generated picklists. Thus we conclude that the improvement due to RFID in the tests stores is approximately 21%. Weekly Trends The analysis by treatment aggregated the data into three time periods corresponding to the test store treatment periods. Another way to analyze the data is by each week during the study, to identify trends. The average out of stocks for the 4,554 products in each of the 29 weeks during the study for both the test and control stores are shown in Figure 7. As shown by the trend lines, out of stocks in both the test and control stores consistently decreased during the study period. 15 However, the rate of decrease for the test stores was five times more than that for the control stores (5.7 items per week, compared to 1.1 items per week). The reduction of 1.1 items per week in the control stores can be considered as the natural rate of improvement and is consistent with the analysis by treatment. Thus the reduction in out of stocks in the test stores that can be attributed to RFID is 4.6 items per week i.e., RFID-generated picklists resulted in a four-fold reduction in out of stocks. Tagged vs. Non-tagged Items Another way of assessing the impact of RFID is to examine out of stocks in tagged and non-tagged items in the test stores. As Figure 8 shows, out of stocks for the tagged items fell by about 5.1 units per week (which is consistent with the reduction shown in Figure 7: Average Out of Stocks in Test and Control Stores, by Week Average Weekly Out of Stock control test Linear (control) Linear (test) week 15 Note: the trend lines in Figure 7 are for visual interpretation only. We are not attempting to draw conclusions about the suitability of a linear trend to explain the data. 188 MIS Quarterly Executive Vol. 7 No 4 / Dec University of Minnesota

9 Measuring the Impact of RFID on Out of Stocks at Wal-Mart Figure 8: Average Out of Stocks For Tagged and Non-Tagged Items in Test Average Weekly Out of Stock week Tagged Non-tagged Linear (Tagged) Linear (Non-tagged) Figure 7), whereas the non-tagged items declined by 1.2 units per week. Interestingly, this reduction is very similar to that in the control stores (1.1 units per week). Stores, by Week Analyzing out of stocks for tagged and non-tagged items in the test stores helps to isolate the impact of RFID in those stores. The similar trend lines for nontagged items in the control stores and the test stores suggests that out-of-stock trends for non-tagged items whether in an RFID store or a non-rfid store were similar. This analysis would thus detect any systemic effort to artificially influence (either positively or negatively) out of stocks within the test stores since both tagged and non-tagged items would be affected equally. As shown in Figure 8, this was certainly not the case as the rate of improvement in tagged items was better than for non-tagged items. Overall, this analysis ensures that any changes within a store (e.g., in a department or a store manager) that could affect process execution would be controlled for and captured in the results. Assessing the Contribution of Automatic Picklists Finally, the study analyzed how the proportions of automatically picked and manually picked items on the daily picklists varied over time, so the contribution RFID-generated picklists made to reducing out of stocks could be assessed. Figure 9 shows, for all test stores, the average daily percentage of items put on picklists by the RFID application (the autopicklist) during the full RFID (treatment 3) period. For example, on day one of this period, the autopicklist items accounted for about 25% of all items on the picklist (averaged across all test stores). The autopicklist is not created on Saturday and Sunday hence the two-day gaps in each week. The data shown in Figure 9 provides two interesting insights into the importance of RFID-enabled autopicklists. First, the number of tagged items represented only a small proportion of the total items, yet for the first several weeks of the full RFID period, they represented about 25%-30% of all items on a picklist. Thus the autopicklist was finding and adding items that would not normally be added by store associates. Second, over time, as the in-stock position of tagged items improved (as illustrated earlier in Figures 6 through 8), the daily autopicklist 2008 University of Minnesota MIS Quarterly Executive Vol. 7 No. 4 / Dec

10 Hardgrave et al. / Measuring the Impact of RFID on Out of Stocks at Wal-Mart Figure 9: Proportion of Autopicklist Items on Daily Picklists During the Full RFID Test Period proportion declined, as shown in Figure 9. Because of the improved in-stock position of tagged items, there simply were not as many out-of-stock items to put on the autopicklist. Thus the autopicklist is clearly improving the in-stock position of tagged items. THE VALUE OF REDUCED out of stocks TO WAL-MART The various analyses of the results from Wal-Mart s RFID-generated picklists provide a consistent and important message: RFID makes a real contribution to reducing out of stocks. The difference that RFID makes is remarkable given the relatively minor changes enabled by the technology. Simply by reading the RFID tags on cases that have entered the backroom, Wal-Mart was able to modify its manual, reactive picklist to make it proactive and automatic. With RFID, associates did not have to scan the shelves to determine out of stocks the system did it for them. It also ensured that the boxes were in the backroom when associates went to retrieve them. Wal-Mart put no extra emphasis on the process and did not change the way associates did their job. Associates who only worked from the picklist (i.e., did not create it) were not aware of a change in the process although they may have noticed the increased number of items and accuracy of the picklists! With just one minor change to the picklist (including items generated by the RFID application), Wal-Mart achieved a 21% reduction in out of stocks in the test stores (after taking account of improvements that would have occurred anyway) and a four-fold improvement in the test stores compared to the control stores. We said earlier that about 22% of out of stocks are due to in-store shelf-replenishment issues (i.e., a product is in the store but not on the shelf). Thus a 21% reduction almost eliminates shelf replenishment as a source of out-of-stock problems. With shelf-replenishment issues greatly reduced, retailers can focus on other root causes of out of stocks, such as store ordering and store forecasting, and how RFID can be used to reduce these and other causes of out of stocks. As indicated earlier, U.S. stores on average suffer from 8% of items being out of stock, which translates to about 3.4% in lost sales for the retailer and about 2.6% for suppliers. Given that RFID was able to reduce out of stocks by 21%, RFID can potentially increase retailers sales by about 0.7% (3.4%x21%) and by about 0.6% for suppliers (2.6%x21%). Wal-Mart s sales in 2007 were almost $400 billion, so a 0.7% increase is substantial. Although this improvement is impressive, RFIDgenerated picklists also provide another significant benefit. The amount of time saved in reducing (or eliminating) the manual scanning of empty shelves can be used to bring more products from the backroom 190 MIS Quarterly Executive Vol. 7 No 4 / Dec University of Minnesota

11 Measuring the Impact of RFID on Out of Stocks at Wal-Mart to the sales floor or to spend more time on the sales floor helping customers. When this simple change to the picklist process is coupled with initiatives such as handheld readers that can be used to quickly locate product, the potential improvements in backroom processes, and in reducing out of stocks in particular, are enormous. EPILOGUE This study has been lauded for being one of the first independent and extensive studies of RFID s potential payback. 16 Certainly, a 21% reduction in out of stocks makes a compelling case for RFID for many companies. As a result of this study, and others, Wal- Mart has continued its rollout of RFID. 17 During the study period, Wal-Mart had 104 RFID-enabled stores; by October 2008, it had deployed RFID applications in more than 1,300 stores, and that number continues to grow. Automatic picklists the cornerstone of using RFID data to reduce out of stocks are used in all of Wal-Mart s RFID-enabled stores and continue to provide value. One store manager commented that RFID-tagged items were on the shelf more often than non-tagged items and said You can see physically that the system is working. 18 While some observers have suggested that the intensity of Wal-Mart s RFID effort has waned, 19 the reality is that adopting any new technology takes time. With more than 4,100 stores and clubs in the U.S., a rapid rollout of RFID is simply unrealistic. It took almost 20 years for the now ubiquitous barcode to be adopted broadly across retailers. Almost 10 years after the barcode was introduced, Business Week declared it a failure after only 50 stores of an expected 1,000 had installed it. 20 Given that RFID began its journey at Wal-Mart in January 2005, and that it has already been deployed in 1,300 stores, it seems that RFID is being adopted at a faster pace than expected. The successful deployment of RFID by Wal-Mart is partly due to the company engaging its suppliers from the start of the initiative and seeking to achieve value both for itself and for its suppliers. Wal-Mart continues 16 Roberti, M. A Look Back at 2005, RFID Journal, December 19, Available at: 17 Roberti, M. EPC Reduces Out-of-Stocks at Wal-Mart, RFID Journal, October 14, Available at: articleview/1927/1/1/. 18 Ibid. 19 McWilliams, G. Wal-Mart s Radio-Tracked Inventory Hits Static, The Wall Street Journal, February, 15, 2007, B1. 20 Varchaver, N. Scanning the Globe, Fortune, May 31, Available at: money.cnn.com/magazines/fortune/fortune_ archive/2004/05/31/370719/index.htm. to hone and adjust its RFID adoption strategy to achieve maximum return on investment. In setting its strategy, it has carried out other studies into RFID s value, such as the impact on inventory accuracy. Sam s Club, a division of Wal-Mart, is now using instore RFID to help locate product on the sales floor. Beginning in 2009, individual selling units (items) in a Sam s Club will be RFID-tagged. Overall, Wal-Mart is aggressively adopting RFID, driven by the desire to reduce costs, streamline the supply chain, and enhance the customer experience. About the authors Bill C. Hardgrave Bill Hardgrave (bhardgrave@walton.uark.edu) holds the Edwin and Karlee Bradberry Chair in Information Systems at the Sam M. Walton College of Business, University of Arkansas. He is founder and Executive Director of the Information Technology Research Institute and Director of the RFID Research Center. Hardgrave s research, primarily in the areas of RFID and systems development, has been published in a variety of leading journals. His research on RFID has focused on the business value of RFID. Subsequently, he has delivered more than 50 invited presentations to more than 10,000 people throughout the world. The University of Arkansas RFID Lab, heralded by RFID Journal as one of the world s preeminent RFID research facilities is supported financially by 55 companies and averages more than 1,200 visitors from over 500 companies annually. Hardgrave also serves as editor-in-chief of the International Journal of RF Technologies: Research and Applications. Simon Langford Simon Langford (simon.langford@wal-mart.com) is Director, RFID and EPC Strategies at Wal-Mart Stores, Inc. As director, Langford has focused on leveraging the collaborative benefits of RFID, which has resulted in improved product availability for Wal- Mart s customers and thus in delivering value for both suppliers and Wal-Mart. He has also worked with standards groups and technology providers to assist the development of global standards and innovative solutions. Prior to moving to the U.S., Langford worked at Asda (the United Kingdom s second largest grocery retailer). Asda was acquired by Wal-Mart in Matthew Waller Matthew Waller (mwaller@walton.uark.edu) is Professor of Marketing and Logistics and Garrison Endowed Chair in Supply Chain Management at the 2008 University of Minnesota MIS Quarterly Executive Vol. 7 No. 4 / Dec

12 Hardgrave et al. / Measuring the Impact of RFID on Out of Stocks at Wal-Mart Sam M. Walton College of Business, University of Arkansas. Waller s research has been published in such journals as Decision Sciences and the Journal of Business Logistics. He also serves as editor of International Journal of Logistics Management and systems editor for the Journal of Business Logistics. Waller is currently living in China, where he is director of the Walton College s Executive MBA Program in Shanghai. Robert Miller Robert Miller (rmiller9@ashland.edu) is an assistant professor in the Dauch College of Business and Economics at Ashland University. He earned his Ph.D. in Business Administration from the University of Arkansas. Miller s research interests include information systems service quality, RFID-enabled supply chain management, and technologically mediated social networks. Before pursuing his Ph.D., he worked for 10 years as an applications developer in the power and telecommunications industries. 192 MIS Quarterly Executive Vol. 7 No 4 / Dec University of Minnesota