Businesses are adopting predictive analytics for supply chain management aspects such as sourcing and logistics. But they can also use data to control a variety of risks.
Richard Parke, head of international supplier organization for global supply chain risk management company Avetta in Orem, Utah, says machine learning—an application of artificial intelligence—can help extrapolate key trends and establish baselines to reduce risks. For example, Avetta's web-based platform connects more than 300 companies with 60,000 suppliers' safety history, track records, performance statistics and other data points.
“We aggregate the data across industries to isolate trends in safety performance and establish baselines and norms, and use predictive analytics to identify which types of trends and approaches can reduce and eliminate accidents," he says.
In financial supply chain management, businesses can use the same technology to help identify partners who have long-term financial stability, and will pay their invoices and stay in business.
“If you bring in contractors and suppliers that don't have the longevity or financial resources to stay within the supply chain, it becomes very disruptive to the supply chain operations," Parke says. “Ensuring they have financial viability and enough capital to complete the job is very important."
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