How AI and Blockchain Could Fix Broken Supply Chains


Posted on January 9, 2022 at 2:00 p.m. by

Andrea Minca

When the coronavirus crisis erupted in 2020, it became evident that the medical emergency was accompanied by severe shortages, especially in some medical devices.

The pattern was first observed for ventilators: demand increased everywhere and the supply chain was disrupted. The production of the devices spanned several countries, with each part depending on other parts made in different locations. The longer the chain and the more complex the dependency, the greater the exposure of one point to the disturbance of another and to compulsory stops.

Now, two years after Covid’s first hit, this pattern has affected almost every sector of the global economy. “Supply chain issues” have become so prevalent that they’re now a common joke, affecting everything from furniture to groceries. But why has Covid had such a severe effect on the way we receive products and goods?

Over the past few decades, supply chains have become leaner and longer as they have become more profitable: more and more steps have been added in the manufacture and transportation of a given product in the name speed and cost. This means that there are more and more places where something can go wrong between your online order and it arriving at your doorstep.

Today, downstream suppliers – such as those who provide vehicle control systems to your automaker – depend on upstream suppliers – such as chipmakers – to deliver on time so they can in turn deliver. deliver to you on time.

With long chains, the risks are now shared between several entities around the world.

Using AI and blockchain to protect commerce

Supply chain issues have a financial ripple effect known as trade credit contagion. This is where companies delay payments to suppliers because their customers are delaying their payments. The cash on delivery model can result in canceled or delayed shipments which in turn can lead to bankruptcy.

Although a high proportion of trade credit risk remains uninsured today, a post-pandemic world could see insurance and reinsurance companies close this protection gap.

Researchers are currently working to develop methodologies to identify vulnerabilities in global supply chains and to understand their risks of trade credit contagion. The goal is to make these systems more robust overall.

How can we design ways to design insurance and reinsurance contracts to effectively share risk and mitigate vulnerabilities? How can reliable trade credit reduce delays in supply chains and replace the familiar situation we face today of paying for something in advance with an unknown delivery date?

Artificial intelligence and complex network theory are useful in identifying structures that could present systemic risk. They help us ask ourselves: What types of connections are likely to lead to delays and trade credit contagion, and which are the most robust?

Using these tools, we can create large-scale simulators of global supply chains that respond to a wide variety of shocks, and then use machine learning techniques to detect problematic parts of the chain. This knowledge can then be used in market designs that strengthen the system before another pandemic or disaster occurs.

Other new technologies such as blockchain promise to use high-quality data to analyze supply chain dependencies. Blockchain technology uses real-time data and transparent verification performed by multiple parties. In combination with other features, such as smart contracts, this could lead to rapid resolution of disputes throughout the supply chain.

My research involves using blockchain to streamline record keeping and payments. This problem is difficult because the adoption of blockchain depends on both the specifics of the technology and the cost.

The problem of technology adoption in the presence of positive externalities (whereby firms adopting the technology in turn improve the operations of external parties) is a long-standing issue in economics, but these externalities are now systemic in nature: the effects are widespread. propagate along chains. The cost of technology depends on the number of companies that adopt it, and each faces company-specific costs based on its position in the supply chain, risk tolerance, and costs for insure these risks.

Real-time record keeping, transaction traceability, and blockchain immutability can all help supply chains become more efficient. This is all the more true when one considers the entire length of the chain, where transactions must be verified by several parties: supply chain actors, insurance and reinsurance companies.

The future of supply chains

Trade credit insurance is expected to expand after the pandemic. It can rely on public-private partnerships – the pandemic has shown that governments become important actors when they impose closures in certain areas.

These funds can be used to compensate for late payments, reduce losses and restart critical production if necessary. But not all links in a chain can be insured, and a big challenge is to identify the most important milestones in different shock scenarios.

Supply chains can also be rewired – large-scale algorithms can identify which suppliers need to be replaced and which ones to emerge.

In a few years, supply chains may look different, as the overall focus shifts from minimizing costs, as was the case before the pandemic, to minimizing delays and trade credit risks. The end consumer will cause the need to rewire the network, as demand changes. Ultimately, the flexibility of the customer determines the resilience of the supply chain.

Andreea Minca is Associate Professor in the School of Operations Research and Information Engineering at Cornell University. She graduated from Sorbonne University (Doctorate in Applied Mathematics) and from Ecole Polytechnique (Diploma from Ecole Polytechnique).

This article is courtesy of The Conversation and can be found in its original form here.

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The opinions expressed here are those of the author and not necessarily those of The Maritime Executive.


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