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Mitigating supply chain security risks

supply chain

Organisations must implement robust security measures to protect their supply chain from cyber threats such as data breaches and malware attacks.

With the increasing use of digital technologies in supply chain management, cyber security is a critical aspect of supply chain management.

The adoption of ‘Just-in-Time’ and ‘lean’ philosophies that relies on the shipment arriving at the moment a recipient needs it has undoubtedly increased efficiency yet the absence of safety stock has increased the vulnerability of companies to adverse events. In addition, globalisation has led to increased complexity and companies becoming less vertically integrated. 

“Data quality and quantity are major challenges for supply chain management, including to the development and use of artificial intelligence,” said Bryan Oak co-founder of Kompozable. “Without large volumes of quality data, it is difficult to train algorithms and develop predictive models. Data security concerns also increase with each new data source, and incomplete data can lead to blind spots and missed opportunities for optimisation and execution. 

“Routine machine learning models can lead to extremely serious consequences if mismanaged. IoT devices can lack sufficient cybersecurity defence measures. The impact of a single supplier being disrupted can affect multiple parties across the chain.” 

AI is an invaluable tool for managing supply chain risk. It can help companies stay ahead of the curve by using real-time data and delivering insights, allowing them to respond quickly to changing conditions and ensure security and reliability. 

“AI-powered predictive analytics can analyse large amounts of data to identify patterns and predict potential disruptions in the supply chain,” said Paul Turner, principal supply chain consultant at Kompozable. “By identifying potential risks ahead of time, businesses can take preventive measures to minimise the impact of the disruption. 

“AI algorithms can analyse historical demand data and market trends to provide accurate forecasts of future demand. This can help businesses optimise their supply chain processes and avoid the overstocking or under-stocking of products.”

AI-powered risk management systems can monitor the chain for potential risks, such as weather events, transportation delays, or geopolitical risks, and provide real-time alerts and recommendations to mitigate the risks. 

AI-powered quality control systems can monitor the quality of products at various stages of the chain, such as during manufacturing, transportation, and storage. By identifying quality issues early, businesses can take corrective measures to avoid disruptions.

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