Application of Digital Risk Management Technology in Safety Critical Control Management

2019

Michael Hartley, Minetell; Sean Dessureault, MST Global; Glenn Lyle, MIRARCO

With the widespread use of internet of things (IoT) and tablet-based technology lowering the cost of digital data collection, vast quantities of data will become available to the mining industry.  How operations use these data to manage risks will determine who thrives and who perishes in the 4th industrial revolution. The push from investors, stakeholders and the International Council on Mining and Metals (ICMM) means that companies need to take the same approach to measuring material risk exposure and critical control management (CCM) as with operational or financial risks. The goal of digital risk technologies is simple: encourage, increase and improve data capture, collection and analysis to answer two questions: What is the current risk exposure? How effective are critical controls right now? App designs emphasizing addictive and compelling interaction and user feedback (aka ‘gamification’) drives a deeper, higher quality and more effective use of big data in the safety and health function.  Millennial and Gen-X workforce expect frequent feedback on performance and micro-awards which can now be done digitally.  Leveraging digital effectiveness can augment operational risk management (ORM) and CCM where data capture through gamification can be measured in terms of input quality (i.e. validity and reliability) and result in greater risk management insight.  The days of ‘tick-and-flick’ have made way for a data science approach to data capture from the industry’s most important assets - its people. Finding technologies that enable this capacity is of significant value to companies in the short, medium and long terms. An example is provided where machine health monitoring data, normally used for maintenance purposes, was used to track operator diving behavior and how providing rapid feedback to the operator reduced that behavior.  Another example describes how using in-cab tablets to automatically create observations is far less expensive than manually documented observations.

Mots Clés: Risk Management; Critical Control Management; Performance Measurement; Real-Time Monitoring; Artificial Intelligence; Machine Learning