Big Data Analytics, Applicability, Implementation & Leveraging it in Mining Operations
For over a decade working in the mining industry's Finance, Projects, Systems and Operations Improvement functions; one word that has increasingly became a central buzzword from my peers in other industries has been ‘Big data’. It was during these past years that mining experienced one of the most notable booms in my career where margins were higher and any talk of increasing operating efficiency, margins and reducing costs were not considered part of the core function. Talk of Big Data, you will be laughed at. However, the recent developments in the global economy and metal prices over the past five years has shifted the key focus of mining operations back to reducing the cost of mining and improving efficiency across the board.
The current operating environment now calls for smarter decision making , supported by facts and these facts are all hidden in the data available.
With every phase of a mining company’s value chain producing large amounts of data on a daily basis, big data plays a crucial role in achieving better decision making processes backed with business analytics and predictive analytics. However, in order to achieve this mining companies need to identify how to manage the diverse range of the data at hand, which data to collect and how to prioritize it. They also need to create interfaces to make big data analytics possible to improve day-to-day operations.
Big data, if used effectively can be used to monitor mining activity in real time and thus help companies achieve competitive advantage. In fact, a number of critics are pitting big data as the element, which will see some companies leapfrog others to become best in class in 2020 and beyond.
Data is woven into every sector and function in the global economy, and, like other essential factors of production such as hard assets and human capital, much of modern economic activity simply could not take place without it. The use of big data — large pools of data that can be brought together and analyzed to discern patterns and make better decisions — will become the basis of competition and growth for individual corporations, enhancing productivity and creating significant value for the world economy by reducing waste and increasing the quality of products and services.
Five ways Mining Operations can leverage big data:
1. Unlocking data to improve business operations
Big data has the capacity to facilitating faster and more responsive business decisions based on business analytics and predictive analytics. Mining corporations capture vast amounts of data on a daily basis and big data analysis can help them make sense of this information quickly. Mining firms can use this information to predict market demand and optimize supply.
2. Reducing down-time and boosting efficiency when it comes to equipment
Managing equipment is one of the most important aspects on a mine-site. Any down time, repairs, or poor logistical planning can have a huge impact on the efficiency and thus the profitability of a mine. Big data can shed light on equipment management to help mining operators drive total efficiency. Furthermore, data such as tire pressure, scheduled repairs, faults and driver information (routes on site, speed, proper use) can all be captured, analyzed and reacted to.
3. People management and operational excellence
Big data can help site managers collect more accurate and detailed performance information on everything from product inventories to sick days and therefore expose variability and boost performance. In fact, some leading companies are using their ability to collect and analyze big data to conduct controlled experiments to make better management decisions.
4. Big data and continuous improvement
Big data cannot only be used to control current operations, but also leveraged to improve operations in the future. Mine site managers can get an understanding of the most productive site conditions and look into the conditions surrounding them. These conditions can then be replicated for greater productivity and efficiency in the future.
5. Minimizing risk
Sophisticated analytics can substantially improve decision-making, minimise risks, and unearth valuable insights that would otherwise remain hidden.
Implementing big data
When rolling out the use of big data its important that you consider the potential teething problems and stumbling blocks that could occur early on, such as legacy systems, privacy aspects as well as storage and security challenges.
Mining corporations also need to ensure that employees are fully equipped with the tools required to manage the volume, variety, velocity and value of data from across the business. Big data bring with it a wide variety of advantages, including the ability to utilize data to operate mines proactively rather than analyzing data and results from the past. However, in order to do this effectively the people on the ground need to be given a solid understanding about how to best define rules around how data gets procured, stored, maintained and used to achieve the best business outcomes.
