By Valentyn Kropov, SoftServe
AI/ML to speed inventory management.
Counting inventory is an inordinately tedious task, often requiring retailers to completely close during the process. It is, however, a vital part of retail and warehouse management.
Taking a physical count of inventory ensures products are in their designated place, in the correct quantity. Comparing on-shelf actuals with records in the warehouse management system (WMS) or inventory management system (IMS) enables leaders to maintain inventory accuracy, spot the causes of shrinkage early, and ensure the right stock is available for the overall supply chain.
As customers demand more products with greater options delivered faster, warehouses will continue to grow in size and delivery speed. There is no time for warehouse employees to stop and ensure correct inventory tallies, especially for difficult to count or odd-sized items. Instead, warehouse managers must implement advanced technology, such as artificial intelligence (AI) and machine learning (ML) to save time and to ensure inventory accuracy.
In previous years, physical inventory counts were completed with a pen and paper. Staff would use a physical inventory sheet to tally up products and then reconcile the data in their system. Even as more advanced WMS systems are made available, the task still requires manual calculation and data entry which is highly inefficient and often requires double entry.
And human error is inevitable. Studies have found manual warehouse totals are only accurate 63 percent of the time, due to human errors on product estimations and shrinkage. For deeper investigation on inventory loss, read our state of the warehouse whitepaper.
AI/ML Is The Solution To The Human Error Problem
The purpose of a warehouse management system (WMS) is to count and track items that move into and out of the warehouse. Even when shipments are inspected upon delivery, information can easily be miscommunicated or inaccurately recorded. If the total was wrong from the beginning, it will be incorrect when a warehouse calculation is completed.
Some items have difficult sizes or are too small or numerous to count. Trying to count the contents of a large box of small screws, for example, would take too much valuable time for workers paid by the hour. Employees would need to make approximate guesses if the information provided by the WMS is correct.
With AI/ML, reporting on product levels becomes straightforward, fast, and accurate. Using a smart scale with built-in AI capabilities, a box of screws would simply be weighed, and the precise contents automatically recorded. This goes beyond the standard idea of merely calculating the net weight of items. Data on inventory can be processed more efficiently and useful information is made available immediately to managers and leaders.
AI/ML can make quick work of counting and recording more exact amounts of assets on hand. For unusually sized or weighted items, such as spools of fabric, this technology can utilize a smart camera and the current WMS to remove human error. A worker snaps a picture image of the spool and algorithms are completed by the intelligent system to calculate the width of the fabric on the spool, which creates a much more accurate and reliable record of the remaining fabric.
Correct Counts, Available On Demand
Although weighing equipment has been around for numerous years, the incorporation of AI/ML with camera functions allows inventory data to be available via cell phones, tablets, and computers immediately. Instead of requiring the scale to be reset every time a new item is weighed, the technology can download the sample’s information (such as product ID, container weight, variances, or other pertinent details about the item). Machine learning grows the network of information on products and samples, calculating the total instantly.
Using a real-time inventory system with AI/ML capabilities, warehouse employees and managers can see inventory and changes immediately, with recording logs saved across the network. Manual counting becomes unnecessary as management has a real-time log to asses actual inventory data and can react quickly to stocking aberrations.
With recent advancements in AI/ML retailers can take control of their inventory like never before. When coupled with other technologies such as Big Data and blockchain for cybersecurity, the warehouse is poised to leap into the future and drive business forward.
About The Author
Valentyn Kropov is VP, Client Success at SoftServe.