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Case study

The challenge

A large US heavy equipment manufacturer and logistics company sells its vehicles to dealers who, in turn, rent or sell them to individual customers. An antiquated, on-premises data center made maintaining and managing its 400,000 pieces of heavy equipment a challenge.

This outdated environment also made it difficult to scale its vehicle monitoring capabilities, assess vehicle health proactively and capture analytics for insights into performance across the company. With its legacy data center at capacity and the high licensing fees associated with available marketplace solutions, the manufacturer needed a partner to help transform its business operations.

Our approach

Leveraging Microsoft’s performance testing Azure DevOps cloud platform, Cognizant developed a custom framework using defined parameters to capture health messages from each of the manufacturer’s vehicles. This system provides a customized view of a vehicle’s mission and overall health, including fuel level, mileage, engine start/stop, service required and parts needed.

In addition to automatically notifying the vehicle owner that service is needed, the system integrates captured data into a separate analytics engine that provides valuable insights to other divisions across the company. The flexible, easy-to-configure framework enables dealers and their customers to monitor vehicle performance in real time, better protect investments and manage fleet needs.

Scaling capabilities and protecting equipment performance in real time

Digital transformation—migrating to the cloud—enables the manufacturer to scale its vehicle performance monitoring capabilities from 400,000 to 2 million vehicles. Through analytics, dealers can predict maintenance requirements and better manage their service supply chains. A key differentiator for the manufacturer is offering the system as a service through its dealers.


increase in vehicle monitoring capabilities


vehicle-related messages ingested per second


savings per year in tool licensing costs by avoiding the purchase of internet of things virtualization