Proactive Detection of After-sales Vehicle Quality Defects: Insights from Recent Recalls

Recent recalls in the automotive industry underscore the importance of connected vehicle data in identifying and addressing potential safety issues before they escalate. OEMs can gain early insights into performance trends by analyzing connected vehicle and diagnostic data and applying ML/AI models. 

Such proactive quality analytics enhance driver safety and significantly reduce recall and warranty costs by starting investigations earlier, even before claims accumulate. Thus, they minimize impact and potentially save lives. 

145,000 EVs impacted by power loss

In November 2024, a significant recall impacted over 145,000 electric vehicles due to a fault in the charging system that could result in a sudden loss of drive power. The root cause was an electrical malfunction in the ICCU (Integrated Charging Control Unit), which led to a “fail-safe” driving mode, reducing drive power.

This case highlights the importance of connected vehicle analytics in proactively identifying such issues. By continuously monitoring the low-voltage system charging levels, anomalies could have been detected earlier. Real-time alerts to field quality investigation teams and after-sales warranty stakeholders would allow for faster root-cause analysis and corrective measures.
Since this recall also manifested in HW failures caused by overvoltage inflicted by SW components in the ICCU, earlier detection could have significantly reduced the total recall cost.   

700,000 vehicles impacted by tire pressure warning light failure

In December 2024, a leading OEM initiated a recall affecting nearly 700,000 vehicles. The issue involved the tire pressure monitoring system (TPMS), where the warning light failed to remain illuminated across drive cycles. This failure meant drivers might not be adequately alerted to low tire pressure, increasing the risk of accidents. 

The root cause of the issue was traced to a software anomaly within the TPMS system. By leveraging connected vehicle data analytics, this issue could have been proactively identified through real-time monitoring of telltale light activations on the instrument cluster or infotainment system, combined with tire pressure readings to detect and flag anomalies early.

Such early detection would have empowered the manufacturer’s quality teams to investigate these anomalies promptly and deploy targeted software patches, thereby enhancing safety, minimizing recall risks, and reducing warranty claims.

This recall underscores the critical need for continuous monitoring and diagnostics to flag software-related performance issues. By leveraging real-time data from vehicles, such problems can be mitigated before regulatory non-compliance or widespread customer impact occurs. Early intervention could have significantly reduced the scope and cost of the recall.

Leveraging real-time and business data for safer vehicles can also help sustain long-term growth

These recalls emphasize the potential of connected vehicle data to transform how automakers address after-sales quality. By leveraging data from vehicles already on the road, the dealership, and claim feeds, manufacturers can identify patterns and start investigating anomalies in performance metrics, leading to earlier detection of emerging issues. This proactive approach not only enhances driver safety but can also minimize the scale and cost of recalls, warranty and reserves. 

Connected vehicle data offers automakers an invaluable multi-sensory source that can help address issues much earlier. By fostering collaboration across the industry and leveraging insights from advanced analytics, the automotive sector is taking a proactive stance in ensuring vehicle reliability and safety. These efforts are essential for meeting drivers’ evolving expectations and maintaining trust in the industry’s commitment to safety and innovation.

In today’s competitive market, time to market is key. It becomes very challenging to keep up with the innovation hockey stick while keeping cars safe and of high quality. That said, automakers face significant pressures to reduce costs, often through workforce reductions or scaling back on technology investments. Addressing early warranty and recall detection presents a unique opportunity to meet cost reduction goals by leveraging existing technology in the era of advanced AI rather than cutting resources. This will allow OEMs to Develop AI models to spot micro-trends early, enabling proactive quality issue detection. Further, building workflows and constant monitoring will streamline recovery, prevent recurrence, and help measure ROI.

Connected vehicle data can be leveraged to identify and investigate potential quality issues early, reducing the frequency and scale of expensive recalls and warranty claims. Importantly, this approach aligns with long-term growth objectives by safeguarding vehicle quality and preserving consumer trust—elements critical to sustained success in a rapidly evolving industry.