The race is on. Companies across every industry are investing in the digital transformation of their supply chains to mitigate disruptions, make better and faster decisions, optimize operations and improve their customers’ experiences.
But according to a recent analysis from Gartner, most Chief Supply Chain Officers (CSCOs) are struggling to deliver on company expectations. Once again, they’re struggling with familiar challenges such as organizational silos, limited access to or usability of data, and outdated legacy technologies.
If only these CSCOs could learn from an industry that has cracked the code on data-driven supply chains that benefit entire ecosystems of manufacturers, suppliers, distributors and customers.
Well, they can. That industry is the $535B automotive aftermarket.
Imagine the Future State
The massive automotive aftermarket includes all of the vehicle parts, equipment, replacement tires, repairs and accessories sold after the sale of an original vehicle. It includes companies in manufacturing, re-manufacturing, distribution, retailing, and installation of replacement vehicle parts, equipment, service repair and automotive accessories.
Thanks to the foresight and imagination of many of the industry’s leaders, the automotive aftermarket is far down the path of digital transformation. Rather than simply rushing to implement new technologies without a bigger picture vision, a consensus emerged as to what the industry was striving to enable.
Leaders imagined a future state in which they had deep visibility into their supply chain ecosystems — the kind of visibility that would enable partners to track a product from the factory, through the distribution channel, to the store and ultimately to the vehicle a part gets installed in. They imagined capturing the performance and failure rates of products. This deep visibility would have the potential to deliver a plethora of benefits to every business in the chain.
Insights Start with Actionable Data
As Gartner notes, many companies struggle with data. So do entire industries. The automotive aftermarket industry has benefitted greatly from industry-wide data standards such as the Aftermarket Catalog Exchange Standard (ACES) and the Product Information Exchange Standard (PIES). These standards ensure compatibility of aftermarket parts and accessories with various vehicles while reducing errors in product information exchange.
With industry-wide data standards in place, aftermarket companies could more easily build “data factories” for onboarding, ingesting and normalizing data so that it is actionable before being published out to the ecosystem.
To supply chain professionals who are struggling with data, first ask whether their industry has large buying groups and/or associations that can come together to create a standard view of data across the industry. Data standards are foundational.
The Many Benefits of Transparency
Many people and organizations harbor a natural inclination to hoard data instead of sharing it. Follow the lead of the automotive aftermarket — share. The benefits of sharing data across supply chains are simply too compelling to ignore. And those who opt out will find themselves increasingly disadvantaged.
First and foremost, when you're a participant in the data pool, you’re ensuring that your parts, products or solutions are going to get in front of potential customers. You don’t want to be invisible or force prospects to hunt down information on your offerings. Second, once you're in the data pool, you can focus on winning based on delivering great customer experiences.
For example, customers in the automotive aftermarket benefit from predictive maintenance that goes beyond the typical recommended service intervals outlined in your average vehicle owner’s manual. By “connecting all of the data dots” on what's been made, where's it’s been sold, and what repairs are being done on equipment, auto shops can now recommend services to a customer based on vehicle maintenance trends in a customer’s own zip code, taking into account the impact of the local weather and other salient factors.
Also, understanding repairs at the field level can inform manufacturers on production and distribution needs. It can help everyone who makes, moves or sells a product optimize inventory and reduce stockouts. Connecting all of these dots presents a myriad of compelling use cases for every company in the value chain.
AI and machine learning introduce an even greater leap in possibilities. For example, we’re not that far away from a future in which our vehicles will become smart, connected concierges that schedule our next service appointments for us. AI-powered ERP systems will automatically optimize inventory and order processes, further reducing the need for manual intervention, allowing workers to spend more time on customer service and innovation.
CSCOs struggling to realize ROI from their digital transformation initiatives would do well to study the automotive aftermarket’s template: start with the data, embrace transparency and focus your efforts on the business problems you most need to solve. As the automotive aftermarket has shown, the benefits of data-driven supply chain ecosystems are not only attainable, but they are also compelling.
