Aftermarket supply chain analytics
Take three minutes to learn how analytics can help
The aftermarket supply chain is becoming a data-rich area, as products are increasingly loaded with sensors, monitors, and more. It’s no surprise, then, that interest in using business analytics to extract insight from supply chain data is growing. Take three minutes to give yourself a mini-crash course to learn how leaders are using aftermarket data to improve the supply chain.
Targeting key business issues
When it comes to the aftermarket supply chain, many companies lead with the data: “What do we have, and what can we do with it?” For others, it’s about a specific tool: “If we implemented this tool, what aftermarket insights could we generate?” In aftermarket and elsewhere in the supply chain, many are deciding to start with well-defined use cases that address the core business issues and drive greater value to manufacturers, dealers and, most importantly, the end customer.
How do you apply analytics to supply chain data to create value?
Using supply chain data in the aftermarket
Stay a step ahead of big warranty and recall issues
With aftermarket data, it’s possible to anticipate and plan for warranty and recall issues far earlier–before the media becomes interested and often in time to address performance issues through design changes.
Deliver on the service promise
With IoT data giving us more insight into which components and subsystems might fail, improvements in service scheduling, aftermarket inventory deployment, and other activities can decrease the time the product may be out of commission.
Optimize pricing and inventory
Knowing which parts are making the most money, where the competition is winning, and which products are selling the most are just some of the insights that can help pricing and inventory decisions.
The entire aftermarket business hinges in part on initial product quality. By applying analytics to supply chain data, it’s possible to improve the information used to inform upstream processes in manufacturing quality, supplier quality, and product development quality. In the end, a higher level of product quality can reduce warranty and recall costs while improving customer satisfaction.
Aftermarket supply chain analytics in action
When a large, global car manufacturer faced stubborn safety issues, proactive sensing analytics was used to glean insights from aftermarket supply chain data. By connecting this data across warranty, the voice of the customer, and the voice of the dealer, the company developed an alerts management model that helps supply chain leaders and others rapidly detect and prioritize safety issues and better scope recalls. Download Creating insights in the aftermarket for more about this solution.