According to research conducted by Inbound Logistics in 2019, more than half of the G2000 manufacturing companies stated they will rely on Artificial Intelligence (AI) for their supply chain management initiatives before 2024. And when you think about it, it makes sense.

After all, AI has been transforming supply chains by enabling machines to learn, solve problems, and make decisions that benefit department leads and business owners. But how do we know that transformation is happening? A clear sign that the change is taking place is how we are adding new terms like AI or Internet of things (IoT) to our lexicon. 

AI stopped being that one concept that despite being around for many decades, at least since the 1950s, we only associated it with science fiction themes where machines generally become a threat to humankind. 

However, to understand the impact of AI on supply chains, we must first understand how it ties into the elements that facilitate its adoption. These elements are the agents that make the supply chain possible, the cloud and IoT, and the most important of all, Big Data. 

Why is Big Data so Valuable to Artificial Intelligence?

If your immediate thought is “knowledge is power,” then you are on the right track. Data plays a fundamental role in any learning and decision process performed by AI. 

In the words of Instructor Brandon’s Technical Architect and Dynamics 365 SCM instructor, Brandon Ahmad, “the role of AI in supply chain management systems is analyzing business data and converting it into knowledge. The AI then uses the latter to make correct data-driven decisions that improve business operations long-term.”

In the past, companies collected data stemming from their operations, but using it correctly proved very difficult. Nowadays, we have access to Enterprise Resource Planning (ERP) solutions which serve as smart data repositories that integrate internal and external business operations. 

Unfortunately, even though ERP solutions are available, the BCI recently reported that the majority of companies (69 percent) do not have complete visibility of their supply chains. That means that most of their information is not stored in ERP databases, but in physical reports or spreadsheets that are difficult to digest and act upon. 

As a result, these reports become more of a tracking mechanism to understand what has happened in the past as opposed to a tool that companies can use to learn and build a better future. In other words, these companies are failing to make “intelligent” use of the information. 

How Are AI-driven Supply Management Systems Different from What We Have Now?

Currently, most of the systems available were designed to support human decision-making. When we start relying more on AI, the management systems themselves will make the decisions and control the operations by using predictive, resilient, and self-sufficient networks. 

After all, one of the best capabilities of AI is recognizing patterns in the three Vs of Big Data (volume, velocity, and variety), as well as finding correlations between them that are difficult to spot by the human eye. 

For instance, a supply chain market analysis conducted by Logility in 2018 showed that 19 percent of companies leverage machine learning to boost forecast accuracy. That proves that predictive analytics are essential to combat the uncertainty posed by most markets.  

Nevertheless, making use of these fantastic forecasting capabilities is borderline impossible if the data is behind restricted access or in an isolated device. For that reason, many companies have migrated to the cloud to facilitate the access and exchange of information between company team members and business partners. 

An Example of a Working AI-driven Supply Chain

Up until now, we have given you a brief overview of the role AI can play in the supply chain, but what are the tangible benefits, and how does it work?

You see, global supply chains are becoming more complex as time passes. They involve an ever-increasing number of businesses that must coordinate their operations to deliver goods and services to consumers. Not only that, but it also must be done promptly to ensure they stay ahead of their competition.

Taking that into consideration, there is simply no way a single member of the supply chain is capable of optimizing the flows of information, materials, and money that are generated every day.

That is where AI comes in. Its main application in the supply chain lies in its ability to carry out real-time planning and execution of different processes based on the current need of each member in the supply chain ecosystem. 

A common real-life application of AI in the supply chain is the one we see in retail when a self-service store monitors the sales of a product. These systems spot real-time changes in consumer behavior. According to the data provided by the purchases (or lack of), the AI will automatically report what needs to be replenished and reflect it on the relevant parts of the chain. 

Smart networks also allow the members of the supply chain to derive real-time actionable information from point of sale systems (POS) or the data generated through the IoT. With that, they are not only capable of planning, but also executing and acting with a set of a very specific set of goals and purposes in mind. 

But it does not stop there. After every decision is made, the AI analyzes the results of these decisions to determine ways in which the results can be improved. The more time passes, the more information will be stored in the intelligent supply management system, allowing it to learn how to best modify the assumptions and models used by companies to improve performance. 

How to Get the Best Out of AI in Your Supply Chain

To ensure we get the best out of AI in our supply chain, it is necessary to guarantee the following conditions:

  1. First, we must make sure the supply chain management system we use has access to the data generated by every process in the supply chain. The information has to be accessible without the need for manual intervention to ensure reliable decision-making.Moreover, supply chain partners must also make their information available for upstream and downstream analysis. The reason is that every decision will be made to optimize every operation of the chain, requiring the system to have full visibility.
  1. Second, supply chain partners must be aware that the system’s primary focus will be maximizing, while saving on costs, the quality of the service received by the end customer. In other words, the goal will be maximizing profit while ensuring customers are satisfied with the service or product. 
  2. Third, the members of the supply chain must be open to the idea of seeing constant changes in their planning and execution. If you are thinking you will be at the mercy of a machine, though, do not fret. Each supply chain member will be aware of the costs associated with each modification, as well as the potential benefits that come with them. 
  3. Fourth, supply chain members must acknowledge that to learn, systems have to analyze problems and processes multiple times. That way, they can adjust the policies and criteria used in their decision-making. In other words, there might be mistakes along the way. 
  4. Fifth, the companies must ensure their management systems are capable of processing huge volumes of data associated with the production, distribution, and sale of products and services in the supply chain. 
  5. Last but not least, the companies must monitor the system during the learning process to address potential problems found in the algorithms.  

Do not forget, however, that on top of these technological requirements, the organization must have in-house talent capable of selecting the appropriate supply management system, generate algorithms, monitor decisions, manage relationships between companies, and design supply chain strategies.

Thank you for reading our blog post. We hope you now have a better understanding of the capabilities of AI and its role in supply chain management. If you have any questions, feel free to leave them in the comment section below. 

By Eddy

Eddy is the editorial columnist in Business Fundas, and oversees partner relationships. He posts articles of partners on various topics related to strategy, marketing, supply chain, technology management, social media, e-business, finance, economics and operations management. The articles posted are copyrighted under a Creative Commons unported license 4.0. To contact him, please direct your emails to editor.webposts@gmail.com.