Effective inventory management can be an invaluable asset for any organization.
With the right management system, a business can improve inventory visibility, optimize its supply chain and navigate shortages.
A growing number of businesses are using AI to make their inventory management systems even more effective. This is how an AI algorithm can create an ultra-efficient inventory management system.
Why Inventory Management Has Become So Important
Right now, most businesses are navigating multiple major supply chain crises — like port congestion and a shortage of truck drivers in the U.S. Experts predict that many of these crises are likely to remain a problem well into the future.
At the same time, as businesses become more efficient, consumer expectations are rising. Customers have come to expect shorter lead times and faster delivery for all orders
Managing inventory, as a result, can be challenging. Businesses have to both contend with an unpredictable supply chain and heightened consumer expectations.
Accuracy in inventory management has become crucial, and predictive tools capable of effectively forecasting market conditions are necessary if businesses want to plan for shortages, delays and other challenges.
Using AI to Build a Better Inventory Management System
AI can improve supply chain management in a few distinct ways.
Businesses have access to vast amounts of supply chain and inventory information, but analyzing this information can be challenging due to its volume.
Artificial intelligence is a powerful tool for sifting through large amounts of data and uncovering insights that other data analysis methods fail to capture. With an AI inventory management system, businesses can optimize inventory management and take full advantage of new sources of inventory data.
Fulfillment Forecasting and Stock Management
Often, one of the biggest inventory management challenges that a business faces is accurate fulfillment forecasting. Predicting demand can be particularly challenging, especially when market forces like inflation or unemployment cause consumer confidence to fluctuate.
AI-powered data science can be an essential tool for businesses that need better fulfillment forecasting. With AI, businesses can analyze both their own fulfillment processes and customer behavior data. ‘The analysis capabilities of AI can improve long-term decision-making by more effectively predicting how customer behavior and demand patterns will shift over the course of months and years.
Some AI tools are capable of analyzing this data in real-time, as it is collected, allowing businesses that employ smart manufacturing technology, for example, to adjust manufacturing processes continuously based on changing customer demand.
Similar tools can also help businesses streamline stock management. Using an AI tool, they can estimate in real-time the amount of stock they need on hand to meet changing levels of demand.
AI in Warehouse Management and Storage Design
Efficient warehouse management is often a serious challenge. However, as storage costs become more expensive, managing warehouses efficiently has become much more important.
A single warehouse may use a variety of storage systems, including conventional static shelving, mezzanines, pallet racks and carton flow racks.
In some cases, a warehouse may use multiple types of the same system for maximum efficiency. For example, one warehouse may use mixed vertical and horizontal carousel systems that offer a combination of efficient use of space and accessibility for site pickers.
Optimizing a complex storage system like this can be a challenge — even if a business has good data on warehouse operations, like information from asset trackers that allow managers to visualize how goods are flowing through the warehouse.
With AI, warehouse managers can extract better insights into warehouse operations, potentially helping them identify process bottlenecks or layout decisions that may be holding the facility back. In other cases, AI may be used to directly automate certain tasks, like worker scheduling and product slotting.
Some businesses also use smart manufacturing technology to improve the predictive maintenance of important factory equipment, including conveyor belts and storage systems.
By monitoring the performance and health of this equipment via internet-connected devices, technicians can know immediately when a machine begins to fail or needs emergency maintenance.
While not common yet, there are also emerging AI warehouse layout tools that businesses can use to reinvent entire facilities for maximum use of space or a more efficient flow of traffic.
These AI design tools can use layout data from existing warehouses to suggest potential layouts for new warehouses, as well as recommendations for the storage technology, material handling system, storage allocation strategy and picking policies of the new facility.
AI-powered layout reviews can also help a business make their existing layouts more optimal. For example, an algorithm could detect floor patterns or storage layouts that may cause bottlenecks and inefficient worker movement, then recommend alternative layouts that will streamline site workflows.
Data-driven layout design strategies can help create much more efficient warehouses that better meet or anticipate the overall needs of a business. For companies that are expanding their storage capabilities, these tools can be invaluable.
AI for Estimating Delivery Times
Businesses can also use AI to more accurately estimate delivery times for customers.
Predicting delivery time can be challenging — a business will need to use information like the quantity and location of available-to-promise inventory, shipping methods available and distance to the customer from a warehouse to determine how long it will take to fulfill an order.
Businesses may also need to balance cost against delivery timing to effectively deliver goods to customers while keeping fulfillment operations economical.
Failing to predict delivery times can make it harder to effectively schedule deliveries and damage a business’s relationship with its customers.
With AI, a business can more effectively analyze available information on stock availability and shipping times. Better analysis can help them provide more accurate estimated delivery times to customers. Companies like Amazon have already developed AI delivery time prediction solutions for customers in the logistics industry.
According to Amazon, these solutions have helped AWS customers improve the accuracy of their delivery predictions by 74% and reduce call center volumes by 40%, as fewer customers were calling support to ask about the location of their orders.
Using AI to Optimize Inventory Management
To manage a changing market and ongoing supply chain disruptions, effective inventory management will be necessary.
With artificial intelligence, businesses can more effectively manage their inventory and fulfillment operations. AI can leverage both historical and real-time data to transform processes like stock management, warehouse management and product delivery.
In practice, businesses like Amazon are already using AI-driven inventory management to streamline operations and improve customer satisfaction.
About the author
Emily Newton, Editor-in-Chief, Revolutionized Magazine
Emily Newton is the Editor-in-Chief of Revolutionized Magazine. She has over four years experience covering stories about warehousing, logistics and distribution
