How can the Intelligent Enterprise Impact the Mining Industry?
The digital economy is disruptive. Mining companies need strategic priorities that drive transformation. SAP supports a reimagined set of E2E business scenarios to support the strategic priorities of working in a digital environment.
Make the business more predictable, sustainable, and safer - Advanced predictive analytics and machine learning integrated with real-time information help make vast operational data more actionable. Predict outcomes or exceptions to support the right decision-making, making mining more predictable, sustainable, and safer for the workforce
Collaborate with customers, suppliers, and workers - Transform interactions with all stakeholders into an interactive, collaborative, and responsive network to strengthen relationships, digitalize data exchanges, make the business more agile, increase profitability, and digitalize the worker.
Enhance operational and commercial agility - Achieve real-time visibility into operations and run a mine like a factory based on advanced planning and execution to increase agility by combining IT and operational technology (OT) along the entire pit-to-customer process.
Increase productivity through automation - Digitalize and automate manual processes and focus on value-added processes for employees while automating operations to keep workers out of hazardous environments.
Supporting next practices in mining with intelligent ERP Transformation in the mining industry is occurring at a rapid pace. Changes in technologies, business environment standards, and the need for agility require constant adaptation. Mining companies must be able to respond to rapidly changing conditions yet still comply with all standards. How does a digital core with a true single source of truth help?
Mining companies must respond to rapid change A digital core is an IT architecture that offers stability and long-term reliability for core enterprise processes yet also provides the flexibility to adapt quickly to new opportunities, challenges, and regulations. In today’s environment, mining companies cannot continue with old ways of working, so they need to change how they operate. This impacts the industry and its IT –the backbone of modern business –which has to be agile to ensure compliance. Support for mergers and acquisitions is also required to ensure swift adaptation to changing markets.
Mine smarter, not harder The ability to respond quickly is an essential part of managing a mining business. To do this, simulation, prediction, and analytical capabilities are important components. For example, this can be the simulation of profitability scenarios to identify the best method of mining or to determine the best time to sell a mine.
Generate additional value from data While overall processes in mining do not change much, the speed of business is disruptive. Mining companies need the computing capability to carry out complex algorithms with large data sets to support timely, real-time analysis. The base data comes from sensors that enable precise digital twins of equipment and processes. In a mine, data sets will be available that can be used by machine learning to improve equipment efficiency and availability. This provides more-reliable information for all related processes. For example, mine production output can be planned and executed more reliably.
Addressing innovative opportunities In the commodity business, you have to differentiate yourself. Mining companies must improve customer interactions as well as increase operational efficiencies to gain a competitive edge. This impacts every facet of business, including end-to-end (E2E) processes across departments and even company borders. Collaboration and sharing of resources will be part of the new operating models –from customers to mine operations.
The Intelligent ERP Bringing SAP S/4HANA and SAP Leonardo technologies together as a digital core will result in a more flexible and intelligent enterprise. To achieve next-generation business processes, mining companies need an intelligent ERP solution. For example, machine learning can help in dai