Could AI be the solution to companies’ supply chain conundrum

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A major theme of the Global Risks Report 2024, published by the World Economic Forum in collaboration with Marsh McLennan, is the need for businesses to get used to a more unstable and volatile world. Nowhere is that more evident than in their supply chains; the lifeblood that allows businesses and our economies to function, and which have been stretched to breaking point by COVID-19, war, and global disruption caused by extreme weather, blockage of the Suez canal, piracy, and terror attacks.

The global economy has never been more interconnected, with companies sourcing their materials and parts from all corners of the world. As such, it’s important for companies to get to grips with their supply chain risks.

Up until now it’s been difficult to quantify or manage these exposures, because organisations may generally only know their first-tier suppliers, essentially those companies who invoice them for their work and from whom they are in more regular contact. Many will have little idea of who supplies their suppliers — and who supplies their supplier’s suppliers, and so on — or the threats those suppliers face in the locations they operate and the logistics routes they use. Often, management will discover its company’s vulnerability only when something happens that threatens to disrupt its own operations, or even its very existence.

New dawn in managing supply chain risks

Traditional approaches to mapping supply chains and quantifying risk have been highly labour intensive, and often reliant on tier-1 suppliers being willing to provide data on who supplies them. It seems we're on the verge of a new era, in which we will see a rapid acceleration in our ability to map supply chains and quantify risk. Advances in data science now allow us to analyse vast quantities of trade data to build a rapid assessment of an organisation’s supply chain. Not only will these insights enable companies to manage the longer-term volatility highlighted in the Global Risks Report 2024, but will also help companies to deal with the growing critical risk of misinformation that businesses now face.

These rapid advances in technology, including AI, have enabled companies to produce detailed maps of the precise origins of their materials and components. We’ve been working with clients to help them piece together the many links in their supply chain, which have previously been completely invisible to them. And with this mapping complete, organisations have then been able to quantify their risk exposures from climate change, geopolitical risks and other threats and move towards being more proactive in responding to risks before they materialise as a disruption.

The processing power of today’s data analysis systems is impressive. An indication of that is that a couple of years back the supply-chain mapping work that took one major global manufacturer six years to complete, with a large team working full time to gather and collate the information, can now be completed in around 72 hours.

We can now use AI to trawl through billions of shipping, logistics, and customs records to discover who supplies a client’s suppliers and with what, then use geospatial intelligence and remote sensing to verify their locations. Then, by overlaying a global risks map with insurance grade analytics, we can help a company quantify what the precise risk is to each of its suppliers’ locations, if it’s vulnerable to hurricanes, typhoons or floods, a militia attack or a riot or strike.

Measuring and managing supply chain risk

The ability to gain visibility enables accurate measurement, and with accurate measurement comes the capability to efficiently manage. The detailed picture that companies can now draw of their suppliers means that the related exposures should be easier to insure. With good quality, reliable data we should see an increase in the ability of insurers to accurately quantify risk and price their exposure. Thanks to AI, this information is available now, which is very exciting.

To drive sustainable growth, UK organisations will need a pragmatic approach to managing supply chain risk in 2024 and beyond. Visit our key trends in a converging risk landscape page for more information on how to stay ahead of the risk curve.

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Article

Could AI be the solution to companies’ supply chain conundrum?

New dawn in managing supply chain risks

Measuring and managing supply chain risk

How economic factors impact trade credit risks and opportunities

The trade credit claims landscape

Optimising your working capital

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Could AI be the solution to companies’ supply chain conundrum?

New dawn in managing supply chain risks

Measuring and managing supply chain risk

How economic factors impact trade credit risks and opportunities

The trade credit claims landscape

Optimising your working capital

Managing business interruption risks amidst uncertainty