OT Data Applications

By Julian Dierkes

{Disclosure: As previously mentioned, I was delighted to be invited to Oyu Tolgoi by the company’s communications department.}

In addition to the pervasive focus on safety, the utilization of data is visible throughout Oyu Tolgoi. The kind of control room that centralizes information and decision-making over the chemical processes as in the photo below is not unique to Oyu Tolgoi of course.

Yet, data appears to be collected everywhere throughout the mine operations and to be displayed to inform safe and efficient operations.

I was constantly reminded of the promise of the “management information systems” wave in corporations that aimed to provide dashboards to management that would allow them to control operations in real time and on the basis of constant data, whether that data be from or about production, efficiencies or market conditions. Some of that promise appears to be realized at OT in more extensive fashion than I have seen elsewhere.

Managing Maintenance and Faulty Equipment

Take the maintenance of machinery and equipment as an example.

In visiting underground and open pit operations, as well as the concentrator, screens documenting the state of repair of equipment could be found everywhere.

Here’s the example of a screen providing information about the personnel cage that serves as an elevator to the operations 1,400m underground.

Not only does it display the schedule of arrivals and departures, but it also shows a delay due to unscheduled maintenance.

Everywhere else in operations, monitors showed similar information.

In the open pit, for example, the giant 300t trucks that move ore out of the pit were all traced on a screen, showing the state of their operations, where exactly they were and what maintenance issues may have arisen.

The incident reports that I mentioned as an element in the focus on safety, also included information of the cost incurred by incidents or malfunctions.

This is where the tracking of equipment goes beyond attention to safety and appears to allow operators to also manage efficiency. In the case of the giant trucks, the weight of their load is not only shown on a large display on the side of the truck, but it is also tracked as data. Other screens thus showed how close operators had come to the maximum load of 300t, presumably striving to consistently reach that maximum but not surpass it given the time from the open pit to destination and the constantly repeated processes that make this time matter in cumulation. Different crews were also compared as to their efficiency in this regard on the same screen as were day-to-day and week-to-week trends.

Spill-Over of Focus on Data

Some of this focus on data is surely driven by the scale of operations at OT. Given the number of truck movements per shift, it makes sense to try to maximize these movements down to the final ton near the maximum pay load in repeated activities. With the focus on safety, I see a clear trajectory by which this focus might “spill over” (not in an, er,  accidental fashion of course) from OT to other Mongolian activities. With data-driven efficiency, I am not so sure. Obviously, this data utilization requires planning and investment resources that might make it cost-effective only on a large scale and not applicably to many business contexts in Mongolia. What does seem applicable, however, is the deliberateness with which processes are designed and monitored.

About Julian Dierkes

Julian Dierkes is a sociologist by training (PhD Princeton Univ) and a Mongolist by choice and passion since around 2005. He teaches in the Master of Public Policy and Global Affairs at the University of British Columbia in Vancouver, Canada. He toots @jdierkes@sciences.social and tweets @jdierkes
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