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Order picking is one of the biggest opportunity areas to quickly gain efficiencies and increase throughput in a warehouse environment. This category of automation technology addresses ways to increase picking capacity, decreasing time spent walking and locating units, and providing reliable and repeatable retrieval of goods.

The fastest and most flexible pick order solutions must be implemented by retailers and third-party logistics (3PL) operators. This is traditionally done by workers walking to each pick location to execute tasks and deliver items to their next workstation. However, this approach lacks key insights into performance and where optimizations can take place. Without access to this data, retailers, and 3PL operators can't fully grasp two of the most important parts of picking workflows - speed and accuracy. A mis-picked unit has varying degrees of cost, but picking accuracy is an important factor in guaranteeing a consistent throughput.

There are generally two methods to order picking; batch order picking and discrete order picking. The batch approach is where orders are separated into individual items, so the same item can be picked one time to fulfill multiple orders, and then later sorted to its proper order container for shipping. Discrete order picking is where orders are maintained, and all items within one order are picked in succession, often directly into the final shipping container.

There are many technological approaches to tackling order picking to increase speed and accuracy. A few prime examples are mobile robotic picking, vision picking, voice picking, and goods-to-person (GTP).

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