At the Data Synchronization Summit last November in Las Vegas, every speaker at some point in their presentation would almost sheepishly acknowledge the need to emphasize “the importance of data accuracy.” It became the running joke of the conference.
Yet data accuracy is something that retailers and manufacturers are taking much more seriously these days as they recognize the significant impact it can have on their businesses. “Manufacturers are really starting to see data accuracy as being as important to their business as the products they make,” said Pam Stegeman, vice president, supply chain and technology, Grocery Manufacturers Association/Food Products Association, Washington.
Why so important? “If the information about products is not completely accurate, then all of the systems used to run the business will not be accurate, and that can lead to higher costs,” Stegeman said. In a simple but telling example, inaccurate case dimension often results in more trucks than necessary being used to deliver products. Or it can lead to problems in slotting products in warehouse, or getting them placed on store shelves in a timely manner.
Wegmans Food Markets, Rochester, N.Y., an industry pioneer in both data accuracy and synchronization, considers inaccurate data “a source of more disruption in our business than anything else,” said Marianne Timmons, vice president of supply chain and global business to business. “Once data is accurate, more time can be spent building sales and growing the business.”
Data accuracy is also the underpinning of the Global Data Synchronization Network (GDSN), which is being used by a growing number of retailers and manufacturers to make sure they are each using the same product data.
Wegmans proved the value of accurate data in a study conducted last year by Accenture, New York. The study, “Synchronization — The Next Generation of Business Partnering,” reported that Wegmans derived a $3.5 million annual savings in transportation costs ($2.5 million for inbound freight and $1 million for outbound freight) as a result of synchronizing accurate product data with suppliers.
The value of accurate data is often found in everyday matters — “five less trucks here, seven less trucks there,” said Brad Papietro, Wegmans' e-commerce manager. “It's a lot of singles that add up rather than one home run.”
DATA CLEANUP
Data accuracy is an issue that involves and impacts both manufacturers and retailers. Both retailers and manufacturers are responsible for “cleaning up” their internal product data, ensuring that it accurately reflects the actual dimensions and weight of cases and individual selling units, as well as the correct UPC or global trade identification number (GTIN). Overall, good quality data is defined by GS1, the global standards body based in Brussels, as master data that is “complete, consistent, accurate, time-stamped and industry-standards-based.”
Once data is clean, retailers and manufacturers are also both responsible for making sure that all of their internal systems are using this pristine data, sometimes called a “single version of the truth.” Some retailers are investing in Product Information Management (PIM) systems to oversee the internal uniformity of data.
Wegmans is working with individual departments to ensure that they don't each try to correct data errors. For example, the retailers' planogram department had been in the habit of manually correcting errors, but now those errors are returned to manufacturers so that they can be corrected at the source, Papietro noted.
Retailers and manufacturers are also both responsible for using the standard definitions of data attributes established by GS1. “Some companies still use their own legacy definitions,” noted GMA/FPA's Stegeman.
When data is clean and organized internally, it is ready to be synchronized with trading partners via the GDSN, which is managed globally by GS1.
Wegmans actually approached the process in reverse, aggressively staking out data synchronization relationships with suppliers, but then finding that their data needed to be cleaned up. “We were a little naive in thinking the quality of our suppliers' data was higher than that we were using,” Timmons said.
Wegmans decided a few years ago to take the initiative in confronting data inaccuracies, beginning with a limited number of manufacturers. Over the past year, the retailer has endeavored to correct data for all of the items in its grocery warehouse. At the beginning of 2006, about 30% of products were completely accurate, but as manufacturers started addressing their internal processes, the rate increased, ending the year with 64% of the grocery items having accurate data, Papietro said. It is now growing at 2% per week.
Wegmans assesses data accuracy by measuring the dimensions and weights of cases, inner packs and consumer packaging of products. It uses standard “dimensional tolerances” released last year by GS1 that allow case data for height, width, depth and weight to be within plus or minus 4% of actual measurements.
If Wegmans finds discrepancies between measurements and data provided by manufacturers, discussions are held with the manufacturers. “It's not a blame game; 50% of the time we own the problem,” Timmons said. But if the supplier is at fault, they are expected to send new data.
“Our suppliers need to understand that we drive our business off their data,” Timmons said. “[Low-quality data] might work in their organizations, but we need data that's higher quality.”
Many manufacturers, especially those involved in data synchronization efforts, are heeding this call, said GMA/FPA's Stegeman.
Stegeman observed that there is no end point with data accuracy. Keeping data accurate is an ongoing process that retailers and manufacturers “need to do every day,” she said.
ASSOCIATED PROGRAM
In recent months other retailers and wholesalers have been addressing data accuracy. Associated Food Stores, Salt Lake City, for example, has embarked on a program to measure the dimensions of a sample of the cases being sent to their warehouse by eight manufacturers, and compare the results with the dimensional data provided by the same manufacturers.
Associated also employs standard dimensional tolerances. If 90% of its measurements fall within that tolerance, then Associated accepts the data as accurate. If not, “we push the data back to the manufacturer and require them to resend it to us after measuring again,” said Corby Bleckert, category manager, special projects.
“We've not come across horrible data yet but we're not that deep into the process,” he said, adding that Associated has been synchronizing data with those eight suppliers for about six months.
Associated laid the groundwork for its current efforts by spending about two years “cleaning our own internal data, getting rid of duplicate UPCs through our network and making sure everything was clean before starting to do data sync,” Bleckert said.
To bolster its internal processing of data, Associated has invested in a PIM system from GXS, Gaithersburg, Md. The PIM helps to synchronize product data and distribute it to Associated's internal systems.
Bleckert acknowledged that Associated has been “riding the coattails” of Wegmans' data accuracy efforts. “By doing the legwork to get data cleaned, they cleaned up some of the mess for us,” he said. Still, Associated elected to do its own physical checks of accuracy to make sure it was correct.
Papietro is aware that Wegmans' work is being applied by manufacturers to other retailers across the industry. At the same time, he believes other retailers and wholesalers should “roll up their sleeves and measure products to understand the situation in their shop.”
Ultimately, Papietro said, Wegmans and other retailers need to come together and develop an “industry solution” in order to lessen the administrative burden on manufacturers. “If we're all doing different things, that's not simplifying our [manufacturer] partners' business,” he said.
How to Fix Your Data
Retailers and manufacturers seeking guidance on how to improve the quality of their product data have an online resource: the Data Quality Framework.
Developed last year under the auspices of GS1, the global standards organization based in Brussels, the Data Quality Framework is available at www.gs1.org/productssolutions/gdsn/. Several industry associations contributed to the creation of the voluntary guidelines, including the Food Marketing Institute and the Grocery Manufacturers Association/Food Products Association.
Central to the Data Quality Framework is the Data Quality Protocol, which has two components: a data quality management system based on best practices for managing data, and an inspection procedure to physically validate product attributes such as dimensions and weight.
The Data Quality Framework also includes sections on how companies can demonstrate compliance to the guidelines either through an internal audit or through third-party certification. However, the compliance steps are still under development, said Pam Stegeman, vice president, supply chain and technology, GMA/FPA, Washington.
Another standard, developed by the Data Accuracy Task Force, a group of retailers and CPG companies, covers “dimensional tolerances” — how far from reality data on physical dimensions and weights are allowed to be. The group set a 4% tolerance for “rigid packaging” such as cases, as well as a 0.25-inch tolerance for consumer items.
The task force is currently working on tolerances for “flexible packaging” such as potato chip bags or bags of sugar, as opposed to boxes or cans, according to Brad Papietro, e-commerce manager for Wegmans Food Markets, Rochester, N.Y., a task force member. The new tolerances should be ready within six months, he said.
— M.G.
