SCRC Meeting: Advanced Auto Parts is investing in Advanced Analytics to drive competition

We had a very successful SCRC meeting this past week, and the speakers provided some fantastic insights to the group on the emerging trends in the digital landscape facing supply chain executives.

Todd Greener, Senior Vice President of Supply Chain at Advanced Auto Parts, led off the discussion (after I provided an overview of what was happening in the digital space).  Advanced Auto Parts (AAP) is a $10B company that provides after-market parts to auto owners, and is seeing strong growth based on vehicle sales.  They are also keenly aware of the move towards autonomous vehicles.  The organization is moving towards an increasing analytical function, and a core cultural belief is around a passion for customers, speaking up, taking action, and moving forward.   With the merger between AAP, Carquest, and WorldPac, there is now a long-term strategy to win, and supply chain growth is a big part of connecting assets and presenting products to the customer is a big part of the strategy.

The company has made a significant investment in talent to begin its journey into the world of Artificial Intelligence. (Our own NC State doctoral graduate, Yung-Yun Huang, is working on this effort!)  Much of this investment is being driven because of the complexity and agility that is inherent in the auto parts business.  AAP has over 300,000 customers a week they distribute to, and a lot of small garages as well as the DIY customer.  Having the part within 30 minutes is really important if a car is up in a bay, and an installed base of 2 million vehicles is a huge part of the value proposition.  Last mile fulfillment is a key component of value in the network, and timeliness is key.  Having all the brands from OEM and near-OEM brands available at the right price point for customers, to facilitate easy decision-making, is an important value proposition.  The current AAP distribution is not integrated across the three banners, so there are clear opportunities for improving efficiency.  The numbers themselves are staggering:

• Carquest – 20,000 SKUS same day delivery, 90K SKU next day
• Advanced Auto Parts – 40,000 SKUs same day delivery, 120,000 SKU’s next day
• World Pac  –  45,000 same day delivery and 110,000 next day.

Each of these companies has a different catalog and availability screen online.  Cross-banner functionality is a key part of the integration effort.

“Right part- right place” is a key metric for availability that is at the core of AAP’s digital transformation.  Machine-based learning will be a core part of identifying how to put the part out in the right place to be able to sell it.   To provide this level of variety with same or next-day customer service, AAP is by definition a slow-moving inventory business, with about 1.2 turns per year.  There are a lot of assets and 100M SKU-Store combinations involved, and landing those parts to serve the long-end of the tail is a continuous challenge. Assorting and stocking in the network is a big cultural change for everyone in the organization.

AAP has over 17,000 vehicles that do last mile delivery, pizza-delivery style, with over a million deliveries a week to customers.  Todd notes that “Historically very decentralized, we have taken an initiative to centralize management of these assets, and provide visibility to how we are performing on last mile.  Telematics, third party software in the storefront, is being used to measure our end customer delivery responsiveness.  This investment came about as we recognized that in a meeting, a board member asked a simple question: how long does it take  to get products to customers, and do you know if you are performing well or not?  This question helped us recognize that we had no visibility over last mile logistics.  So we have started to create an exciting roadmap for improving our order delivery time on last mile, but also having assets deployed and utilized.  Big efforts around Machine-Based Learning is occurring around dynamic dispatch and assets on the road and in our stores.  How do we do more order promising with our customers, as most deliveries occur between 10-3 when the garage is open, and at the end of the day, how do we set up for the next day?  This is a technology rich area, and excited about the power of the fleet.

AAP is working on transforming end to end processes with big data.  There are over 2M catalog lookups per week, over 6500 stocking locations, 100M store-sku combinations, 10M units shipped per week, and 1M professional deliveries per week.  The focus of using big data is on adding big data expertise across key functions, upgrading and standardizing data/analytics infrastructure, incorporating machine learning/AI capabilities to improve traffic, assortment/stocking, delivery, and pricing.  The team is also focusing on the need to drive electronic transactions to replace phone orders for customers. The quality of the information is much better and actionable when captured by a machine.  Theuy are also incorporating MBL and AI in traffic management, Todd notes that “Being able to make rapid decisions from a transaction standpoint is critical for us.  Telematics data, and the 30 second pings, the fulfillment information, the driver information, and what the vehicles are doing is all data that can be leveraged.  And we know we have to invest in these capabilities to be competitive.”