From Sensing To Action: How Warehouses Turn Real-Time Data Into Automated Decisions

Rising labor constraints, tighter service-level expectations, and persistent execution gaps are pushing warehouse operators to move beyond visibility and toward real-time decision automation on the warehouse floor. As distribution environments grow more complex, the ability to translate frontline data capture directly into automated actions is increasingly viewed as an operational necessity rather than a technology upgrade.

Why Decision Automation Has Become Urgent

The pressure is most visible at the point of work. Inventory accuracy, exception handling, and task prioritization all depend on data quality at the edge, yet many operations still rely on manual interventions or batch-based system updates. This disconnect slows response times, inflates labor costs, and limits the value of analytics further upstream, particularly in high-throughput and omnichannel environments.

In response to a media query from The Supply Chainer, Andre Luecht, Global Strategy Lead for Transport and Logistics at Zebra Technologies, said the most consistent gains appear when automation is anchored directly to frontline execution rather than centralized planning layers.

Where Automation Delivers Measurable Impact

“In our customer deployments, we see the most successful conversion of real-time data capture into automated action at the edge of the enterprise. This is where the work gets done,” Luecht said. He pointed to RFID-enabled cycle counting, where retailers move from roughly 85% inventory accuracy to over 99%, allowing replenishment and omnichannel fulfillment decisions to be triggered automatically without human intervention.

According to Luecht, similar benefits emerge in exception handling and machine vision use cases. Automated barcode capture at pack stations and on material handling equipment removes repetitive manual scanning and enables real-time verification during receiving, staging, and loading. “This automates barcode scanning at the pallet level during workflows such as receiving, staging, and loading, where both the pallet barcode and location barcode are read simultaneously and automatically,” he said.

Andre Luecht, Global Strategy Lead for Transport and Logistics at Zebra Technologies

These capabilities translate directly into higher throughput and labor productivity. Luecht noted that hands-free wearable workflows can raise individual worker productivity by 15-20% by eliminating wasted motion, while dock-door automation can process thousands of parcels per hour without manual scanning bottlenecks.

Scaling Automation Without Breaking Operations

As automation expands, new constraints emerge. Highly optimized systems can introduce process rigidity, and large fleets of mobile devices require disciplined governance to ensure uptime, updates, and consistency across sites. Integration with legacy WMS and ERP platforms remains a structural challenge, particularly when those systems are not designed for continuous, high-volume data ingestion.

“The data still struggles to support automation reliably when the backend systems are not equipped to handle the richness of the data we can now capture,” Luecht said, noting that API-first integration approaches are increasingly used to bridge that gap without full system replacement.

For supply chain leaders, the implication is pragmatic rather than transformational. The path forward is less about full-site automation and more about scaling discrete, high-impact workflows that align frontline execution, backend integration, and workforce adoption. Organizations that get this balance right are likely to realize faster returns while maintaining operational resilience as automation deepens.