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Retail chains rely heavily on the smooth distribution of goods. Every day, deliveries must be carefully planned to ensure that store shelves are stocked according to current demand. But when data goes wrong, the consequences can be disastrous. That’s exactly what happened to one retail company—whose name we’ll keep to ourselves.
The trucks hit the road as usual, but by mid-morning it became clear: something was off
It all started quietly. The overnight data processing ran as usual—or so it seemed. Sales data from the point-of-sale (POS) systems was transferred into the data warehouse (DWH) through an ETL process. From there, the ERP system was supposed to use it to calculate orders for individual stores and forward them to the logistics system (TMS – Transport Management System). But something went wrong. During data aggregation in the DWH, inconsistencies emerged. Due to faulty data transformation, certain products appeared to be sold out—even though they were still in stock at the stores—while others showed up as extremely high in demand. As a result, the ERP system generated incorrect orders, which the logistics team sent on to the warehouse management system (WMS) without validation, and the goods were shipped out. The trucks hit the road as usual, but by mid-morning it became clear: something was off. Some stores received an oversupply of slow-moving items, while key products were missing altogether.
Some bitterly compared the situation to planned economies under socialism
Things escalated quickly on the shop floor. Staff were confused by the deliveries—why were they receiving so many niche items, while everyday goods were nowhere to be found? Customers snatched up basic goods immediately, and others grew frustrated by the empty shelves. Some bitterly compared the situation to planned economies under socialism—"You could only get yogurt before noon"—while others simply yelled at shop staff, who were not to blame. Store managers flooded headquarters with phone calls: “We’re out of milk! Why didn’t we get any beer? Why did you send us an entire pallet of buckwheat?”
The CFO countered that IT costs the company a fortune. How is it that with all that money, things still keep breaking?
Chaos broke out at the logistics center—even though the orders in the system looked correct. The problem had to be in the data. “Those IT guys messed it up again!” someone said.
A system audit revealed the issue: an error in the transformation of sales data into delivery plans. Poorly interpreted figures made it look like certain products were out of stock (when they weren’t), and others were replenished in absurd quantities. The fix wasn’t technically difficult—but the damage was already done. The day was lost. The trucks were long gone, and the next deliveries wouldn’t arrive until tomorrow.
The CEO was furious with everyone—this wasn’t the first time, and it was pure amateurism
Senior management held an emergency meeting. It wasn’t a pleasant one. Fingers were pointed in every direction. IT should have caught it. Logistics should have noticed that the order volumes didn’t make sense—they’re not new to this. How could no one question the fact that staple goods were being delivered in unusually small quantities? The head of marketing threw up her hands—there was a major campaign running, and now the company couldn’t even get enough chicken to stores. The CEO was furious with everyone—this wasn’t the first time, and it was pure amateurism. The CTO pushed back—he didn’t have enough staff, he had to monitor thousands of alerts, and this happened at night when no one from IT is even on site. The systems are underfunded and constantly patched. The CFO countered that IT costs the company a fortune. How is it that with all that money and all those high-priced tech people, things still keep breaking?
We’ve left out the names—but if this story sounds familiar, you probably have the same problem. IT outages aren’t a matter of if, but when. The difference is whether you can predict them—and resolve them fast. Get in touch with us. Qeedio will help you be ready—before it’s too late.
