According to Warranty Week, claims totaling 46 billion USD were paid by the global automotive Original Equipment Manufacturers in 2021. 54 billion USD in accruals have been made. This means that based on experience, roughly $630 per vehicle sold is held back for upcoming warranty issues. The challenge to avoid or reduce warranty claims and their costs is enormous, as flaws can happen along the complete value chain. This is where a digital twin can help.
The current warranty landscape
Lean production leads to a higher efficiency, less material usage, and reduced costs. But it also leads to a higher risk for new, unknown quality issues, and therefore potential warranty topics. With more and more software built into a vehicle, the percentage of software-related warranty claims is increasing year over year. The need now is to detect new unidentified failures and problems as early as possible.
Generally, software issues can easily be fixed via over the air and do not need a recall. This leads to a reduction in total warranty costs for software related warranty topics in a customer-friendly and efficient way. At the same time, the total figures of global claims and accruals did not change much over the last five years. What does that mean?
Early data-driven warranty re-invention
The global automotive OEMs have always faced warranty issues and therefore their warranty management capabilities are quite mature. From including social media data to stay aware of trends, to using IoT data to decrease failure rates in plants, some over-performing companies are leading the direction in leveraging data for warranty topics.
Our 2020 IBV benchmark study “data driven warranty reinvention” emphasizes this point, given the responses of the 300 automotive leaders responsible for warranty management in their organizations across 11 countries in Asia Pacific, Europe, the U.S., and Canada. They were, among other things, asked for their warranty KPIs. The ranges of performance fed back to us show potential for improvement for every company. Even the over-performing early technology adopters have still a lot of possibilities to better use their data.
Opportunities with data-driven digital twins
Much has happened in engineering (e.g., avoiding warranty issues through simulation), manufacturing (e.g., detecting and preventing failures through sensor data analysis) and after sales (e.g., detecting trends through social media analysis) through the usage of data analytics. But even as the adoption of new technology supported new warranty improvement practices, it remains a huge undertaking to root cause failures backwards through the value chain. Additionally, the warranty costs are still handed back to the supplier.
The reasons are manifold—from siloed information, missing data, and unclear data ownership to outdated analysis tools—and the recent manufacturing 4.0, smart factory or internet of things approaches do not resolve these issues completely and to full satisfaction.
The new shiny knight for reinventing warranty analysis is the digital twin. Here’s why: The digital twin is not a one-time project to hook up different systems to connect different sensors. It is a process. More specifically, it is a living process that makes true root-causing and early detection possible, including cross-referencing alerts along the value chain, from design and build to sales and after sales. It gathers and connects information, making it cross-referenceable and ready to analyze group-wise.
The digital twin has the power to resolve the old issue of, “We know the failure part, we kind of know which vehicles this part was built in, but we do not know which supplier batch was erroneous. Therefore, we cannot recall only the affected vehicles, we need to recall all possibly affected ones.”
When the digital twin of a vehicle spans from design and engineering to manufacturing of the operational twin, we have all the information together for both warranty reduction and warranty avoidance.
Warranty management is a continuous process. And it will be reinvented with the wide availability of digital twins.
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