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FLEX. Logistics
We provide logistics services to online retailers in Europe: Amazon FBA prep, processing FBA removal orders, forwarding to Fulfillment Centers - both FBA and Vendor shipments.
Introduction
The operational efficiency of a distribution center is frequently measured by its ability to fulfill orders accurately and rapidly. Within this environment, order picking stands as the most labor-intensive and costly activity, often accounting for more than fifty percent of total warehouse operating expenses. Extensive time-motion studies have consistently revealed a startling reality: as much as sixty to seventy percent of a picker's shift is spent not on the actual selection of items, but on traveling between storage locations. This unproductive movement represents a significant "waste" in Lean logistics terminology. As global supply chains face increasing pressure from e-commerce growth and labor shortages in 2026, minimizing travel time has become the primary lever for enhancing throughput and protecting margins. The following seven methods represent the most effective strategies for curtailing unnecessary movement and optimizing the picking journey.
1. Implementation of Velocity-Based Slotting and Heat Mapping
The foundation of a low-travel warehouse is a sophisticated slotting strategy. Slotting is the process of organizing inventory within a facility to optimize the flow of goods. The most effective approach is velocity-based slotting, which utilizes historical and predictive data to categorize items by their movement frequency, often referred to as ABC analysis. "A" items—the top twenty percent of stock-keeping units (SKUs) that typically generate eighty percent of the volume—are positioned in the most accessible "golden zone" locations near the packing stations or shipping docks.
By placing high-velocity items at the front of the warehouse and at chest height, picking travel is reduced at two levels: horizontal distance and vertical reach. Modern slotting software now incorporates dynamic heat mapping, which visualizes picking density in real-time. If a heat map indicates that pickers are constantly converging in a specific aisle for "A" items, causing congestion that slows down travel, the system suggests "balancing" the slotting. This might involve spreading high-velocity items across multiple aisles to maintain high pick density while avoiding traffic bottlenecks. For example, during a seasonal promotion, an electronics retailer might move promotional items to "end-caps" or cross-docking areas to eliminate the need for pickers to enter deep storage zones entirely.
2. Strategic Adoption of Batch Picking and Cluster Picking
Traditional "discrete" picking, where a worker fulfills one order at a time from start to finish, is inherently inefficient for multi-item facilities because it requires a full circuit of the warehouse for every order. Batch picking overcomes this by consolidating the requirements of multiple orders into a single picking pass. A picker is directed to a location and instructed to pick the total quantity of a specific SKU needed for all orders in that batch. This "pick-to-summary" approach ensures that a picker visits a specific bin only once, regardless of how many orders require that item.
Cluster picking takes this a step further by utilizing carts or autonomous mobile robots (AMRs) divided into multiple bins, each representing a distinct customer order. As the picker travels through the warehouse, they sort the items directly into the correct order bins at the point of pick. This method eliminates the need for a secondary sorting process at the pack station while still drastically reducing travel distance per order. In an apparel warehouse where orders often consist of two or three items, cluster picking can reduce travel time by over forty percent compared to discrete methods, as the travel distance is amortized across ten or twelve orders simultaneously.
3. Transition to Goods-to-Person (G2P) Automation
Perhaps the most radical method for reducing travel time is to eliminate picker movement altogether through Goods-to-Person (G2P) technology. In a traditional "person-to-goods" setup, the worker travels to the inventory. In a G2P system, automated storage and retrieval systems (AS/RS), horizontal or vertical carousels, or grid-based robotic systems bring the inventory directly to a stationary picking station.
By centralizing the picking activity, travel time is effectively reduced to zero. The worker remains in an ergonomically designed workstation, and the system sequences the delivery of bins to ensure high productivity. While the capital expenditure for G2P systems is significant, the ROI is often driven by the massive gains in labor efficiency and the ability to utilize the full vertical height of the warehouse. For instance, in high-density pharmaceutical distribution, a G2P system allows a single worker to achieve pick rates that would require five or six manual pickers in a traditional racking environment. Furthermore, since the system manages the movement of goods, the warehouse can operate in a "lights-out" or temperature-controlled environment that would be challenging for human travel.
4. Optimization via Path-Sequencing Algorithms
In manual or semi-automated warehouses, the sequence in which a picker visits locations determines the total distance traveled. Basic Warehouse Management Systems (WMS) often sequence picks by location ID, which may lead pickers on a "zig-zag" path that doubles back on itself. Advanced path-sequencing algorithms, often based on the "Traveling Salesman Problem" mathematical framework, calculate the most efficient route through the warehouse for any given set of orders.
The most common algorithms include "S-shape" (or serpentine) traversal and "largest gap" routing. In an S-shape strategy, the picker enters an aisle at one end, travels the full length, and enters the next aisle from the opposite end. This is highly effective for high-density picking where almost every aisle contains a required item. Conversely, heuristic algorithms can dynamically adjust the path based on real-time factors, such as aisle blockages or the presence of other pickers. By implementing intelligent path sequencing, facilities can often achieve a fifteen to twenty percent reduction in travel distance without changing their physical layout or investing in heavy automation.
5. Implementation of Zone Picking and Pick-and-Pass Systems
Zone picking, frequently referred to as the "assembly line" approach to order fulfillment, divides the warehouse into distinct physical areas or zones. Each picker is assigned to a specific zone and only picks the items from their area for any given order. Once the picks for that zone are complete, the order (often in a tote on a conveyor) is "passed" to the next zone.
This method reduces travel time by confining each worker to a small, manageable footprint. The picker becomes highly familiar with the locations in their zone, further reducing "search time," which is a secondary component of travel. Zone picking also allows for the synchronization of different storage environments; for example, one zone might be a high-security area for electronics, while another is a standard bulk storage area. By preventing workers from traversing the entire length of a massive distribution center, zone picking minimizes the "fatigue factor" and ensures that picking velocity remains consistent throughout a shift.
6. Utilization of Cross-Docking to Bypass Storage
The most efficient way to reduce picking travel is to avoid the storage and picking process entirely for as many items as possible. Cross-docking is a strategy where inbound goods from a supplier are moved directly from the receiving dock to the outbound shipping dock with little to no storage time in between. When an inbound shipment arrives, the WMS identifies if there are active backorders or immediate requirements for those specific items.
Instead of traveling to a storage bin in the back of the warehouse, being put away, and later being picked by a worker traveling to that same bin, the goods are diverted to a staging area near the shipping doors. This eliminates two major travel events: the put-away journey and the picking journey. Cross-docking is particularly effective for fast-moving consumer goods (FMCG) and items with high demand predictability. For a high-volume grocery distributor, cross-docking can account for up to thirty percent of daily volume, drastically reducing the total "travel miles" logged by the warehouse fleet and manual pickers.
7. Deployment of Collaborative Autonomous Mobile Robots (AMRs)
Collaborative AMRs represent a middle ground between manual picking and full G2P automation. In this model, human pickers remain in specific aisles or zones, and the AMRs travel between the picking zones and the packing stations. The robot meets the picker at a specific location, the picker places the item on the robot, and the robot then travels to the next pick location or back to the shipping area.
This "follow-me" or "lead-me" robotics strategy ensures that the humans focus on the high-value task of picking—which requires human dexterity and visual recognition—while the robots handle the low-value task of long-distance horizontal travel. This separation of duties allows pickers to remain in a "productive flow" within a few aisles rather than walking miles every day. Data from implementations suggests that cobotic environments can double or triple units-per-hour (UPH) metrics by simply removing the "walk to pack" and "walk back to pick" segments of the cycle.
Conclusion
Reducing picking travel time is not a matter of making workers move faster; it is a matter of making them move smarter. As analyzed, the most effective methods range from foundational data-driven strategies like velocity-based slotting and path sequencing to advanced technological interventions like G2P automation and collaborative robotics. Each method aims to maximize the time spent on value-added selection and minimize the time lost to transit. For logistics managers, the successful integration of these strategies is essential for building a resilient, high-throughput fulfillment operation that can scale alongside increasing consumer demands. By focusing on the "science of movement" within the four walls of the warehouse, organizations can achieve a profound impact on their overall supply chain efficiency.
