Smart stock management in markets and supermarkets

Food retailers are facing unprecedented pressures in an increasingly competitive sector. Ensuring that adequate quantities of high-quality products are always available requires the allocation of staff to carry out periodic stock checks in-store. In addition, it is necessary to have a team to reprice perishable products that are reaching the end of their shelf life, encouraging customers to buy them.

In response to these challenges, ASUS IoT and Macnica have developed advanced solutions that enable supermarket chains to modernize their stores by automating previously time-consuming procedures, resulting in:

• Greater operational efficiency
  
• Faster response to market demands
• Reduced waste
• Increased profitability
• More informed decision-making

Effective stock replenishment in supermarkets is crucial to financial success. Perishable items such as fruit, vegetables, sweets and confectionery require precise control to ensure adequate availability.

If replenishment is too slow, it can result in product shortages and frustration for customers, as well as lost sales opportunities. On the other hand, replenishing too quickly can lead to overstocking, exposing low-quality products and discouraging purchases, which can damage the supermarket's brand reputation and reduce revenues or customer loyalty.

Regularly monitoring stock levels of various items requires a significant allocation of human resources, increasing operating costs and diverting focus from other important tasks. In addition, busy employees may not immediately notice a product shortage, resulting in late replenishment.

Furthermore, manual approaches are subject to judgments that may not be accurate. To avoid these problems, retailers are looking for a data-driven approach to decision-making, and this is where our solution will make all the difference in this segment.

Operating 24 hours a day, 7 days a week, this intelligent solution for markets and supermarkets offers continuous visibility to track and respond to fluctuations in stock levels of different types of products, ensuring that they are always kept at optimum levels.

Through the use of data acquisition and AI accelerator hardware, combined with the ASUS IoT store manager's AI analysis, we were able to eliminate guesswork in merchandise replenishment and base this activity on hard data.

By relying on computer vision instead of level sensors in the containers, we are able to obtain more accurate data on the quantity of items. Based on parameters such as size and average daily sales, it is possible to set a fill limit for each container of products without a barcode.

For example, the limit for watermelons can be significantly different from that for bananas, considering that watermelons are larger and sold less frequently, but fewer units fill a container. Store managers can easily adjust these limits as needed.

Regular image capture makes it possible to determine product levels almost in real time, thanks to the refined image recognition and deep learning AI algorithms developed by ASUS IoT and integrated by Macnica.

Through the app associated with the system, store employees receive alerts on their smartphones or PDAs when certain items need to be replenished. For example, if the level of fruit in a container falls below the predefined threshold, an alert will be triggered in the app. A team member can then react by refilling the container with more of that fruit. In addition, the interval between product replenishments can be monitored via a counter displayed on the user interface.

The AI-based ASUS Smart Replenishment solution is fit for the future. As well as being simple to install, once in operation it requires only minimal maintenance by the system integrator.

In addition to modernizing the replenishment process, the ability to make rapid changes to product prices is another important dimension to consider. In this respect, ASUS IoT algorithms once again take advantage of the data acquired to make operations more efficient and minimize human resource costs.

For example, if it is determined that the products in certain containers need to be sold by the end of the day to avoid deterioration in quality, their electronic price tags can be dynamically updated to reflect the discounts applied. This also allows the description of a container to be changed if it is filled with a different type of product.

Macnica is also responsible for designing the automation system that identifies the price tags using an AI algorithm and correlates them with the corresponding product, ensuring that the correct price is always displayed.

Want to find out more about this intelligent solution that will transform stock management in markets and supermarkets? Get in touch with us.