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Uncovering Supply Chains’ Deepest Risks With Data Innovation
The ongoing trade disputes between the U.S. and China, and between South Korea and Japan, have forced corporates to shift their supplier bases into new markets to maintain their business continuity. Expansion of any business means unfamiliar territory, whether it be new geographic markets, following new rules & regulations, business partners or otherwise. Also complex regulatory demands, for instance, are a major headache, leaving supply chains at risk for noncompliance when operating with suppliers and business partners in new markets, often with unfamiliar compliance requirements and such changes inevitably cause disruption among their corporate client bases.
In a discussion with PYMNTS, Resilinc Co-founder Sumit Vakil told, "on top of geopolitical factors, there are a slew of risks facing supply chains from many angles. The technologies that enable seamless, secure movement of data for risk analysis has been driven by the rise of Software-as-a-Service platforms but still presents one major hurdle: what to do with the information being collected".
Artificial intelligence (AI), machine learning and natural language processing (NLP) are the three technologies have the most promise in positively disrupting this area of supply chain risk management. Supply chain risk mitigation platforms like Resilinc Eventwatch AI is an ideal combination of AI, machine learning and NLP that can not only analyze data, but they can learn from human behavior to suggest what actions need to be taken to mitigate supply chain risk.
Though this applies to the information shared between companies, certainly, yet these technologies are beginning to allow for risk mitigation efforts to take a global, real-time view of current situations.
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