Intelligent replenishment system，Timely reduction of stockouts in stores

Intelligent replenishment system

Timely reduction of stockouts in stores

Company B is a large chain supermarket company that has been in business for many years. In order to reduce the out-of-stock rate in the store and save the investment in labor costs, it cooperates with DMALL to use the intelligent replenishment system. Based on real-time data calculation and analysis, and the combination of AI cameras and visual algorithms, the replenishment tasks in the store are digitized, which not only improves the efficiency of manual work but also reduces the out-of-stock rate.

Background and Issues

Low replenishment efficiency in stores

Relying on staff to patrol the store and record out-of-stock items results in low execution efficiency.

Loss of sales opportunities

When replenishment efficiency is not guaranteed, empty shelves can appear, leading to lost sales opportunities.

Difficulties in quantifying and managing labor costs

Employee wages do not match the amount of replenishment work, making it hard to achieve quantifiable management and increasing management complexity and costs.

Real-time data analysis to reduce stockouts

By analyzing sales, inventory, and display data, the system enables timely and efficient replenishment management, reducing stockouts and improving operational efficiency.

Task assignment and replenishment completion rate exceeds 95%

Through system calculations and AI cameras, tasks are digitized and pushed to staff, resulting in a replenishment completion rate exceeding 95% and reducing replenishment costs.