One of the world’s largest mining contractors was looking for ways to optimize operations. Like many mining companies, however, it found itself working with siloed processes, isolated teams and too many manual, paper-based tasks.

Complicating matters was the fact that the company had a growing volume of operational data that it could draw on to drive efficiencies—but understanding, interpreting and acting on that data was a slow, difficult process. The company needed a solution to identify, analyze and address obstacles to mining productivity. Specifically, it wanted to use its IT data to improve mine-site efficiency, with a focus on hauling management.

Strategy and solution

To optimize the hauling of materials from mines, the company created a system that uses IoT, analytics and machine learning to collect and analyze heavy equipment data. The system then recommends actions in key process areas, including:

Road maintenance

Truck sensors capture vibration and movement, and then send alerts to maintenance teams to inform them of roadway areas requiring urgent attention.

Maintenance optimization

A new dashboard provides maintenance schedule recommendations based on truck health, part readiness and manpower availability.

Inventory management

An inventory management system—supported by predictive analytics—monitors fuel and parts inventory levels for future maintenance and operations.

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With Accenture’s help, an innovative system is now in place that delivers actionable insights to help the company better manage people and equipment, prioritize tasks, and rapidly respond to changing conditions. Key outcomes include:


More than 700 users now have near real-time access to key metrics about mine operations.


IoT and predictive analytics provide performance insights that have prolonged component life by 10 percent.


Real-time visibility into operations and actionable recommendations have allowed the speed of hauling to increase by 5 percent.


Operational improvements made possible with the new system have reduced overall truck-hauling costs by 11 percent.

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