Cluster picking is a picking strategy where warehouse workers pick items for multiple orders at the same time. With cluster picking, items are arranged in different bins. Each bin is numbered, so pickers can identify the product and its location quickly. The pickers move around in the picking area by using a picking cart or trolley. It allows employees to fulfill several orders in a single operation without the need for further sorting.
When is Cluster Picking Used?
Cluster picking is suitable for medium to large-sized warehouses.
Advantages of Cluster Picking
- Reduces handling and sorting requirements further down the line
- Optimal for small and medium-sized items
- Lower walking distance if you combine the right orders
Disadvantages of Cluster Picking
- The number of orders per cart of each trip is limited
- Long pick paths that take a lot of space
- Large items can’t fit on the cart
- At maximum capacity: problem with congestion and inefficiency
How is Cluster Picking Done Currently?
Cluster picking usually is done with the help of a warehouse management system (WMS).
In most WMS, like SAP EWM, Manhattan, and BlueYonder JDA cluster picking is managed by basic business rules, leaving optimization potential on the table. These rules often focus on basic criteria, without considering more nuanced factors that could enhance efficiency and reduce walking distance for the pickers.
It can only be done in an intelligent way if warehouses have a digital twin layout. This replica of your warehouse allows you to simulate different picking strategies and assess their impact on picking distance throughput time. It is mandatory to have the distance between every location in the warehouse. By running “what if” scenarios, warehouses can identify the most efficient strategies for your special operations. That is the reason why digital twins become more relevant and popular because they provide faster results and allow warehouses to test solutions faster.
A Smarter Approach
With smart picking solutions, warehouses can implement addons on top of their existing warehouse management systems allowing 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 reduce 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 smart solutions to improve picking performance