For a retailer running 16 stores across the Northeast, stale inventory wasn't a small problem. It was a monthly bill. Products that didn't sell in time had to be discounted hard or thrown out, and every stale item risked a bad review, a lost customer, and damage to a brand built over years.
EverGreen wasn't missing data. Sales, inventory, and product performance lived in its systems. The problem was turning that data into action before products became hard to sell.
For Lexy, who oversees a network of stores across the state, the problem was bigger than any one location. She needed to know which stores were sitting on slow-moving inventory and whether her managers were catching it in time. But with hundreds of SKUs moving across many locations, expiry dates were hard to track and visibility broke down as inventory scaled.
“I think it would be useful to know if there are products we haven't sold in several days. If I have items that might not be stale but also haven't sold in a week, I like to pay attention to what's moving and what's not.”
The challenge: slow-moving inventory caught too late
Most inventory systems can tell you what's in stock, but not which products are quietly losing momentum. A product might go days without selling, or a category might slow down, while a store still looked healthy overall and certain items aged on the shelf.
By the time the issue was obvious, managers had fewer options: discount harder, push promotions, or spend extra time moving inventory they could have addressed earlier. And because each store handled visibility differently, some checking dashboards, others relying on memory or meetings, Lexy couldn't easily tell which managers were staying on top of inventory and which needed her support before small problems turned into losses.
EverGreen needed every store to answer the same questions: What hasn't sold in days? What's becoming at risk? Where should the team focus today?
The solution: AI-powered reports built around store decisions
EverGreen partnered with 100xTeam to build AI-powered store reports from its existing sales and inventory data.
Every business has reports. What EverGreen didn't have was one that read the data like an analyst and told each manager what to do. Instead of just sharing numbers, the reports flagged the products at risk and the action to take, every day.
The shift was practical. Instead of digging through dashboards without strong analytical support, managers opened a report that already pointed to the items needing attention, so they could run daily or weekly inventory refreshes before products became hard to move. For Lexy, the reports created a consistent view across locations, and she could finally see how each store was executing.
The results: less stale inventory, faster action
The reports quickly became part of how stores reviewed performance. At one location, a general manager found his report useful enough to print and pin to the office wall.
“It helped the whole team get a good sense of how we were performing and catch issues before it was too late.”
Across 16 stores, EverGreen cut stale inventory loss by 32% and improved top-category sell-through by 28%.
For EverGreen, the result was not just better reporting. It transformed inventory management from a constant scramble against stale products into a system managers find intuitive and easy to run, protecting both margin and the customer experience.
* All names have been modified to preserve privacy.
