The time has come; it is time to evaluate your warehouse’s picking strategy. In most situations, picking strategies do not change that often. However, all aspects of your operation should undergo evaluations from time to time to make sure that there is no process or product out there that could support your activities to a higher degree. Why would the evaluation of your picking strategies be any different?
For warehouse managers, any successful picking operation’s priority is to minimize the order selection time and distance your employees are walking. Manually moving products from one place to another is among the least efficient tasks in warehouse operations. Some of the inherent inefficiency caused by travel distance should be accounted for at the design-level, meaning your facility layout and storage configurations should already be optimized to this to some degree. (If it is not, let us know! We can help.) However, there is still work to do to ensure your fulfillment strategy is in sync with your warehouse’s design.
One easy comparison to a warehouse picking strategy is grocery shopping. So, let us examine some of the most common picking strategies, using grocery shopping as an analogy:
Single order picking, also known as discrete picking, involves a picker traveling around all of your aisles and picking a complete order. In the “grocery shopper” scenario, the selector has a full grocery list and then picks items accordingly. It is the most common, most natural, and intuitive. This strategy does not require any technology and is ideal if the warehouse is on the smaller size where order picking is a manual process. The downside to discrete order picking is that it is not typically efficient due to the travel time (unless technology is introduced). The inefficiency becomes more pronounced as order volume or facility size increases.
Multi-order picking is typically an enhanced version of discrete picking. It involves a picker traveling around your all of your aisles and picking multiple complete orders on a single trip. In the “grocery shopper” scenario, the selector has several full grocery lists and then picks items for each list on a single trip through the store. This strategy typically requires a small amount of technology or systems support, but may still be pretty manual. Multi-order picking is more efficient than single discrete order picking, but typically still less efficient than other methods that utilize technology to drive faster throughput & more labor efficiency.
Batch picking occurs when SKUs to fulfill multiple orders are picked simultaneously. This works best when a relatively small #of SKUs account for a large percentage of the picking. The picker takes the order and travels to SKU locations picking items for several (“a batch”) orders, then brings back all items to be sorted to specific orders later. In the grocery shopping example, this would be like one-person shopping for many orders (many of which have oranges on the list). The picker would select all the oranges to fulfill all orders, then also pick the next most popular item on the orders until all of the items needed for that batch of orders have been selected. This style of picking is less-than-ideal if you have a lot of SKUs & the demand for them is fairly evenly spread over a large # of orders. In many situations, this style of picking is matched with zone picking to create a hybrid strategy.
In zone picking operations, you will have a worker assigned to a specific zone and pick all items associated with an order within their area. In the grocery shopping analogy, this would be akin to someone only assigned to pick items when a request comes in for produce, for example. Warehouses employ zone picking strategies because workers don’t have to walk a lot and are very familiar with their assigned area, and it works well for warehouses of any size. However, order accuracy may go down if good systems support is not used because multiple people are touching the order.
Cluster picking allows workers to pick multiple orders at a time, with totes or bins separating each order or batch, depending on which strategy they employ. Essentially, this is a pick-to-cart strategy that allows pickers to make one pass through the pick path, fulfilling multiple orders as they travel through the facility, reducing travel distance per order by grouping orders systematically with like SKUs on them. In the grocery store scenario, this would be like having several baskets within a cart, and the shopper selecting orders for multiple people at the same time& putting each order in its basket.
There are strategies out there that combine various picking styles like Zone/Batch Picking, Zone/Wave Picking, and even Zone/Batch/Wave Picking. Each variation adds a layer of complexity to the methodology, but these options should mostly be considered based on your layout, operations, quantity of SKUs, order profile and volume. However, before evaluating combination strategies, you should speak with an expert in fulfillment to find the right mix based on your specific picking requirements and how quickly they need to be fulfilled.
Which to Choose?
Ultimately, it is up to you and what works best for your business. There may not be just one strategy that best suits your operations. Perhaps the ideal process is a combination of approaches. However, these evaluations are part of a healthy routine to ensure your facility operates at peak efficiency, especially with the industry is changing as rapidly as it is.
If you need help getting started, or even help with evaluating what works for you, give us a call. Our team of experts is ready to talk through any challenges you see and provide solutions through processes or products that we know will work. Let’s get started!