A leading automaker set out to answer a simple question: could emerging vehicle issues be identified before customers experienced them?
For most manufacturers, quality issues become visible only after a customer visits a dealership, a repair order is created, or a warranty claim is filed. By then, engineering teams are working backward to determine the root cause and assess the broader impact.
The goal was simple: identify emerging quality concerns before they became widespread customer and warranty events.
Introducing SIGNAL
SIGNAL transforms connected vehicle telemetry, diagnostic trouble codes (DTCs), warranty history, repair orders, dealer diagnostics, and manufacturing data into early quality intelligence. Powered by Databricks, SIGNAL helps manufacturers detect patterns sooner, prioritize investigations faster, and improve readiness across engineering, service, and operations teams.
The results extended beyond forecasting. Quality teams gained earlier visibility into emerging concerns, enabling faster investigations, improved service readiness, and a more proactive approach to quality management before widespread customer impact.
Strategic Shift
Before SIGNAL
- Repair orders and warranty claims were the primary indicators of quality issues.
- Investigations typically began after the customer and dealer impact.
- Vehicle, warranty, and service data were spread across multiple systems.
- Emerging concerns were difficult to prioritize consistently.
- Forecasting was limited by fragmented data sources.
After SIGNAL
- Connected vehicle and diagnostic signals provided earlier visibility into emerging concerns.
- Quality teams gained an early-warning path for investigation.
- Vehicle, warranty, service, and manufacturing data were unified for analysis.
- Emerging issues were surfaced and prioritized for action.
- Predictive models helped identify potential quality concerns before widespread customer impact.
Validating the Signal
Initial forecasting models achieved an average error of less than 3% when trained on the first two data tranches, demonstrating the ability to identify emerging quality patterns with a high degree of confidence. Even as additional vehicle data was introduced and conditions changed, the models continued to surface meaningful signals for investigation, helping quality teams maintain visibility into potential issues before they became widespread warranty events.
Looking Ahead
Every warranty claim begins as a signal. By transforming connected vehicle data into actionable quality intelligence, SIGNAL helped a leading automaker move from reacting to quality issues to identifying them earlier. The result was a more proactive approach to investigation, service readiness, and customer satisfaction, laying the foundation to reduce warranty exposure while improving the ownership experience.
