The globalization of supply chains over recent years has made the industry more complex than ever before. Our digitally connected world has allowed for more competition, making it absolutely necessary to maximize productivity and reduce uncertainties of all kinds. What’s more, consumers and businesses alike have greater expectations for the speed and efficiency of operations.
Clearly, an innovative method of addressing these concerns was necessary. Enter artificial intelligence and machine learning. By implementing AI and machine learning, companies have been able to optimize their operations. This meant that tasks could be completed faster, with fewer errors, and required less human oversight. Furthermore, operations are subject to continuous improvement when AI is implemented properly.
Benefits of AI Implementation
- Accurate Inventory Management
Accurate inventory management is one of the most challenging aspects of the supply chain, especially for larger organizations. The volume of products to be accounted for and the numerous variables associated with them can be difficult to track. Processing, picking, and packing orders can be a challenge in and of itself, but when this operation is coupled with other responsibilities such as replacing inventory and predicting the demand for products it can become easy for a person to make mistakes. Computers are much better equipped to handle massive data sets. AI-driven tools have the capability to track thousands of values simultaneously with a very low rate of error.
On top of this, AI is capable of combining past data with real-time data in order to create predictive and prescriptive analytics. Predictive analytics can be used to develop a set of likely outcomes. For example, software could predict whether or not a shipment will arrive on time with upwards of 90% accuracy. Prescriptive analytics can be thought of as the next step to predictive analytics. If the software predicts that a supplier will be late to make a delivery, then it can use external data to find alternatives that match your timeline and quality standards.
- Warehouse Efficiency
An efficient warehouse is a crucial aspect of the supply chain. If warehouses aren’t working smoothly, then your company will likely fall behind on orders which will lead to customer dissatisfaction and an overall loss in potential revenue. Automation such as warehouse shipping software can assist in critical warehouse operations. This includes timely retrieval of items and ensuring a smooth journey to the customer. AI-driven automation can also reduce the need for and cost of warehouse staff.
- Enhanced Safety
By making the warehouse a more efficient and better-planned workplace, AI can indirectly improve the safety of workers and materials. AI also has the capability to analyze workplace safety data and use it to inform managers about possible risks to safety. This helps warehouse operators react more quickly to possible hazards and ensure a workplace that is compliant with safety standards.
- Reduced Operations Costs
An overall reduction of operations costs is one of the primary benefits of AI implementation in any supply chain. Compared to people, artificial intelligence can work longer hours with fewer errors and at a quicker pace. This will streamline any operation it is effectively implemented into and reduce its cost while also boosting its productivity.
- On-Time Delivery of Goods
Artificial intelligence can lessen your company’s reliance on manual efforts in the shipping process which will make it faster, smarter, and safer. By streamlining the shipping process your business will see a drop in late deliveries, which will result in increased revenue by cutting the expenses and lost opportunities that late deliveries create.
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Challenges Associated with Implementing AI
- System Complexities
AI-driven systems are incredibly complicated and require expert knowledge to implement and maintain. You’ll save money on some labor such as warehouse workers, but chances are you’ll have to hire someone with machine learning experience to make sure that the system is running smoothly. On top of that, the hardware required to run these systems can be costly and take up a great deal of space.
- Initial Costs
The expenses associated with setting up a robust, AI-driven system can be incredibly high. And these expenses will only increase the larger your organization grows. This can make AI implementation daunting for many business operators who aren’t aware of the several benefits associated with artificial intelligence.
Best Practices to Implement
There are dozens of specific ways that AI can be effectively implemented into a supply chain. The most effective implementations will be ones where the AI can replace or reduce human labor or in areas where large amounts of data and variables must be considered.
- Demand Forecasting
As previously mentioned, artificial intelligence is incredible at understanding and manipulating massive amounts of data and statistics. One of the major ways this can benefit supply chain operators is through demand forecasting. This is a process where an AI-driven tool finds patterns in past and real-time data in order to make predictions of what products will have the highest demand. Meaning warehouse managers can spend less time figuring out which products to keep in stock and instead order inventory based on a computer’s recommendation.
- Optimizing Routing and Delivery Efficiency
AI systems can also be fed external data to optimize other operations within the supply chain. An example of this is using artificial intelligence to analyze roadmaps and decide upon the most optimized route for a given delivery. For example, one cargo van carrying 25 packages to different locations could have thousands of possible routes to take, but only one will be the most efficient. What’s more, artificial intelligence is capable of making these optimizations far faster than any person could. A smooth delivery process is paramount in today’s world where consumers expect quick and simple access to the goods they purchase online.
- Improving the Longevity of Equipment
Another more niche example of how AI could improve supply chain operations is through equipment longevity analysis. For example, artificial intelligence could be used to analyze a log of past transit vehicle malfunctions and maintenance requests to make predictions on the average lifespan of a shipping vehicle and possibly even recommend maintenance before an issue occurs. This would eliminate impediments that would otherwise be completely unpredictable.
