One of the biggest challenges and priorities for warehousing and distribution managers is achieving operational efficiency. Changes in warehouse workers, products, and processes can cause delays, mistakes, and errors that reduce the efficiency of your operations. Since efficiency is the deal breaker between your business thriving or failing, tools have been created to help managers handle these changes and reduce their rate of errors across warehousing processes. Machine learning is one of these tools, and here’s how this technology is revolutionizing warehousing and distribution in Toronto and around the world.
Receiving the Product
New products that enter your warehouse need to be stored and organized. It takes time to remove items from their original packaging, track their storage location, and carefully place them on the shelves. One of the benefits of machine learning is that it can analyze the current location of items in the warehouse, and as new shipments come in, they can match them to the correct location. This reduces the time consuming and often inefficient process that manual workers need to go through to keep the warehouse organized. Machine learning can also direct manual workers to the shortest route to get where they need to go, which saves time.
Picking an Order
Inefficient picking processes can lead to incorrect picking, which leads to unhappy customers and a sinking business. Proper inventory management and optimal picking order are paramount to running a smooth warehouse. Picking is the highest visibility task in the warehouse, and machine learning can optimize this process in numerous ways. For example, it reduces the number of steps in the picking process. As a result, there are less opportunities for error or damages.
Validation of an Order
Small items or those that are similar in appearance to others can cause problems for pickers. Machine learning helps prevent issues and mistakes in this area by analyzing order history and highlighting items that are at higher risk of error. It flags these items to notify pickers to be extra careful when handling and moving these items.
Picking Multiple Orders
Efficiently picking a single order is the minimum level of efficiency in the warehouse. However, many times workers need to combine picking movements for multiple orders. Picking multiple orders can be time consuming and inefficient if the right paths and organization are not in place. Machine learning helps by analyzing the orders in the system, and arranging the direction path, while simultaneously separating orders.
Warehouse Inventory Management
Inventory management is one of the most important aspects of the supply chain. Plenty of time is put into improving optimization techniques to make this process as smooth and organized as possible. Machine learning can improve inventory optimization, especially for businesses that have multiple warehouses. The technology can take into account independent variables that could cause errors or delays, and efficiently provide suggestions and solutions to manage stock. By diverting the bulk work to artificial intelligence, warehouse staff can focus more of their energy on product quality and customer experience.
Reducing Waste
Warehouse workers need to pay extra attention to items with expiration dates or sell-by dates. If these items are not properly handled or organized and picked on time, they can spoil and will cause waste and loss of revenue. Machine learning adds a level of intelligence to physical controls that you have set in place.
Improving Customer Satisfaction
Machine learning technology helps communicate in the warehouse, but it can also connect and interact with your customers. Using features like real-time data, machine learning can help customers by scanning inventory, searching for specific items, or notifying them of current deals. Bots can improve customer relationships while identifying low stock levels, product backorders, and provide valuable information that helps set customer expectations. By focusing more on customer satisfaction and product quality, you will ultimately improve your performance as a business.
Minimizing Stagnant Stock
Stock levels are one of the major factors affecting inventory management. Machine learning can make predictions on how much stock to carry, and can track inventory as it comes in or goes out of the warehouse. This resolves the concern of excess and idle stock that essentially stands for tied-up money that could be used for a better purpose. Current data provided by inventory tracking features in machine learning can ensure optimal business performance, better use of inventory, and satisfied customers.
How Lean Supply Solutions Can Help You
As you can see, the impact of machine learning on inventory management is profound. This technology resolves many of the issues that warehouses are facing today with growing customer demand and requirements for quality products. Artificial intelligence may not solve every problem, but it proves powerful insight that can help your warehouse team better manage their daily tasks. In addition, there is a growing need to compete against other businesses who have already begun to bring technology into their supply chain. Without the right warehousing and distribution services, your business can fall behind, and your consumers will be unsatisfied. To get the most from the amazing features of artificial intelligence, you will need a third-party logistics partner that has the right technology available to you.
Lean Supply Solutions provides effective supply chain management using automation and robust technology, and we make ourselves aware of the rising trends to help our clients succeed. We commit to being aware of our clients’ operational challenges and help them get the most out of their processes. We can offer consistent, accurate, and quality results by striving to ensure that the right products are provided to the right customers at the right time, while saving you money, and we can help you track and understand your metrics better. To learn more about our warehouse value-added services, or to ask any questions, contact us today.
