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ADVERTISEMENT FEATURE Automated warehousing


HOW DEXORY’S DATA INTELLIGENCE TRANSFORMS PEAK FULFILMENT


HOW DEXORY’S DATA INTELLIGENCE TRANSFORMS PEAK FULFILMENT


  


I


n a world where next-day delivery has become the norm, warehouses are under more pressure than ever. E-commerce growth, labour shortages, and rising customer expectations have created a perfect storm. As a result, maintaining accuracy and speed is essential to protecting customer trust.  operations. Experts refer to this as the “warehouse chaos cycle”. Fragmented data and reactive decisions create growing operational issues across operations. This loop also limits the real  operations.


 Post-pandemic shifts in shopping behaviour


  more SKUs, tighter delivery windows, and higher accuracy requirements. Seasonal peaks such as Black Friday and Christmas only magnify these pressures, stretching already limited resources.


  “A single misplaced pallet or inaccurate count can slow down the entire supply chain, impact  The issue, he added, is that traditional


warehouse visibility simply can’t keep pace  inventory checks and partial scans leave  preventing them. This reduces operational  customer service.   partial cycle counts, which only provide snapshots of the inventory landscape. These    end up making decisions in the dark. Over    business decisions. “You start with incomplete data, which leads to reactive decisions, which in turn


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create more errors and bottlenecks,” Boone said.  than focusing on improvement.”


Labour shortages compound the operational


pressures already in place. During peak retail  Temporary workers often lack the training and experience to maintain accuracy in fast-paced environments.


 “It’s about empowering the people you already have. It also means giving them the tools to  time insights.”


 Dexory’s solution is simple yet powerful.  warehouse each day and capture a complete, accurate snapshot of inventory. “Instead of sampling small parts of the


warehouse, we scan everything,” Boone explained. “That gives our customers full visibility. They keep clear oversight of all inventory, its location, and any items that may be missing.” Dexory’s analytics platform, DexoryView, automatically receives the data, creating real- time digital twins of warehouse operations. This level of data integration supports stronger risk  


proactive, data-driven decisions,” Boone said. “They no longer have to react only after problems occur.”


By unifying operational information with


relevant customer data, warehouses gain a clearer picture of demand patterns and can adjust    the approach. Across Dexory’s customer base, sites have seen:   


Boone says the implementation is also  minimal integration,” he said. “This means warehouses can keep running without stopping operations or overhauling their systems.” These improvements strengthen the


warehouse bottom line, delivering a clear competitive advantage.


  customers are now moving beyond visibility to true predictive intelligence rooted in predictive analytics and modern data science. “Our robots scan entire facilities every day, building a rich dataset that reveals long-   compare performance across multiple sites.” This level of insight helps warehouses


 op. It also sets the foundation for predictive decision-making and stronger strategic decision frameworks.


  of chaos compounding over time, data becomes the driver of continuous improvement.”  Dexory recently passed a major milestone:


 achievement shows the scale and adoption of  every scan, the company’s vision of a smarter, data-driven warehouse ecosystem becomes more tangible.


“In the end, visibility isn’t just about knowing


where your stock is,” Boone concluded. “It’s about giving every warehouse the intelligence  and agility.’


Dexory www.dexory.com


Automation | January 2026 27


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