Inconsistent and nonintegrated data often stored in silos during the warranty period impedes manufacturers’ field diagnostics and repair services. Consolidation and analysis of this data takes too much time and leads to high warranty costs for the company.

Real-time telematics data can be leveraged in new ways to reduce costs and increase customer satisfaction and trust. Automobile manufacturers can now avoid vehicle failure on the road and schedule maintenance intervals in advance.
This results in lower maintenance and warranty costs of up to 20% and fewer critical incidents as a result of the ability to react before an incident happens. Additionally, predictive diagnostics increases customer satisfaction, brand loyalty, and vehicle uptime.

A typical Predictive Analytics process

Predictive Diagnostics

Integrating vehicle telematics, warranty, production quality, service and after-sales data to enable the use of intelligent classification and prediction, improves the quality of data and leads to reduced time-to-correct cycles. Setting up diagnostic knowledge databases including defect symptoms and solutions supports this predictive diagnostics effort. Leveraging data mining and machine learning techniques to create automated diagnostic, scripted repair processes and identification of which parts need replacing can help to anticipate potential incidents.

Using real-time telematics data, highly detailed information for every component of the car is directly transmitted car manufacturers.
Using predictive diagnostics, the applied algorithms are able to analyze and recognize patterns within delivered data and calculate probabilities of upcoming failures in the future.
This allows the manufacturer to contact customers and schedule repairs in advance and thereby saving the manufacturer costs and impact on customer satisfaction.

Predicting and diagnosing potential incidents in the automotive sector is becoming increasingly critical to stay competitive.
Reducing the time required for defect identification and repair leads to increasing customer satisfaction and brand reputation. Decreasing the detection-to-correction cycle allows clients also to benefit from a significant reduction in claim-related and warranty costs. Less warranty claims result in an improvement of cost and accrual forecasting since less warranty accruals are needed.

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