Wave picking is an order release strategy where groups of orders are assigned to pickers at specific times. This method organizes the picking process to align with packing and shipping operations and can be combined with other order picking techniques.
In wave picking, order items are not picked immediately upon order arrival. Instead, they are released in "waves" at specific intervals for picking when multiple orders are grouped together based on factors such as storage location, order priority, item type, count, or carrier.
This strategy allows multiple orders to be picked simultaneously in one trip, optimizing picking operations and increasing daily order fulfillment.
Note: Wave picking is often referred to as cluster picking, however, cluster picking is the grouping of orders without the scheduled picking into waves. Cluster picking is often combined with wave picking.
In wave picking, order fulfillment is synchronized with operational schedules, while in cluster picking, the emphasis is on minimizing travel distance and time during the picking process.
Steps in Wave Picking
Wave picking involves 3 main steps:
- Pre-wave picking includes scheduling waves based on specific variables like shipping time, item location, order priority, etc.
- Performing wave picking - pickers move through the warehouse, collecting items for all orders in a wave before starting the next one.
- Post-wave picking occurs after items are picked, where orders are organized for sorting and packing before being loaded and shipped.
Advantages of Wave Picking
- Highly efficient for picking multiple orders with the same items.
- Saves time when retrieving items for multiple orders with identical or nearby stock.
- Separates picking and packing processes, providing two opportunities to verify order contents. This process becomes very secure if both pickers and packers scan the items.
Drawbacks of Wave Picking
- Requires careful planning and coordination with every aspect of your business which requires an effective WMS
- When each order is unique, the efficiency of picking multiple items at once is compromised.
- Requires more space for staging between the picking and packing processes.
- When handling numerous orders with diverse items, finding specific items in the staging area can be challenging for packers.
Best suited for warehouses that have high order volumes, a large inventory, and a sophisticated warehouse management system in place - making it a popular strategy for e-commerce warehouses with many SKUs.
Order Picking Method Comparison
How Do Warehouse Management Systems Perform Wave Picking?
In a warehouse management system (WMS), wave picking is typically managed through predefined rules or algorithms that determine how orders are grouped into waves for picking. However, these rules may sometimes oversimplify the process by focusing on basic criteria such as order arrival time or order number, without taking into account more nuanced factors that could optimize efficiency and reduce warehouse congestion.
When a WMS lacks the flexibility to incorporate these factors into its wave picking logic, it can lead to inefficiencies such as increased traffic and confusion in the warehouse.
For example, picking waves that are poorly planned may result in pickers traveling long distances between different storage areas or encountering bottlenecks at packing stations due to mismatched order priorities.
Smarter Approach to Wave Picking
With smart picking solutions, warehouses can implement more addons on top of their existing warehouse management systems allowing them to reduce pick distances by 25 - 40% by applying a 2-step approach:
(1) Order clustering - strategically cluster orders together while considering all factors and reducing pick distances by 15 to 30%.
(2) Picking path optimization - generate the shortest pick path avoiding the typical scenario where a picker will follow intuition which will drive them in a snake pattern picking path, causing longer than necessary walking distances.
The picking path optimization module is applied to the optimized clusters to get the shortest pick path within those clusters allowing to cut walking distance by an additional 10 to 20%.
Learn more about optimizing wave planning in your picking operations.