Inventory validation is becoming a critical component of fulfillment accuracy — and of the confidence leaders place in the operation. It’s within reach but won’t be easy. Warehouses have spent years adding automation, optimization software and robotics to increase resilience and performance. Early movers deploying software-enabled and robotics solutions have enjoyed a temporary competitive advantage throughout COVID, tariffs, high oil prices and inflation. The next challenge is not simply moving more product faster, but building processes that can detect and prevent errors before they become downstream costs. 

SKU counts and fulfillment complexity continue to rise across retail, distribution, manufacturing and omnichannel operations. Skilled labor remains difficult to recruit and retain, service expectations keep increasing, and costs remain volatile. AI and analytics can create new visibility, but they cannot compensate for weak processes or unreliable operational data. 

Translation: “Good enough” accuracy is no longer good enough. Raising the performance bar requires a more connected approach to the physical warehouse, process design, data and digital tools. The objective is greater operational confidence — knowing that inventory data, workflows and the customer promise can be trusted. 

The Cost of Getting It Wrong 

The first step is understanding the true cost of a fulfillment error, because its impact extends far beyond the cost of correcting an order. 

“There’s been a shift in consumer expectation that changes how we all need to think about the supply chain,” explains TJ Fanning, vice president sales and consulting for Kardex, a Swiss provider of automated warehouse storage and retrieval systems. “Historically, people have thought about a missed shipment in terms of just the cost to process it, but what’s the brand impact from receiving the wrong product when it’s so easy next time to find another domain selling the same product at the same price?”  

At that point, the ability to guarantee on-time delivery of the product and quantity promised becomes the key differentiator. E-commerce customer retention rates now hover around 30%, according to Shopify data; a recent Microsoft study reports that 95% of consumers say customer service quality is essential to brand loyalty, while 73% say they will switch brands after one bad experience, according to PwC. 

Many factors contribute to inventory errors, including temporary or less experienced workers, high turnover, long or demanding shifts, simple data-entry mistakes, items moved out of position, and product or packaging information that changes faster than warehouse records are updated. 

A more fundamental challenge across fast-moving fulfillment environments is product data that changes faster than item masters are updated — new pack sizes, packaging, dimensions, formulations and supplier configurations. “A supplier may ship toothpaste in a master pack as a unit,” Fanning says, “but then suddenly the store receives 30% more toothpaste because of some random box change. Or there’s an initiative to save on cardboard and they change the packaging, but nobody updates the item files. Or a manufacturer ships from two different facilities, one with the old packaging line and one with new, totally different form factors.”  

Fanning estimates that four in five shippers don’t have confidence in their data internally or from suppliers, on the product dimensions of the goods they’re moving and storing. That’s a problem for the warehouse if weight and cubic capacity are among the data fields essential for inventory validation.   

Errors can also become more costly when they go undetected. Fanning cites an instance of a customer ordering an individual video game online, receiving an entire 20-game pack, then posting about the error online, prompting copycat orders. “There’s no accountability for that in today’s market,” he says, “because they likely won’t know for months that they mis-shipped the unit.” The broader issue is how long it can take an operation to discover the root cause of a mis-shipment and correct the underlying data or process. 

As warehouses quietly become more operationally fragile from poor visibility, more demanding customers and expanding workloads, teams are spending more time validating inventory, correcting preventable mistakes, managing exceptions and working around broken processes than ever before.  

From Detecting Errors to Preventing Them 

So what should operations do to reduce fragility and improve inventory confidence? Fanning points to four areas where better process design, automation and AI-assisted validation can work together: 

AI-assisted validation.  Internet-of-things (IoT) technology — sensors, scanners, readers, scales, cameras can create additional validation checkpoints as goods move through the operation. Used in the right places, these tools can help compare what the system expects with what is actually being received, stored, picked or shipped. 

Products and quantities can be validated by their relative weights on the truck, forklift, in storage, from station to station, to shipment. And barcode, dimensional and image data can provide additional evidence that products and quantities match expectations. Those records can help flag exceptions earlier and, where appropriate, support traceability, compliance and issue resolution. 

“With that data and the power of AI you can combine things like the task, the related data, item and quantity picked out of this unit from this location,” Fanning says. “With the weight and a picture before and after the pick, and the master item file dimensions, you can quickly feel confident the right thing was shipped.”  AI does the analytics and validates a correct shipment in seconds without need for complex operator keyboard commands or help from a human supervisor.     

Intelligent operator guidance.  An automated, goods-to-person (GTP) system reduces travel and brings inventory to controlled workstations, where additional guidance and validation tools can be concentrated. That creates an opportunity to simplify the operator experience while adding more consistent checks at the point of work. 

The objective is not to remove human judgment entirely, but to reduce unnecessary decision burden in fast-paced workflows. Technology can help answer routine questions: Is this the right product or product mix and count? Is it the best travel path and sequencing of steps in the pick? Are the orders prioritized correctly? Is the cartonization optimal in terms of size, material used and dimensional-weight postage?  

Shifting these decisions to AI allows faster, frictionless handling across the pick, pack, putaway and replenishment stages, at the same time reducing human stress and fatigue.     

Real-time inventory confidence.  Continuous, end-to-end order and inventory tracking — from pallets received to storage to items shipped — by SKU product code, dimension, weight and photographic validation, plugs major visibility gaps where exceptions arise. A well-designed GTP operation can also significantly reduce unnecessary human touchpoints and create more controlled points of interaction with inventory. 

“Controlling and minimizing where the people are ensures that the inventory is accurate when stored, because the only time people can interact with it is to capture the initial data to confirm,” Fanning explains. “After that, physical movement of the material for storage and retrieval is done by a robot.”  

Sensors 3D cameras and scale tools can add validation checkpoints around bin and workstation interactions, helping flag mismatches in weight, dimensions or item identity before they become downstream errors. So if, say, a stray item has fallen into a bin, the system will sense it and not allow that bin to be filled further. In a manual operation, by contrast, a worker under time pressure might put the stray item back with a like product, creating a potential mispick and exception later.  

Workflow optimization.  Reconfiguration of the warehouse footprint, also enabled by AI and automation, can deliver enhanced benefits beyond just that of inventory validation and improved accuracy.  

High-density cube storage and GTP workflows, for example, can reduce travel and use vertical space more efficiently, freeing footprint for slower-moving or non-bin-friendly inventory, added product lines, value-added services or future expansion. “You can now use this newly available space to accelerate growth and to compete on something more than just price,” Fanning says. 

Working in combination, a goods-to-person system with high-density vertical storage and AI-assisted inventory validation can triple the throughput of a comparable manual warehouse, reducing floor space by up to 85% and workforce by as much as a third to a half, with better than 99% inventory accuracy rate. Results, however, depend on the operation, SKU profile, process design and how well the technologies are integrated into the broader fulfillment flow.              

Technology will remain critical in helping warehouses keep pace with demand and disruption. But the next competitive advantage will come from building confidence into the operation — confidence in the inventory data, the workflow and the promise made to the customer. That requires targeted investments that prevent errors, reduce exceptions and help technology and people work together more intelligently.

Resource Link: Kardex, https://hubs.li/Q03ZyNHG0