Labor is the single largest operating cost in most DCs, and travel often accounts for half of all labor time, especially in order picking. In some DCs, pickers can travel upwards of 12 miles per shift. In order to reduce travel, some warehouses utilize batch picking. (Read about other strategies for reducing travel – including slotting and robotics – in this white paper…)
Batch picking is an alternative to discrete order picking. In discrete order picking, workers pick each order individually on a trip through a DC or zone. By picking multiple orders simultaneously on a single pass through the zone, travel is slashed and productivity climbs.
Traditional batch picking follow static (FIFO) rules that batch orders as they are imported and disregards travel patterns, pick locations, order priorities etc. which minimizes travel reductions with batching. In contrast, Intelligent Batching with Lucas Dynamic Work Optimization (DWO) evaluates millions of potential combinations to determine the “best batch” or grouping of work among the available orders while taking into account order priority, pick location, travel cost, product attributes, and other factors.
What is Batch Picking?
Batch picking (which is also referred to as cluster picking) is a strategy for work execution in which workers pick multiple orders on each trip through a distribution center or zone within the DC. So, rather than making two discrete trips through a DC to pick two orders, a single picker can pick a batch of two orders on one trip, cutting travel in half.
Batch Picking Benefits
Batching allows for pickers to slash travel. If 16 orders are batched together, a picker will be able to pass through the pick zone once as opposed to 16 times, dramatically increasing productivity.
Higher productivity reduces costs, and has additional benefits for workers. In addition to reduced fatigue, batching can reduce crowding within a pick area, since you need fewer workers to pick the same volume of orders.
Traditional Batching From Warehouse Management Systems
Traditional pick paths will send a picker through a serpentine pick path to pick up all the items for each order. Batching with a warehouse management system will follow a FIFO sequence (order 1 will be batched with order 2, etc.) without taking travel distance or other factors into account.
Unfortunately, this method, with an attempt to reduce travel distance for pickers, isn’t as effective as one would hope. In order to effectively reduce travel, batching orders will need to take into account product locations, starting and ending points and the potential travel path. Below are a few illustrations to show the difference between traditional batching and intelligent batching with Lucas.
Traditional FIFO Batching
In the above illustration, the warehouse management system batches together orders 1 & 2 (FIFO). This solution offers very little travel savings.
Intelligent Batching With Lucas DWO
Lucas Dynamic Work Optimization (DWO) uses advanced mathematical models and artificial intelligence (AI) to eliminate warehouse travel. Customers using DWO have more than doubled picking productivity and cut labor hours in half without making any changes to their warehouse layout or adding expensive automation or robotics.
DWO weights a number of factors in addition to travel and applies Lucas algorithms to determine which orders and items should be grouped together in a batch. The Lucas tool considers the following factors, which can be weighted differently in different operations:
- Order priority
- Product locations
- Product dimensions
- Starting and ending points
- Potential travel path
- User Permission
Intelligent Batching With Lucas
Interested In Learning More?
Lucas Dynamic Work Optimization takes into account more than just batching orders together. DWO helps optimize picker paths so they are taking the most optimized route throughout the warehouse. This module of Lucas Engage has reduced travel 30-70% and has led to greater than a 120% increase in lines picked per hour.
Watch this short animation below to learn more about Dynamic Work Optimization and don’t hesitate to reach out if you’d like to schedule a demo.