When Faster Picking Creates a New Supply Chain Bottleneck

Regional distributors can absorb rising order volumes only for so long before warehouse processes begin to restrict the wider supply chain. The warning signs are often gradual: longer picking routes, inconsistent inventory information, growing spreadsheet use and more time spent coordinating warehouse, purchasing and sales teams.

These problems extend beyond the distribution centre. Picking delays affect inventory availability, order accuracy, carrier cut-off times and customer commitments. In sectors such as plumbing, HVAC and industrial supply, an incomplete or late order can also interrupt work at a contractor’s job site.

Research shows why picking performance attracts so much operational attention. An academic review published in the European Journal of Operational Research estimated that order picking can represent as much as 55% of total warehouse operating expense. Separately, the 2025 MHI and Deloitte Annual Industry Report identified workforce and talent shortages as a highly impactful supply-chain trend among 35% of surveyed professionals.

Growth Exposes Process Weaknesses

This was the challenge facing Hirsch Pipe & Supply, a Southern California distributor operating 30 locations. Distribution volumes across its network had more than doubled, placing pressure on processes that included manual and spreadsheet-based work.

Adding employees could have provided temporary capacity, but it would not necessarily have corrected the underlying constraint. When workers depend on fragmented information and inefficient travel routes, increasing headcount can create additional coordination requirements without producing a proportional improvement in throughput.

Hirsch implemented the Latitude warehouse management system from PathGuide Technologies to coordinate warehouse activity more effectively while retaining its existing enterprise resource planning environment.

The implementation included zone-based picking, which assigns workers to defined areas instead of requiring each picker to travel throughout the facility. The approach can reduce travel and build familiarity with products and storage locations, particularly in warehouses containing varied product categories.

Hirsch reported a 25% improvement in picking efficiency following the implementation. The company also reduced manual spreadsheet activity and made inbound and operational information more accessible to its warehouse, purchasing and sales functions.

“We needed a system that could scale with us without forcing us to change how we operate,” said Robert Gabrielson, Vice President of Supply Chain at Hirsch Pipe & Supply.

Faster Picking Can Move the Constraint

After a WMS improves picking speed, the bottleneck can move to consolidation, packing and shipping. In zone-based picking, different parts of the same order may be collected simultaneously and then brought together at a single point. If downstream capacity and synchronization are not adjusted to the new pace, queues form, orders wait for items from other zones and loading is delayed.

A local 25% improvement in picking can therefore increase pressure elsewhere without reducing total order-cycle time. Faster warehouse execution may also expose weaknesses in replenishment, transportation scheduling or carrier capacity. For supply-chain leaders, this means that picking performance cannot be assessed separately from the complete order flow.

As Keith Moore, CEO of AutoScheduler, told Warehouse Insider in previous coverage: “You either work faster or you work more intelligently. Working more intelligently is where most people miss the opportunity.”

The distinction is important. Increasing the speed of one process produces limited value when the surrounding operation cannot absorb the additional volume. Supply-chain teams need to monitor order-cycle time, packing queues, dock utilisation, carrier cut-off performance and overtime alongside traditional picking metrics.

MHI’s Solutions Community has similarly warned that downstream bottlenecks can cause orders to accumulate at packing stations and delay the flow of goods to carriers.

The Measure Is End-to-End Flow

The 25% figure disclosed by Hirsch provides evidence of improved picking productivity, but the company did not release the original picking rate, implementation cost, order-accuracy results or measurement period. Without those details, the complete return on the investment cannot be independently assessed.

A stronger evaluation would compare performance before and after implementation across the entire fulfilment process. Relevant measures include the time from order release to shipment, labour hours per completed order, replenishment delays, mis-picks, packing capacity and the percentage of orders meeting carrier collection deadlines.

Eric Allais, President and CEO of PathGuide Technologies, said the implementation improved labour efficiency and helped Hirsch identify further productivity opportunities.

For supply-chain professionals, the wider lesson is that a WMS should not be treated as an isolated warehouse upgrade. Its value depends on how effectively it connects inventory, labour and order information with purchasing, sales and transportation decisions.

The immediate objective may be faster picking, but the operational goal is consistent flow from inbound receipt through final dispatch. If the improvement merely moves congestion from the aisles to the packing station or loading dock, the warehouse has accelerated one task without improving the supply chain.