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Supply Chain News: Still Many Opportunities to Improve Order Picking Productivity in the DC without Automation

 


Better "Smarts" Can Improve Order Batching, Optimal Pick Paths, More, Lucas Executive Says

Oct. 11, 2016
SCDigest Editorial Staff

Order picking has traditionally been the highest single bucket of distribution center costs, often representing 50% or more of total labor expense.

And that scenario for most companies is getting worse, as order profiles continue to change in ways that increase picking costs, such as more full case and "eaches" picking.

Supply Chain Digest Says...

The 22% reduction is achieved through a combination of what orders to put in a batch for a given picker and how to optimally sequence those picks.


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Efulfillment is certainly a factor here for a growing number of companies, driving part of the increase in the percent of expensive eaches picking, as well as in many cases adding more travel time in order picking, as ecommerce DCS often store more SKUs, requiring more space, than traditional facilities.

So, what are distribution managers to do in the face of these rising picking costs, and therefore in the end higher logistics costs as a percent of a company's sales?

Materials handling automation is certainly one answer - and many companies have gone down this path. But such systems don't come cheap, often in the many millions of dollars, an investment level many companies can't or do not want to pursue. Other companies have concerns about system flexibility over time.

So what then is an answer?

It turns out, there are in fact a number of options for software and other technology-based systems that can have a significant impact on picking productivity – at a fraction of the investment in automated materials handling.

That was the theme of a recent Videocast on our Supply Chain Television Channel, featuring Ron Kubera, EVP and chief marketing officer at Lucas Systems, provider of distribution center technologies, with a special focus on order picking solutions. You can watch this excellent Videocast on-demand, or download a copy of the slide materials, at the link here: Videocast: Reducing Order Picking Costs in the DC without Automation.

One alternative is to move to Voice technology for order picking, an increasingly popular approach that delivers productivity gains from its hands- and eyes-free attributes. Those gains can be substantial, often in the double digit range. However, Kubera said the real opportunity is to not just Voice-enable an existing order picking process, but to use software tools to re-engineer the current process, rather than just replicate existing RF screen flows with Voice, in a way that usually provides substantial additional productivity improvements.

That led to a discussion between SCDigest Editor Dan Gilmore and Kubera on what Lucas calls "Mobile Work Execution," sort of a missing link between what most traditional Warehouse Management Systems (WMS) do and significant materials handling automation.

Gilmore noted that many existing WMS providers built their order picking capabilities quite a few years ago, and often have not really improved those capabilities in recent years, as the R&D investments went into areas often outside of four-wall DC processes.

But there is a real opportunity to optimize that Mobile Work Execution, Kubera says, with a big impact on ordering picking costs, by intelligently managing the full mobile order picking activity in real-time to take advantage of consolidation and other techniques to reduce travel time and make each order picker as efficient as possible.

Lucas likes to think of this in terms of "Dynamic Work Optimization," which Kubera said involves advanced mathematical techniques that go far beyond what most WMS systems can do in this area.

Key to that in turn is optimizing batches of work so that travel time in order picking is minimize while adhering to other constrains, such as order priority.

Kubera walked through an example, showing how typical order batching in a piece picking scenario might just grab the first six orders in a pool to assign to a given order picker. In this example, the total travel distance to pick these six orders is 176 feet, as shown below.

 

Batch Optimization Example: Typical Order Picking Grouping

 

 

But, Kubera noted, this approach misses many opportunities. There may be a pick in the overall pool, for example, that is in nearly the same location as say the first pick, resulting in a travel distance of zero. Batching these picks together obviously make great operational sense -but to do so across a large pool of orders requires some advanced system intelligence.

(See More Below)

CATEGORY SPONSOR: SOFTEON

 

Playing out his example, Kubera showed how a pool of six orders for the first order picker could require just 138 feet of travel distance, a 22% reduction in travel time versus the original batch that required 176 feet of travel, as shown below in another slide from the Videocast. This reduction is achieved through a combination of what orders to put in a batch for a given picker and how to optimally sequence those picks.

 

Travel Distance Reduced 22% with Dynamic Work Optimization

 

 

All these years later, Kubera said there are also still major opportunities to improve pick path sequencing in the DC to further reduce travel time and order picking costs. He played a short video, seen below (no audio) to illustrate how sophisticated such pick path optimization can be.

 

Pick Path Optimization can  be Quite Sophisticated

 

 

Later in the broadcast, Kubera said he is very bullish on the growing use of smart phones as mobile terminal and Voice units in the DC, versus traditional RF and Voice devices, and also sees great promise in the use of smart glasses to visually show pick and put locations and the optimal pick path, which also can lead to significant productivity gains.

There is a lot more in this great broadcast. Again, you can view the on-demand Videocast, download the slides, or listen to a podcast of the excellent QA session here.

Do you see opportunities to reduce order picking costs through better batch optimization or improved pick paths? Are you bullish on smart phones or smart glasses in the DC? Let us know your thoughts at the Feedback section below or the link above to send an email.

 

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