The COVID-19 pandemic has become a proving ground for innovations across multiple industries. This is not surprising. Throughout history, crises have spawned innovation. Now the world is being invited to innovate once again amid a cataclysmic disruption to our global supply chain.

The problem we’re experiencing now may seem like a hopeless bottleneck, and the changes we need to make to fix it are going to take some time to realize value. But artificial intelligence, combined with other technologies and innovations, could bring about some long-lasting improvement across the entire supply chain, from the manufacturing floor to the retail shelf. Here are some scenarios.

Improving the Factory Floor

The news coverage of the supply chain bottleneck tends to focus on ships stuck at sea amid port closures. But supply chain managers know that improving the supply chain extends to the factory floor where raw materials are sourced and manufactured into products. AI connected to other technologies can make a big difference. For example, a data-driven forecast on the supply of raw materials can help optimize manufacturing planning decisions as well as labor planning to reduce burnout. Additionally, smart sensors on the factory floor can make production more efficient and responsive to both supply as well as demand fluctuations. Smart sensors can also warn the manufacturer when vital parts are wearing down, making it possible for the manufacturer to take proactive corrective measures before a disruption happens.

I’m most excited by the potential for businesses to combine immersive technologies such as virtual reality, mixed reality and augmented reality with AI (e.g., the marriage of deep reinforcement learning with 3-D simulation) to improve manufacturing processes. Businesses can use AI to simulate different production scenarios and optimize the factory floor in ways that are less time consuming and more cost effective. In addition, with 3-D simulation and reinforcement learning, a manufacturer can optimize the entire production process, whereas physical manufacturing experimentations may only optimize for a specific process. As the promise of metaverse takes hold, this virtual application of AI could help transform the factory floor, not just make it more efficient.

Reacting to Disruption

AI makes it possible to use data and analytics to identify and map out the inventory that is getting affected by the supply chain disruption. If a business lacks visibility of a ship transporting its materials, then it should use the crisis as an opportunity to justify prioritizing supply chain digital transformation with data, the internet of things and advanced analytics (e.g., machine learning and simulation). A business needs to know where its goods are at all times to successfully gauge what impact supply side constraints will have on its operations and ability to meet market demand expectations. This is especially true of complex supply chains that rely on many players operating globally, as we see in the automotive industry. Automotive manufacturers and retailers are struggling to trace the bottlenecks in the supply chain for semiconductors from one country to the next. This lack of transparency makes it nearly impossible for them to take steps such as identifying how to break the bottleneck or to predict when inventories might return to normal. Transparent data sharing and AI can help solve this problem.

Responding to Consumer Demand

It’s instructive to remember that there would be no supply chain crisis without consumer demand. AI can help everyone in the supply chain ecosystem get more aligned with consumer demand through digital shelf technology. The digital shelf refers loosely to a product display — both in-store and online — that is connected to a retailer’s entire operations and supply chain through real-time data. With a digital shelf, a business knows its precise inventory levels at every store at all times.

Take Amazon.com Inc.’s grocery stores. Sensors throughout Amazon Go stores provide constantly updated intelligence on digital shelves, which makes it possible for the retailer to customize inventory levels based on regional demand and also to respond to sudden surges or decreases in product demand. On a larger scale, Walmart Inc. is building this capability, too.

The concept of the digital shelf has existed for a few years, but the pandemic has made it more urgent and timely. That’s because the rapid and unpredictable changes in consumer demand and a surge in online/offline commerce emerging from the pandemic have removed any margin of error for businesses managing inventory levels. 

A digital shelf won’t solve the supply chain bottleneck, but it will help businesses more smoothly manage a crucial element of the supply chain — the last mile of delivery. 

Managing the Labor Shortage

One of the reasons the supply chain crisis has intensified is a lack of available labor, such as warehouse workers to unload products and truckers to transport them. AI can help businesses manage a tight labor supply, especially if companies get creative about how they use it to source contractor labor. Many businesses are still operating in the dark ages when they find temporary help to manage surges in capacity: they pick up the phone and call a staffing company. This is a highly inefficient approach. What if a business were to find the resources they needed by tapping into a single portal powered by data and AI? Assuming businesses and their staffing partners kept the portal up to date with information about their staffing needs and resources, AI could match resources depending on factors such as the scope of the need, proximity to available staff and resources, and timeframe. AI would not solve the problem if zero resources were available — but it would certainly help if enabled by the right platform. 

Planning for the Next Crisis

AI can help a business conduct scenario planning exercises and inform critical business decisions. The pandemic is a wake-up call for businesses to plan for the next disruption — be it another pandemic, natural disaster, civil unrest or any other disruption. AI can help companies anticipate shortages and supply issues ahead of time and then respond with resiliency strategies — for example, rerouting delivery of essential materials when a port closure occurs. This would require having the data and being able to simulate resiliency responses. AI could also help businesses along the supply chain predict if a particular disruption (such as a natural disaster upending coffee production) is transitional or longer term and simulate response scenarios based on that data.

Similar to AI-powered factory simulation, businesses can use digital twins to do scenario planning for the next disruption. As the MIT Technology Review noted, “What if there's a drought in Taiwan and the water shortage shuts down microchip manufacturing? A digital twin could predict the risk of this happening, trace the impact it would have on your supply chain, and — using reinforcement learning — suggest what actions to take to minimize the harm.”

There is no easy way out of the supply chain crisis. AI in and of itself will not provide the solution, either. I suggest that businesses first break down the supply chain crisis into smaller pain points and figure out how to solve them, as this post has done. Asking, “How can we protect our business from the next disruption?” is probably too broad a question. Instead, focus on something that is more concrete and more easily solvable, such as “How can I align my truck driving fleet more effectively with surges in demand?” Answering the question will help the business understand a clear and compelling role for AI. 

Ahmer Inam is chief AI officer at Pactera EDGE, a global digital and technology services company.

The COVID-19 pandemic has become a proving ground for innovations across multiple industries. This is not surprising. Throughout history, crises have spawned innovation. Now the world is being invited to innovate once again amid a cataclysmic disruption to our global supply chain.

The problem we’re experiencing now may seem like a hopeless bottleneck, and the changes we need to make to fix it are going to take some time to realize value. But artificial intelligence, combined with other technologies and innovations, could bring about some long-lasting improvement across the entire supply chain, from the manufacturing floor to the retail shelf. Here are some scenarios.

Improving the Factory Floor

The news coverage of the supply chain bottleneck tends to focus on ships stuck at sea amid port closures. But supply chain managers know that improving the supply chain extends to the factory floor where raw materials are sourced and manufactured into products. AI connected to other technologies can make a big difference. For example, a data-driven forecast on the supply of raw materials can help optimize manufacturing planning decisions as well as labor planning to reduce burnout. Additionally, smart sensors on the factory floor can make production more efficient and responsive to both supply as well as demand fluctuations. Smart sensors can also warn the manufacturer when vital parts are wearing down, making it possible for the manufacturer to take proactive corrective measures before a disruption happens.

I’m most excited by the potential for businesses to combine immersive technologies such as virtual reality, mixed reality and augmented reality with AI (e.g., the marriage of deep reinforcement learning with 3-D simulation) to improve manufacturing processes. Businesses can use AI to simulate different production scenarios and optimize the factory floor in ways that are less time consuming and more cost effective. In addition, with 3-D simulation and reinforcement learning, a manufacturer can optimize the entire production process, whereas physical manufacturing experimentations may only optimize for a specific process. As the promise of metaverse takes hold, this virtual application of AI could help transform the factory floor, not just make it more efficient.

Reacting to Disruption

AI makes it possible to use data and analytics to identify and map out the inventory that is getting affected by the supply chain disruption. If a business lacks visibility of a ship transporting its materials, then it should use the crisis as an opportunity to justify prioritizing supply chain digital transformation with data, the internet of things and advanced analytics (e.g., machine learning and simulation). A business needs to know where its goods are at all times to successfully gauge what impact supply side constraints will have on its operations and ability to meet market demand expectations. This is especially true of complex supply chains that rely on many players operating globally, as we see in the automotive industry. Automotive manufacturers and retailers are struggling to trace the bottlenecks in the supply chain for semiconductors from one country to the next. This lack of transparency makes it nearly impossible for them to take steps such as identifying how to break the bottleneck or to predict when inventories might return to normal. Transparent data sharing and AI can help solve this problem.

Responding to Consumer Demand

It’s instructive to remember that there would be no supply chain crisis without consumer demand. AI can help everyone in the supply chain ecosystem get more aligned with consumer demand through digital shelf technology. The digital shelf refers loosely to a product display — both in-store and online — that is connected to a retailer’s entire operations and supply chain through real-time data. With a digital shelf, a business knows its precise inventory levels at every store at all times.

Take Amazon.com Inc.’s grocery stores. Sensors throughout Amazon Go stores provide constantly updated intelligence on digital shelves, which makes it possible for the retailer to customize inventory levels based on regional demand and also to respond to sudden surges or decreases in product demand. On a larger scale, Walmart Inc. is building this capability, too.

The concept of the digital shelf has existed for a few years, but the pandemic has made it more urgent and timely. That’s because the rapid and unpredictable changes in consumer demand and a surge in online/offline commerce emerging from the pandemic have removed any margin of error for businesses managing inventory levels. 

A digital shelf won’t solve the supply chain bottleneck, but it will help businesses more smoothly manage a crucial element of the supply chain — the last mile of delivery. 

Managing the Labor Shortage

One of the reasons the supply chain crisis has intensified is a lack of available labor, such as warehouse workers to unload products and truckers to transport them. AI can help businesses manage a tight labor supply, especially if companies get creative about how they use it to source contractor labor. Many businesses are still operating in the dark ages when they find temporary help to manage surges in capacity: they pick up the phone and call a staffing company. This is a highly inefficient approach. What if a business were to find the resources they needed by tapping into a single portal powered by data and AI? Assuming businesses and their staffing partners kept the portal up to date with information about their staffing needs and resources, AI could match resources depending on factors such as the scope of the need, proximity to available staff and resources, and timeframe. AI would not solve the problem if zero resources were available — but it would certainly help if enabled by the right platform. 

Planning for the Next Crisis

AI can help a business conduct scenario planning exercises and inform critical business decisions. The pandemic is a wake-up call for businesses to plan for the next disruption — be it another pandemic, natural disaster, civil unrest or any other disruption. AI can help companies anticipate shortages and supply issues ahead of time and then respond with resiliency strategies — for example, rerouting delivery of essential materials when a port closure occurs. This would require having the data and being able to simulate resiliency responses. AI could also help businesses along the supply chain predict if a particular disruption (such as a natural disaster upending coffee production) is transitional or longer term and simulate response scenarios based on that data.

Similar to AI-powered factory simulation, businesses can use digital twins to do scenario planning for the next disruption. As the MIT Technology Review noted, “What if there's a drought in Taiwan and the water shortage shuts down microchip manufacturing? A digital twin could predict the risk of this happening, trace the impact it would have on your supply chain, and — using reinforcement learning — suggest what actions to take to minimize the harm.”

There is no easy way out of the supply chain crisis. AI in and of itself will not provide the solution, either. I suggest that businesses first break down the supply chain crisis into smaller pain points and figure out how to solve them, as this post has done. Asking, “How can we protect our business from the next disruption?” is probably too broad a question. Instead, focus on something that is more concrete and more easily solvable, such as “How can I align my truck driving fleet more effectively with surges in demand?” Answering the question will help the business understand a clear and compelling role for AI. 

Ahmer Inam is chief AI officer at Pactera EDGE, a global digital and technology services company.