Inventory Management Systems are tools that businesses use to determine the best way to manufacture and store the product. The goal is not to have too much product sitting on-hand whilst still fulfilling customer desires when it's required. According to Oracle's Netsuite, here are some of the top inventory management trends to look out for:
Organizations have begun to adopt Artifical Intelligence (AI) and Machine Learning (ML) as part of their inventory management systems. These new methodologies work in tandem with newly implemented Inventory Internet of Things (IIoT) capabilities that have become the norm in the industry.
Machine learning could also be used to detect product defects, and also packaging errors that result in customers getting only the best quality products. As inventory is constantly in flux, it also means that product levels are constanting growing or shrinking - making it challenging to get an accurate dataset - this is where AI and ML come in.
Businesses can now track and trace inventory in real-time, and this has revolutionized the industry. Cloud-based solutions allow data from organizations to be stored safely and securely, additionally this data can be accessed from anywhere, allowing decision-makers to swiftly address and tackle inventory issues.
Concentrating data in a central location simplifies adding new locations and distribution centres to fulfill customer demand. GPS location capabilities also allow businesses to track pallets as they move to their destinations. They also allow for containers or delivery vehicles to be monitored in real-time with accurate time-to-destination predictions. This data suite allows for better inventory prediction and decision-making.
Distributed inventory management
Inventory distribution that has been strategically placed across several storage facilities can result in lower operational costs and faster delivery times. By allocating product at the best locations, coupled with dispatch consistency from the warehousing team - organizations can achieve both maximum efficiency and customer satisfaction
This methodology can be used in parallel with both cloud-based solutions and AI/ML as described in the above. Organizations can use the data provided by both in order to conduct data analysis to see where and when products should be allocated to certain locations.