‍The challenge

A top producer of heavy machinery had utilized telemetry data for over a decade to optimize its fleet and equipment management. However, this information was not being effectively utilized across all business units and the company's solutions were disconnected. The company aimed to change this fragmented approach and use telemetry data to provide its customers with unique, data-driven services through the Internet of Things (IoT) and data analysis. To achieve enterprise-wide insights and generate revenue from its data, the company sought the assistance of Cloudseed.

‍Our Approach

By utilizing Microsoft Azure and its specialized services for IoT, we assisted the client in constructing an all-encompassing telemetry platform that houses, oversees and evaluates telemetry data from various devices and products. This centralized platform enables the seamless transfer of information between different applications, and we also developed proprietary file parsing techniques that cater to various file sizes and schedules. Our connected data strategies allow the company to handle data across multiple business units and product lines using a single, enterprise-wide data repository. The field data collected is not only used to fuel the company's applications but can also be accessed by other systems through an API layer when required.

By utilizing a unified IoT platform that facilitates data analysis, the manufacturer is now capable of exploiting the benefits of telemetry. A more organized and accessible pool of company-wide data allows the firm to offer improved solutions, boost internal and partner innovation, and grow at a faster and more stable rate.

Cloudseed developed exclusive parsing methods to accommodate the varying utilization of the equipment in the field and the different customer product service cycles. These routines are capable of handling different file sizes and schedules and contain information about equipment usage hours, fuel levels, location, efficiency, and diagnostic reports. With Azure's IoT services that have the ability to scale, the manufacturer will be able to manage more than 2 million active machines, an increase from the current 300,000.

The client has implemented a centralized enterprise data warehouse to handle data across all business units and product lines. This has opened up new opportunities for the company to utilize advanced analytics and gain valuable insights. The client's applications are powered by data collected from field equipment, and this data can also be made available to other applications through the API layer when necessary.

The client has improved their ability to take advantage of telemetry opportunities thanks to the implementation of a unified IoT platform for data analytics. This platform offers a more cohesive and easily accessible set of data across the enterprise, allowing the company to offer superior solutions, foster innovation through partnerships, and achieve faster and more sustainable growth.

‍The Results:

‍The company has made significant improvements by increasing the number of installed connected machinery it can support in the field. Previously, the company could only support 300,000 machines, but now, with the upgrades, it has the capacity to support 2 million machines.

The data collected in the field daily has gone through a significant scaling process, from 15 gigabytes to 6,000 terabytes.

Streamlined information and procedures to promote uniformity and creativity.

Lowering the time needed to access equipment and job data refers to reducing the amount of time it takes to gather information about the equipment and job being performed. By reducing the time it takes to access this data from weeks to hours, the company has gained a significant advantage in terms of performance and productivity.