Big Data

How MDM Improved Customer Satisfaction and Reduced Costs at Advance Auto Parts

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Cost awareness among automobile consumers has led many to invest in servicing and repairing their vehicles rather than purchasing a new one. Supporting the auto parts and do-it-yourself kits necessary to keep today’s automobiles running is challenging due to the plethora of part numbers, numbering nomenclatures and system “bundles” that may exist for the same part or parts. Achieving service leadership and superior product availability is a business imperative for Advance Auto Parts, Inc. (AAP), which ranks among the Fortune 2000 World’s Largest Companies and operates 3,794 stores plus an online shopping channel. Here’s how AAP achieved five challenging objectives by leveraging a multidomain master data management (MDM) platform called Stibo Systems STEP. 

Advance Auto Parts embarked on its MDM deployment in 2010. Objectives for its MDM/ Product Information Management (PIM) initiative included:

  1. Increase revenue and customer satisfaction by streamlining merchandising efforts and time to market and by improving reaction time
  2. Receive accurate information from manufacturers/third-party vendors
  3. Comply with Automotive Aftermarket Industry Association (AAIA) standards
  4. Reduce data-entry costs
  5. Reduce product returns 

To support its merchandising efforts, AAP sought to consolidate product data for more than 650,000 products/SKUs that span more than 350,000 vehicle models, include more than 35 million part-to-vehicle relations and have greater than 500,000 interchange records (i.e., records that cross-reference the part number for an auto part with other part numbers that could serve as a viable replacement). 

AAP also sells product bundles called “kits” or “systems.” These systems include all the necessary parts, accessories and/or tools needed to repair the entire system in a car and are often bundled based on the function (i.e., a brake system, a coolant system, etc.).  

Driving data efficiencies 

Data accuracy is the lifeblood of AAP and the deployment of correct and accurate data provides major benefits to both internal operations and customers that are in the ordering process.  Previously, the company updated vendor information on a quarterly basis, and interchange/hierarchy data often took weeks. In contrast, Stibo Systems’ MDM platform, STEP, updates AAP’s data continuously. 

STEP systemically validates and processes product, attribute data and digital assets received from vendors and delivers them into AAP’s information supply in near real time. Any information reviewed by AAP personnel is validated, reviewed and put through syndication/delivery process in less than 48 hours to ensure data accuracy. 

AAP first created a fully automated data processing pipeline that would allow vendor-supplied data to be delivered by vendors in industry-standard formats known as “Product Information Exchange Standard” (PIES) and “Aftermarket Catalog Enhanced Standard” (ACES) data. The STEP platform automatically validates and imports the data and initiates the workflow for information requiring review.  

Once processed, data is automatically syndicated and delivered to any downstream consumer of the information. AAP uses IBM SI to provide an FTP interface to suppliers, allowing for automatic drop of files and retrieval of data processing reports delivered by Stibo Systems’ STEP MDM solution. 

Busing its way to product accuracy 

Once the master data management platform automates the validation/processing of vendor-supplied information, it then takes the data that was delivered by vendors through an optimized workflow process for the few pieces of data that require manual review/approval.  When processed and approved, the STEP system syndicates the information to AAP’s Enterprise Service Bus (ESB) via a WebSphere MQ interface ensuring guaranteed delivery. 

The ESB brokers the messages and delivers them to any downstream system that would consume the data including AAP’s point-of-sale system, ERP system and Shelf Tag Label printers should an updated product description necessitate an update to a shelf tag. 

Reduced processing time. The fully automated processing/delivery model is in contrast to the manual mapping/processing that is the industry norm. Leading independent third-party catalog providers have processing times that include error-prone manual processing in the range of 60-90 days compared to less than 48 hours for AAP.  

Steering customers to the correct product 

Ensuring that its mutually interacting applications are using the same information, AAP is able to compile accurate data from its complex IT landscape and deliver that data to its stores on an automated basis. This has significantly cut down on lag time and the amount of effort needed to make data corrections and greatly improved the time it took for updates to be fed to its customer-facing systems. 

Improved customer buying ability. As a result, AAP achieved a 15 percent improvement in its customers’ buying ability as AAP stores now have better and more reliable catalog and part information.  

Previously AAP had to keep track of all of the individual part numbers and, when necessary, cross-reference a part number to other part numbers that could serve as a viable replacement (aka an interchange record). Interchange records take into account basic vehicle information such as the year, make and model of a vehicle, and the description of the part (such as an air conditioning compressor) and then provide information about the specific stock part number and any other related part numbers that may be used for that component. 

Reduced errors and product returns. AAP also lowered its customer order-processing errors and decreased its product returns by 10 percent. Traditionally AAP store personnel work with do-it-yourself customers and professional installers to make accurate recommendations regarding the car, the parts and/or the systems required. Prior to the MDM initiative, and due to inaccurate information in the system, it was not uncommon for the store clerk to give the wrong recommendations, which led to a returned product.    

In addition, AAP reduced risk and loss by implementing the MDM solution. Previously and because of data inaccuracies, it was not uncommon for a customer to leave the store with two or three variations of a product/part because they didn’t know which would fit. They felt it would be easier to buy all of them, try them until they found the one that fit and then return the rest. Not only did this prove to be inconvenient for the customer, but the returns were usually dirty, in ripped boxes and often with brackets/screws/gaskets, etc. missing. This made it difficult for AAP to resell the return, especially if this was the second or third time the item was returned. Consequently AAP assumed the loss. 

Transporting data achieves industry compliance 

A goal of Advance Auto Parts’ MDM strategy was to shift the responsibility of loading product information from internal AAP data administrators. By enabling more than 650 third-party vendors to self-populate data, attributes and images, AAP reduced data entry costs by more than 50 percent and lowered its internal data administration headcount by half.  

AAP also increased the number of times it could do a full review of a vendor’s product information, moving from a yearly review to one that can be / is done monthly.  The company also shortened the time it took to buy the parts and distribute them down to the stores by 20 percent.  

Further, and perhaps most importantly, AAP was able to better comply with industry standards set forth by the AAIA including:

  1. Product Information Exchange Standard data, which is an industry standard considered a first step towards ensuring data synchronization with channel partners. It also provides a best practice for the management and exchange of product attribute information in the vehicle aftermarket industry. 
  2. Aftermarket Catalog Enhanced Standard data, which is the North American industry standard for the management and exchange of automotive catalog applications data. With ACES, suppliers can publish automotive data with standardized vehicle attributes, parts classifications and qualifier statements. ACES also prescribes a machine-readable format (XML) for trading partners to use in exchanging vast amounts of catalog information. 

AAP’s four-phased approach for MDM 

Advance Auto Parts’ Phase 1 MDM deployment began in 2010 and involved supporting industry-standard PIES data.  AAP built out the technical infrastructure that would allow for vendor-managed data to flow seamlessly from vendors to any system that would subscribe to any aspect of the provided information. In this phase, AAP provided a new streamlined process for creating SKUs. AAP creates hundreds of SKUs each week. 

Phase 2 of AAP’s deployment took place in the first quarter of 2011 and involved supporting the product maintenance process from vendors to AAP’s downstream systems. In this phase AAP allowed any updated information that third-party vendors provided to flow seamlessly through their systems. 

Phase 3 of AAP’s deployment took place in mid-2012 and involved supporting the AAIA’s ACES data. In this phase, AAP streamlined the process of receiving and validating ACES data. Later this year, AAP will start to publish this information to all sales channels. 

In the future (Phase 4), Advance Auto Parts will develop a vendor portal that will give AAP vendors the ability to directly upload and populate data into the AAP MDM platform and create the equivalent of an FTP “Farm.” This secure portal will allow manufacturers to make changes to a file or format on the fly and directly from the portal — thereby saving both the time and resources typically needed to publish reliable data.

Christophe Marcant is vice president of product strategy for Stibo Systems. Contact him at Christophe.Marcant@stibosystems.com.

Comments

By Sandeep Deshpande

Good strategy and very pragmatic approach. Since the data attributes for each part flows from the vendor, would be interested to know how parts with same set of attributes and attribute values, from different vendors, were managed to avoid part number duplication.

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