OEMs that utilize AI for the right aftermarket use cases will gain a transformational advantage, one greater than an extra 1,000 human specialists could offer. By automating complex processes and extracting value from existing data, ROI can be boosted by 50x.
A sophisticated solution will aggregate your datasets autonomously, even your most elaborate, historical parts and contract pricing information, and use it to fuel enterprise-wide data intelligence and increase supply chain resilience.
Winning in the aftermarket requires the ability to source insights from existing data and analyze it in real-time. This capability not only makes activities like predictive maintenance and parts planning possible, but it also makes them globally scalable.
“This is nothing short of a paradigm shift. OEMs that make AI a top priority will access the revenue streams of the future.”
Taj Abdullahi, Director Product Management, Syncron
In this article, we will zero in on the impact that AI has on parts planning, parts pricing, and contract pricing – with a focus on predictive and operational advantages.
Predictions powered by data
AI-enabled demand forecasting for parts planning is a major aftermarket advantage for OEMs. In this era of supply chain disruption and uncertainty, the ability to boost efficiency and resilience is vital, and OEMs can use these technologies to ensure demand planning precision. The result is optimal inventory levels and improved customer satisfaction.
The integration of predictive maintenance is also a prime example in the context of parts planning, with AI-based solutions enhancing the collaboration between service and inventory teams. By processing historic data and real-time customer data simultaneously, part failures can be pre-empted with elevated levels of accuracy.
AI also allows OEMs and distributors to do data-driven cost predictions for contract pricing. ML has a key role to play here, taking data like material, labor, and travel costs into account and identifying ways to optimize pricing throughout a contract’s lifecycle. This equips teams to secure their aftermarket margins and improve profitability.
Optimizing operations
In such a crowded, complicated market, an OEM’s aftermarket success is impacted heavily by the suppliers and dealers it engages with for parts planning. AI can be used to ingest performance data to determine the most reliable partners to work with and to score them accordingly. This significantly reduces disruption and helps deliver the high-quality outcomes customers expect in 2024.
Another valuable activity OEMs can optimize with AI is yield management, allowing them to continuously monitor and adjust contract pricing based on expenses, target margins, price elasticity, and segmentation. AI’s ability to process enormous amounts of diverse data means that OEMs can provide customers with optimal quotes, maximizing levels of acceptance while supporting margins.
Understanding which prices are elastic and which are not is crucial when engaging in the aftermarket, but also knowing to which degree they are or not. Achieving this level of granular visibility on an ongoing basis with a human team is impossible, but AI enables you to keep track of these calculations and maximize part sales.
Automation in action
Effective service lifecycle management (SLM) is essential for aftermarket success, as it relates to the alignment of functions like parts planning and field service management. AI is now enabling OEMs to autonomously orchestrate functions, teams, and tools like before.
Al-Futtaim, a global leader in the automotive aftermarket sector, uses a suite of AI-based Syncron solutions to enhance their SLM. The combination of capabilities enables the organization to price parts rapidly and precisely, while also tracking stock levels so that prices can be adjusted dynamically in real-time in the event of excess. This was achieved by our Connected Service Experience platform (CSX), using autonomous logic technology and advanced predictive analytics.
Syncron also helped automate dealer-to-OEM returns processing for PACCAR, a manufacturer of premium light, medium, and heavy-duty trucks. Without the automated capabilities made possible by AI, back-office teams were burdened with manual tasks like line-item removals, and dealers were sending returns in bulk at month end and without approval.
PACCAR wanted a globally scalable way to monitor and process all return transactions and associated data, factoring in part orders, warranty management, and third-party logistics. To autonomously coordinate these elements, a connected platform with AI at its core was required.
Our CSX Platform made it possible for PACCAR to achieve predictable monthly and quarterly return projections, significantly reducing warehouse backlogs, while also eliminating unnecessary IT services and program administration costs.
Beyond parts and contracts
AI can also have a powerful impact on other key aspects of aftermarket activity, including warranty processes. From analyzing claims to detecting fraud, to intelligent rule cataloging and claims scoring, AI-based tools are now being used to pinpoint costly anomalies and improve transparency.
Crucially, by bringing more valuable data to light than ever, these technologies are helping once siloed business units to collaborate and provide better service than ever. Inventories can now be managed dynamically based on demand forecasts, and field service history insights are being used to optimize contract pricing.
To find out more about game-changing applications of AI in the aftermarket, download and read our latest eBook on the topic!