How AI and Automation are Connected to the Supply Chain

With supply chain disruptions as a constant issue in today’s e-commerce landscape, businesses are doing what they can to mitigate problems down the road. New technologies built to overcome supply chain challenges are one way that organizations are ensuring that they always have their best foot forward when navigating these issues. Two key words come into play when we think of cutting-edge supply chain solutions: Artificial Intelligence and automation. Incorporating AI and automation are proven to help curb operational inefficiencies and build more resilient businesses; organizations that fail to incorporate them risk eroding their bottom line. But how, exactly, does implementing AI and automation help with supply chain woes?

Manufacturing 

91% of employees say that automation has helped with their work-life balance, which is a strong argument for implementing automated processes. Moreover, according to a survey done by McKinsey, 53% of manufacturing leaders cited increased bottom lines directly from incorporating AI  into their organizations. When automation and visual algorithms (powered by AI) come together, this sort of software can help detect product issues in a factory line.

Regarding production timelines, AI-backed technology can help with decision-making and prediction. If there will be manufacturing bottlenecks down the road or any other unforeseen circumstances that could risk production, AI, combined with automated workflows, can let supply chain partners know ahead of time. This sort of knowledge allows executives to have more seamless operational management, while having the foresight to opt into alternative production plans when necessary, without losing time or getting behind schedule. 

Inventory and Order Management

AI-driven software is key to improving inventory management. An AI-backed system has the ability to interpret large amounts of data in real time, providing forecasting that can help determine inventory levels over a specified period of time. This ability, in turn, can help brands and retailers never overstock or understock their products. Predictive tools can also help illuminate shopping habits and demand by season.

Automated processes can also increase efficiency. By automating specific operations in order management, companies can curb the fallacy of human error. If an organization doesn’t adopt automation into these operations, they risk orders getting processed incorrectly, leading to unhappy customers. Another way that automation helps with order and inventory management is by providing real-time reports. This type of real-time reporting, allows companies to track customer trends and product performance.

Warehouse Management

Warehouses that rely on manual processes are destined to fail in this age of cutting-edge warehouse management technology. An automated, AI-backed system can optimize efficiency and increase order accuracy while decreasing warehouse operation costs. This software can automate orders with shopping carts and integrations while speeding up warehouse processes. By utilizing AI automation, warehouses can curb the mistakes that inevitably occur with handling, packaging, and sorting. Robotics, for example, can pick and pack various loads within a warehouse, take on repetitive tasks with pre-defined instructions without the risk of exhaustion, and operate with the same speed and accuracy each time they execute a task. Robotics can also help with stock control because they automatically keep track of and update inventory information, in real time. 

Another way a robotics-backed warehouse can improve overall warehouse operations is by enhancing safety measures. When warehouse workers have to transport hazardous materials or get products from hard-to-reach locations, this can create precarious, unsafe conditions. Robots, however, can be programmed to access difficult locations, precisely handle hazardous materials, and be collision-proof, creating a safer environment for both warehouse employees and the products surrounding them. 

Delivery

AI and automation can also be helpful in last-mile delivery. A Transportation Management System, or TMS, is a technology that manages all elements of an organization’s transportation processes. These elements include loading, routing, and tracking. Like an OMS, a TMS can be integrated with a WMS. If a 3PL does not invest in a TMS, then they risk supply chain inefficiencies that culminate in longer delivery times, lack of visibility, and a general distrust among partners, such as customers and shippers. An AI-automated TMS supplies transparency to 3PL partners, including real-time updates regarding the location of goods and even geo-fencing, which provides a virtual fence around a certain location, notifying you when a driver has crossed the ‘“border.” A TMS can also optimize routes. Let’s say you’re working with a distributor who is shipping items to separate stores; a TMS can optimize the route a driver needs to take to make all their deliveries in a timely manner that correlates with the stores’ hours. 

Moreover, a TMS can help with loads. With automation features, you can set up your system to accept loads that meet specific guidelines, which omits any questions about what loads are accepted and allows you more flexibility to oversee other parts of your business. Likewise, a TMS allows for load consolidation, coordinating shipments based on dimensions and size. This function allows 3PLs to optimize space and helps 3PL customers cut costs since their items are sharing rides with same-sized parcels. Similarly, a TMS can allow 3PLs to provide capacity via backhauls. The software can produce the backhaul using the freight carrier nearest to the backhaul location and allocate an order to that driver. The system can also recognize whether the driver has enough time to make the delivery. 

In this new age of supply chain management, AI and automation are key for supply chain leaders to create better processes, stay agile, and navigate disruptions. Those who don’t invest in AI-backed, automated software risk falling behind in a competitive landscape, while also, unfortunately, losing potential customers due to relying on error-ridden manual processes.  According to a study by McKinsey, implementing AI-enabled supply-chain management improves logistics costs by 15%, inventory levels by 35%, and service levels by 65%. The time is now for all supply chain partners to pivot to AI and automation.