Securing Complex Supply Chains with AI
Govciooutlook

Securing Complex Supply Chains with AI

By Gov CIO Outlook | Thursday, April 04, 2019

Louis Columbus, a leading supply chain analyst, stated that the biggest challenge faced by the high tech industry in 2019 is to secure a company’s supply chain. The main reason for the challenge is that the supply chain grows more complex, and manufacturers find it difficult to answer the question with confidence about who their suppliers are. Previously, the problems with supply chain would revolve around the product quality and cost. The high tech products of today are prone to making national security vulnerable.

PricewaterhouseCoopers (PwC) has launched a new platform called Know Your Vendor, a new platform for manufacturers to reduce downfalls surrounding reliability and vendor risk. The user can easily identify the primary supplier, but when it comes to downstream manufacturers, it is difficult to know who supplied a specific subcomponent upstream. Lack of clarity makes it difficult to find the rogue spyware chip that sneaked into the finished goods before the manufacturer can realize. The PwC software makes use of machine learning and to assist the manufacturers in opening a window to their supply chain to know about the potential compliance issue and risk exposure in their supply chain. The platform helps the business to identify the vendor in the business’s supply chain. The data gathered from various sources will support the manufacture to quantify the risks involved in conducting business with subcontract vendors. The task is very, but by utilizing big data and then training machine learning models, the result could be obtained.

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Constantly changing global supply chain makes it difficult for people to handle complex tasks; hence, the most feasible option is to implement automation. The familiar combination of data science, domain expertise, and data engineering will help in automating solutions. To identify every instance of complaint regarding product counterfeiting, the manufacturing customer can scan social media, customer portals, and other sources using natural language processing. By using machine learning, the service is able to identify the level of confidence regarding risks, and in some cases, the solution can also find an alternative sourcing strategy which reduces risks and regulatory compliance issues. Humans cannot be eliminated from the equation but deciphering global supply chain has become so complicated that a machine is needed to resolve certain challenges.

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