A common challenge for shippers, third-party logistics, and retailers in fulfilling orders in distribution centers is the efficiency of pick and pack operations. Pickers can spend up to 60 % of their time just walking from one item location to another.
However, addressing this through expensive approaches like automated systems or warehouse layout modifications is not always the most practical or cost-effective choice.
We want to argue that alternative, efficient, and cost-effective solutions, such as picking optimization, can achieve the same level of efficiency improvements in pick and pack operations.
What Is Pick and Pack
Pick and pack is the process of picking the right number and type of products from warehouse shelves and then packing them for shipment.
Pick and pack is one of the first steps in order fulfillment. In the packing step of pick and pack, items from the order list can be packed in totes, bins, or straight into shipping boxes (pick-to-box) or pallets (pick-to-pallet). In the case of Pick-to-pallet, elements of pick and pack and palletizing are combined.
The Optimization of Pick and Pack
The biggest factor that increases the time of pick and pack is the picking part – the time it takes picker(s) to find and retrieve items from one or multiple orders.
The number of items in an order can range anywhere from 5 to 100. As the number of items per order increases, the margin of error in picking distances also grows.
Picking sequence plays an equally important role. While it may not matter much in certain industries like clothing, where items are packed straight into boxes, it has substantial importance in sectors dealing with goods of different sizes and weights that need to be strategically loaded on pallets, such as beverages.
The picking sequence directly impacts pallet stability. A stable pallet is crucial during pick and pack operations to prevent potential damages and ensure safe transportation & storage of goods.
In a picking tour, lighter boxes may be closer during the start-off point, however, a key practice for pallet stability involves prioritizing heavy items at the bottom and placing lighter ones on top to ensure an evenly distributed weight, reducing the risk of instability.
Without the aid of data-driven decisions, it becomes challenging for any human to analyze and determine the most efficient way to pick items across today's large distribution centers with a wide variety of items and large order volumes.
This is where picking optimization comes in handy, recommending the best and fastest way to pick items for orders.
The Good, The Bad and The Ugly of Pick and Pack
In a warehouse where human intuition guides the picking and packing of orders, efficiency can suffer, resulting in slower and more error-prone order fulfillment.
Specific errors we highlight in the Pick and Pack process include:
- Picking path selection:
- Allowing only gut feeling to dictate picking paths leads to pickers spending 60% of their time walking.
- Disregard for picking sequence leads to:
- Incorrect selection of pallet or box sizes and quantities, resulting in re-stacking items to either a larger container to accommodate all items or a smaller one to avoid excess shipping costs.
- Unstable pallets - heavy items placed atop lighter ones damage products during storage or shipping and result in customer satisfaction at risk.
- Overhanging of items on pallets which creates difficulties for carriers, opening companies up for increased shipping costs and
What It Looks Like
Finding The Solution in Picking Optimization
Picking optimization consists of 2 modules: (1) order clustering which combines orders into a single pick route & (2) pick path optimization which generates the shortest path within that route.
Order Clustering Module
Order clustering in warehousing is designed to boost the efficiency of order fulfillment by having pickers retrieve items from warehouse shelves and racks for multiple orders simultaneously.
However, in conventional warehouse operations, this does not bring too big of an improvement to walking distance reduction due to basic business rules of order item clustering.
With smart order clustering, pick distances can be reduced by 15 to 30% by strategically clustering orders together while considering factors such as item types, location, and order priority.
Additionally, order clustering takes into account the picking sequence of items to be stacked on pallets, factoring in the location of the items in a warehouse, size, weight, and the optimal arrangement of goods on the pallet.
Simple representation of order clustering
Picking Path Optimization Module
Picking path optimization generates 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%.
Simple representation of a picking path optimization
Bottom line
Combining both smart order clustering and picking optimization proves to be a powerful strategy for warehouses which reap benefits such as:
- Decrease in walking distance by 25 – 40 %
- Increase in warehouse productivity by 15 %
- Decrease in labor costs by 5 – 15 %
- Stable pallets
Equip new workers with a tool that will assist them in operating optimally right from the start without the need to overgo weeks of onboarding to learn the ins and outs of picking processes.
Learn more about picking optimization.