- A supply chain refers to the network of businesses, individuals, and materials related to the production and delivery of goods for a company.
- Management of a supply chain is crucial to the company’s being able to function properly and maintain operations.
- Supply chain organizations expect machine automation in their processes to double between now and 2028.
- Artificial intelligence (AI) can take over much of the difficult work of supply chain management and optimization, freeing human worker time for other things, improving efficiency, and more.
- AI can be used to manage large amounts of supply chain data and to analyze it, identifying trends and making predictions about future concerns.
- AI systems are fast, efficient, and tireless, making it possible to improve efficiency in a supply chain, reduce the need for human work, improve safety, and cut costs.
- Forecasting capacity constraints and customer demand is essential for managing a supply chain, and AI can be trained to do both tasks with efficiency.
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Supply chain management is crucial for successfully running many companies. A supply chain is the complicated network that exists between a company and its various suppliers and providers. It is, essentially, all of the items and steps necessary to produce an item and deliver it to customers. One kink in the chain and a company can quickly find itself in serious trouble, not being able to complete manufacturing, distribution, or delivery needs.
For these reasons, supply chain management is a vital part of many businesses’ operations. But managing a supply chain is highly complex, difficult work. It involves coordinating countless parties and considering factors ranging from availability of product materials to labor issues to price fluctuations and much more.
Fortunately, artificial intelligence (AI) has transformed in recent years, developing into a powerful tool for a variety of business applications. Below, we’ll look closely at how AI can be used to take on—and improve—the optimization of a supply chain. Indeed, a recent survey of supply chain organizations found that this category of business expects machine automation in their processes to double between now and 2028.
One of the difficult aspects of supply chain management is overseeing and properly categorizing or logging data. Supply chains produce large amounts of data, and watching this data carefully for trends or signs of potential issues is key for supply chain optimization.
AI trains by analyzing and responding to vast pools of data. As it does, through processes known as machine or deep learning, an AI system “learns” and becomes more refined, faster, and more capable at processing this data. It is natural, then, that AI systems could be trained through the management of supply chain data, helping them to better be able to note inconsistencies, identify patterns, and spot potential problems.
Optimizing a supply chain is all about efficiency. Because of the interconnectedness of supply chains, a delay or issue in one part of the network has wide-ranging impacts on other parts of the network as well. AI boasts a tremendous efficiency advantage over humans and even other computer-based systems, allowing it to take care of any issues as quickly as possible.
While all businesses hope to create supply chains thoughtfully so as to avoid potential inconsistencies or inefficiencies, the reality is that this part of a company’s operations can be anything but smooth. An AI system can take a broader view of a supply chain to find ways to optimize it—perhaps by consolidating multiple suppliers of a certain product into one supplier, say, or by identifying faster or cheaper ways of sending materials between two parts of the network.
Capacity and Demand Forecasting
Supply chains undergo a variety of stresses related to delays, backups, the breakdown of one part of the chain, unexpected demand, and more. AI programs are useful in delivering improved forecasting tools for customer demand and for the capacity of a supply chain. This can make it possible for a business to preemptively add capacity during a busy time, say, or to scale a supply chain down during less busy periods in order to cut costs.
Depending on the type of company, accurate inventory management may be one of the most important aspects of maintaining a supply chain. It ensures that items can flow in and out of a company’s warehouse facilities smoothly while working to protect against under- or overstocking. Inventory management involves many factors, from order processing to picking, packing, and more. Together, overseeing inventory can be time-consuming, costly, and error-prone. AI’s capacity to handle large amounts of data make it very effective at managing inventory.
Reducing Costs, Boosting Safety
AI can help to enhance warehouse management by reducing inefficiencies. When warehouses are better managed, it follows that workers and materials tend to see a boost in safety. To be sure, some AI systems can even automate certain aspects of work traditionally done by humans, further increasing safety by removing humans from the picture entirely. After all, AI systems are able to work at a fast pace and without errors for a much longer period than any human team could. This makes them also helpful at reducing costs (although there are potential concerns about AI’s role in eliminating jobs).