The continued disruption of supply chains suggests that the challenges of the COVID-19 era have been more than a blip in an otherwise stable period of global business. Supply chain professionals must consider that this instead marks the beginning of a new era of continuous disruption — and it’s time to take proactive action to prepare.
Technology increasingly appears to offer promising answers to complex problems in business operations, and the supply chain is no different. Logistics professionals should explore integrating cutting-edge systems, particularly those centered around artificial intelligence, to fill gaps that the human workforce can’t effectively manage. By combining human oversight and experience with the AI tools described below, leaders can better protect supply chains against current and future global challenges.
Building a Digital Twin
A digital twin is a virtual replica of the supply chain that can include assets, warehouses and materials. The advantage of a digital twin is it allows supply chain professionals to simulate the flow of materials, acting out a multitude of possible “what-if” scenarios.
For example, a digital twin could predict how a supply chain will be impacted if there is unrest in a location where warehouses are located, or if materials get lost due to extreme weather conditions. Creating potential scenarios and watching how each will impact the supply chain provides a unique vantage point to effectively judge risk and efficiency.
Companies that have successfully integrated a digital twin into their supply chain preparedness are still in the minority. It remains an emerging technology for many to explore, especially for smaller organizations that may be worried about cost. However, the upside is significant if the right dedicated professionals manage this tool.
Harnessing the Internet of Things
The internet of things (IoT) is a system of self-reliant, internet-connected objects that can collect and transfer data over a network without the need for human intervention. IoT devices help monitor supply chains by gathering data needed to alert supply chain professionals when a machine needs maintenance or replacement.
Amid a massive heat wave, for example, IoT devices can monitor the internal temperature of precious cargo such as vaccines, which are sensitive to extreme temperature changes. Using IoT to monitor and flag temperature changes streamlines the transportation process and reduces risk by ensuring vaccines will be viable once delivered to their final destination.
Smaller companies might find it difficult to implement IoT, as it requires a significant up-front investment in smart machines, and necessitates the ability to analyze swaths of data. But cloud computing makes it possible for even smaller companies to have considerable processing power without having to buy racks of in-house computer servers.
The Power of Machine Learning
Machine learning is a system that is constantly learning from data in real time, and alerting companies to potential supply chain impacts. The system can analyze copious amounts of data quickly, and recognize signals, patterns and trends in the data, allowing for supply chain adjustments as needed.
The use cases for machine learning are endless. With the right algorithms in place, it can help determine the most cost-effective way to route an important transport, factoring in wear-and-tear on vehicles and equipment, maximizing miles and fuel costs, and avoiding high-risk areas. This could mean the difference between a global shortage of a key product or swiftly and cost-effectively replenishing supply amid high demand.
Still, companies should exercise some caution when implementing machine learning. The technology allows for large volumes of data to be analyzed, but can only be fully maximized with skilled and knowledgeable workers to build the models and analyze the results. If you get it wrong, it can lead to bad decisions and even risk a brand’s reputation. But at the end of the day, the upside of machine learning is worth pursuing.
AI can be extremely helpful in the supply chain, but companies shouldn’t rely on it alone. Human expertise is still essential, as technology comes with its own set of unique challenges. By harnessing the strengths of both elements, while strategically utilizing each to offset the other’s weaknesses, supply chain effectiveness can be dramatically enhanced.
Prior to the pandemic, supply chain disruptions were rare; they’re now the new normal. As we continue through the thick of the disruption learning curve, it’s evident that the implementation of advanced technology is a critical need for many businesses.
Craig Civil is director of data science and artificial intelligence with BSI.