In many a warehouse today, control feels like a compromise. Speed or accuracy. Cost or service. You might get two, if you’re lucky.
Under pressure from tighter service-level agreements (SLAs) and rising expectations, every misplaced pallet carries more than just a financial cost. It can jeopardize a customer relationship, invite penalties, or trigger a cascade of operational issues.
Warehousing has changed. What used to be invisible infrastructure is now a visible link in the customer experience. Yet, despite significant investment in forecasting and fulfillment, inventory control remains outdated in most facilities. Wall-to-wall counts are still common — often done once or twice a year, supplemented by monthly or ad hoc cycle counting. In between, most inventory movements go unchecked.
That leaves long stretches with limited visibility, relying on reactive firefighting when discrepancies surface. Some operators attempt to close the gap by scanning everything frequently—but the cost, disruption, and diminishing returns make that approach unsustainable.
After more than 100 million autonomous location checks, a different approach is emerging.
Why brute force falls short in the warehouse
Scanning everything is intended to reduce risk. The logic is straightforward: more scans equal more control. But the numbers tell a different story.
On average, it takes 650 random checks to find a single inventory issue using traditional methods. That’s hours of effort, equipment wear, and process disruption—for one result. Multiplied across large networks, the cost is substantial.
Worse still, this approach often creates a false sense of control. The friction it introduces doesn’t consistently prevent the kinds of issues that matter—late shipments, stockouts, or partial orders.
And fundamentally, brute-force scanning runs counter to the principles of operational excellence. It prioritizes volume over value, activity over outcome. It ties up time and resources without proportionate impact—something no truly efficient operation can afford.
In short: it’s effort without impact.
Save now with early bird registration
A smarter model: targeting risk, not routine
Verity’s system works differently. Instead of applying checks uniformly, it prioritizes areas where discrepancies are most likely, guided by patterns in historical data, risk levels at specific locations, and operational context.
The result: One in 59 targeted checks uncovers a discrepancy. That’s more than 11 times the effectiveness of random checks.
It’s similar to a postal worker who already knows where to deliver mail. No time wasted checking all addresses just in case—just a direct path to what matters that day.
What 100 million checks reveal
Smarter scanning can reshape performance across the board:
- Issues are caught earlier—before they snowball into disruptions.
- Inventory accuracy improves, leading to more on-time, in-full deliveries.
- Operational teams regain time otherwise spent on rework or firefighting.
- And because the system runs autonomously, it adds control capacity without adding pressure—working during off-hours or between shifts.
This isn’t just about efficiency. It’s about resilience.
The real stakes: experience and margin
Every avoided error is a smoother delivery, a more satisfied customer, a reputation maintained.
In business-to-business (B2B) markets, 65% of customers say they’ve switched suppliers due to poor service. So while warehouse leaders face pressure to cut costs, reducing control is rarely the right answer. Poor control leads to rework, lost trust, and shrinking margins.
Verity’s approach offers a way out: Reduce cost by increasing focus—not by reducing oversight. That shift supports teams who are balancing the hidden cost of excess inventory with the visible impact of a failed delivery.
Looking ahead: from compliance to confidence
Traditional control systems were built for compliance. But compliance alone is no longer enough when customer experience drives competitive advantage.
What’s needed now is predictive, intelligent control—something that prevents issues before they happen. It’s not about checking boxes. It’s about removing friction from the system.
Warehousing is entering the age of artificial intelligence. But success won’t be defined by whether AI is used—it will be defined by how it’s applied. Like large language models (LLMs), where better prompts lead to better answers, the real advantage lies in how the system focuses its effort.
With over 100 million autonomous checks behind us, one insight stands out: Effective control isn’t about scale. It’s about precision.
About the author
Markus Waibel is co-founder and chief strategy officer of Verity, a leading provider of AI-powered autonomous systems for warehouse intelligence and inventory control. A key member of the executive team, he shapes the company’s strategic direction and drives its growth, drawing on deep experience in robotics, entrepreneurship, and technology leadership.
Prior to founding Verity in 2014, Waibel was deputy director of the Institute for Dynamic Systems and Control at ETH Zurich, where he led the groundbreaking cloud robotics project RoboEarth. He also co-founded routeRANK, the world’s first multi-modal travel planner (acquired in 2022), and Robohub, a major online platform for the robotics community.
Waibel serves on the board of Verity AG and was the founding president of Switzerland’s Drone Industry Association. He holds a Ph.D. in robotics from EPFL and an M.Sc. in technical physics from TU Vienna.
