Using AI for supply chain success

Much is made of Artificial Intelligence, from its amazing capabilities to warnings of its potential for world takeover. The reality is that AI is an amazing tool that can be used in many ways, including for supply chain success. But a tool is only as good as its user, so it’s important to understand how you can use cutting-edge AI technology to maximize efficiency and create more effective supply chain management processes.

AI excels in understanding vast amounts of data and identifying non-obvious patterns that humans might overlook, even with manual effort. In the realm of supply chain management, AI, paired with advanced analytics, becomes an invaluable ally at every stage. It helps you spot potential risks and enables swift responses, transforming how decisions are made. No longer do you have to rely on educated guesses about your strategy. With AI handling the heavy lifting, your supply chain management team can focus on making the most effective decisions for your business, ultimately driving success and efficiency.

AI in supply chain

Before you run to your favorite generative AI chatbot and ask it what your supply chain strategy should be, let’s quickly run through what outputs AI can provide for your supply chain management processes. AI tools can provide forecasting models, text generation, classification models, and prescriptive models. This means that AI tools can take data from multiple sources, organize and categorize, and present you with an indication of present, emerging, and potential risks.

 Of course, using AI isn’t a guarantee against risks, but it can significantly reduce the amount of time it takes to sport a risk and act accordingly. Even if your business faces a disruption, the ability to cut delay times in half is priceless.

Using AI to understand your supply chain

It’s impossible to make effective decisions about your supply chain without understanding it fully, from its inception to endpoint. Mapping out your supply chain that includes not just your suppliers, but also your suppliers’ suppliers to the nth degree is key to detecting potential disruptions early. While the mapping process is data intensive, AI streamlines the data discovery and analysis to provide you with a comprehensive view into your supply chain.

AI can help you build out a digital twin of your company’s supply chain, helping you chart your supply chain end-to-end using information from your company’s systems, partners, and open sources. This is particularly useful in cases where one entity is referred to by multiple names and in denoting what the company supplies and their place within your supply chain. The output can then be verified by your supply chain management team, and the computer model can be updated or re-trained as necessary.

Using AI to assess supply chain risk

AI can be used for risk scoring, giving you at-a-glance insights into potential disruptions and emerging threats for your specific concerns. Once your digital twin or supply chain mapping is set up, continuously feed your AI tool with real-time data from a variety of sources to keep your supply chain risk scoring up-to-date. Billions of new data points are automatically analyzed and used to alert you to significant events that could cause delays.

Figure 1 – Everstream Analytics engine of AI and ML to generate actionable intelligence

Data sources can include publicly available information, such as news and media, that are not always readily accessible. For example, including media sources from around the world means that AI can notify your supply chain management team of an event relevant to one of your global suppliers, even if your team doesn’t speak the language. AI tools can also incorporate proprietary and industry-specific data sources, further ensuring that your team doesn’t miss any chance to get ahead of business disruptions.

Using AI to proactively respond to events

If an AI tool flags a change to the risk score or a developing situation, the supply chain risk management team can then evaluate it and respond accordingly. Using historical and current event data, AI can not only highlight potential risks, but can also predict the possible ramifications on your supply chain.

Since some risks are more volatile than others – weather, for example, can change rapidly and without much warning – AI’s predictive analysis is useful to make impact-based decisions. Acting early can help save money and time, and lessen any delays within your supply chain. For example, if your supply chain management team receives an alert that an extreme weather event may effect a key supplier, your team can take steps to engage an alternate supplier, or order extra supplies ahead of time. These kinds of AI-powered insights can be the difference between a company that succeeds in the face of supply chain disruptions and a company that flounders at the slightest disturbance. 

Next Steps

AI is the future of supply chain management. In today’s global supply chain environment, there is simply too much data to field manually. If you aren’t using AI in your supply chain management, it’s time to start looking into how to streamline your processes to improve efficiency and efficacy. Remember, human oversight is still key in using AI-powered tools. AI offers very powerful analysis and suggestions, which your supply chain experts can put into action depending on your company’s priorities and overall strategy.

To start this process, take a hard look at your current processes and identify any bottlenecks. Consider where your supply chain team is sourcing key data and your current visibility into your end-to-end supply chain and sub-tier suppliers. And, finally, review your company’s ability to respond quickly to an emerging disruptive event. Then, find the right AI tools to address your needs, such as Everstream’s Reveal, and transform your supply chain management processes.

AI can provide supply chain management teams with powerful capabilities, allowing them to manage new and existing risks without the hassle of manual data processing. AI-powered analytics and tools are increasingly common within the supply chain world. Companies that embrace the insights that AI can offer will be better prepared to flourish, even in the face of difficult or complex supply chain risks.