How AI can improve Logistics and Supply Chain Management

September 14, 2018 | Sakshi Sharma

Artificial Intelligence (AI) has been around a long time and pretty much everyone knows what it is. If you don’t have a clue what it is and/or what it can do, take a look at how it relates to business and how it is changing our world to get a better understanding.

AI has made huge strides in supply chain management especially because that industry, like most, has been heavily dependent on the labor force. Now companies have shifted to making it more automated because it improves speed, accuracy, and efficiency which saves time and money.

Less than 15% of companies say they are incorporating AI algorithms into their logistics system but many are interested in it but just haven’t done it yet. This interest in AI for supply chain software and logistics companies has increased due to the need for a more automated and predictable system.

Although there are many different AI software vendors out there for supply chain management and logistics the complexities and differences from one company to another can render that software incomplete. This is when companies decide to build technology that is specifically tailored to their business needs. This makes it even more efficient than ready-made software.

All you need is the right software development company that understands your specific needs and can build something that with make logistics and the supply chain smooth and efficient. The development team should be able to define clear business used cases to drive the AI development to improve pricing and demand prediction, manage and secure the supplier inventory, transportation management, account for disruptions, and more.

Now, let’s get into the details about AI and how it can positively affect supply chain management.

2 Main categories of AI in supply chain management

There are 2 main types of AI for the supply chain management. Depending on your business 1 may work better than the other or you may need both. Either way, there are advantages to both.

1. Augmentation: Information needs to be gathered from tedious, repetitive tasks to be able to provide outputs. It needs inputs from human interaction to be able to make future predictions. A good example of this is your phone’s personal assistant. It tracks what you do on your phone and then creates inferences based on that for future use.

2. Automation: This requires less human interaction. It can basically do tasks start to finish without input from humans. The robots used in manufacturing plants is a great example as humans don’t physically do anything in the plant. The robots complete everything themselves.

6 Ways AI improves your business

Supply chain management and logistics have seen major changes over the years. These processes will continue to change-making things easier for businesses. Incorporating AI to help manage your business better can have quite a few positive outcomes such as the following:

1. Algorithms are used to analyze very complex data incredibly fast which makes forecasting more accurate.

2. Companies can quickly see what they can improve on in their physical supply chain as well as applications used with the use of Machine Learning.

3. Inventory and operations costs can be reduced by combining both machine learning and other related technologies throughout each stage of operations.

4. By connecting all the networks in the supply chain using AI the transportation costs and supplier risk factors are reduced.

5. Machine learning with the use of IoT sensors and real-time monitoring increases visibility in production, scheduling, compliance patterns, and more.

6. The accuracy of forecasting what products will be in demand and what factors may cause changes in the need for a product has become a huge factor in improving supply.

Real-World Examples

Logistics companies like AG-World are always looking to improve the efficiency of each sector whether that be operations, finance, or inventory management. Like AG-World many companies have repeat customers but also have a pretty large percentage of new one-time transactions. Machine learning has made these one-time transactions a lot simpler than they used to be.

Thomas Fallon, the CEO of Infinera talked about a serious change that was needed within the company because the profit margins tanked within the last couple of years. They have been working on implementing AI specifically focused on the supply chain side that expands through the other sectors of the company. The goal is to use machine learning to improve product delivery, make more accurate delivery date predictions using the data from production lead time variables and logistics performance. This also improves the sales team calls where they can provide more accurate delivery details keeping customer satisfaction high.

You may have heard of the company Target, one of the largest retailers. They have been working on technology that uses a stereoscopic camera to sift through the inventory to help with inventory management accuracy.

Logistics businesses have seen a huge disturbance in delivering goods for relief to victims of natural disasters as well as union/employee strikes. Take the hurricanes in Puerto Rico as an example. If these logistics businesses had the proper AI software they can deliver food, shelter, and other products that are needed much easier.

AI relies on algorithms to find patterns in supply chain and logistics to determine the best course of action to take for each individual situation. The system is constantly learning giving it the ability to make unique changes to determine how to make successful deliveries.

One thing you need to keep in mind when deciding to move forward with these types of advanced machine learning algorithms is the amount of data that will need to be collected. You will need all the data from your resellers, suppliers, distributors, and manufacturers. This is often why it takes time because it’s not easy. Each source will provide their data in a different way so matching everything up is complex.

With that said, AI and machine learning can help improve your logistics and supply chain. Even if you have already incorporated software to help, it can be improved upon. Customization is the best way to go as it will fit your company’s structure like a glove.

If you would like to discuss more about how the different AI implementation strategies can streamline your logistics business then don’t hesitate to contact us.

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