Where Warehouse Operations Are Finding Labor Leverage
The operations pulling ahead in this labor market aren't trying to escape labor costs. They're getting more out of every person on the team. That's the whole game right now: warehouse labor costs are up more than 15% since 2020 and turnover sits near 49%, so where you point your people is one of the largest variables on the P&L.
Most operations track the visible costs, headcount and overtime. The less visible ones are just as real: productivity lost when an experienced cycle counter leaves, errors from undertrained new hires that turn into chargebacks and missed SLAs, supervisors pulled off the floor to absorb the gap. Most of it traces back to one thing, what you're asking your people to do.
Where your team's time actually goes
Manual cycle counting is the closest most operations can get to ground truth in their facility. It's how teams validate what the WMS says against what's actually on the floor, but "closest" isn't the same as accurate. Even a well-run counting program only covers a fraction of the facility at any given time. And shutting the floor down to count means lost throughput, while counting around active operations means the data can never be fully accurate.
The way most operations are forced to do it comes with real costs. It's time-consuming and often hazardous, whether that means operating in freezer aisles or climbing cherry pickers thirty feet up. And it pulls experienced people away from fulfillment and exception management, the work that has direct impact on the floor.
The data problem compounds the human one. By the time a manual count is complete, the floor has moved on, and hours of careful work have produced something the operation can't fully rely on. When a meaningful share of the job is work that could be automated, and the output isn't reliable when it's done, retention gets harder to defend.
How the math compounds across the network
Every departure means rehiring and retraining. New hires make more errors that become mispicks, then chargebacks that land on the P&L with no obvious origin. Overtime added to finish long counts becomes a fixed cost nobody questions. Across a network of facilities the drag is real but diffuse, which makes it hard to fix at the source.
What automated counting unlocks
When cycle counting is automated, the team doesn't shrink. It gets redirected to work with more direct impact on the operation. For operations using agency crews for periodic counts, that recurring cost disappears entirely.
At Barrett Distribution, after deploying Gather AI, the inventory team went from six dedicated cycle counters in very narrow aisles to one person managing the program. The rest of the team got redirected to value-added work, and Barrett eliminated $250,000 in material handling equipment.
And because automated counting is continuous, the data stays current. Order pickers find product where the system says it is, and exceptions get caught before they become chargebacks. The accuracy and labor problems have the same root cause and the same fix. This is what Physical AI for logistics delivers: accurate, current floor data as the default.
The part you can actually control
The labor market is what it is. What's actually in your control is what your team is tasked with. When people do work that's engaging and connected to visible outcomes, they stay longer. That shows up as lower hiring costs and error rates.
In an industry where high turnover is the norm, that's a competitive advantage. The operations redirecting their teams aren't just cutting costs. They're becoming places people actually want to work.
You can't be immune to the labor market. But you can be the anomaly inside it.
See how operations like yours have redeployed their teams with Gather AI. Request a Demo.
