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About the Author

Cliff Holste is Supply Chain Digest's Material Handling Editor. With more than 30 years experience in designing and implementing material handling and order picking systems in distribution, Holste has worked with dozens of large and smaller companies to improve distribution performance.

Logistics News

By Cliff Holste

October 28, 2015



Logistics News: Deploying Flexible & Scalable System Operations Presents Unique Challenges

Efficiently Managing Both High & Low Volume Periods is Key


Holste Says:

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While staffing levels are relatively easy to adjust, system operations may be less flexible.
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Previous Columns by Cliff Holste

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Sorting It Out : The Business Case for Project Planning in Materials Handling Automation

Sorting It Out : Consultant Verses Industry Expert -- Understanding The Difference

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Sorting It Out : Operating a High Performance DC Depends On Smooth, Flat Floors

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Not only are shippers subjected to the ebbs and flows of incoming orders, but they are also subjected to a changing mix of work content for those orders. Some orders may be dominated by full cases or even full pallet loads, while others have a high piece-picking content. Still others may require value-added services such as gift wrapping, serial number capture, and in some cases price ticketing. If ecommerce orders are thrown into the mix, they may be single line and/or single-piece orders. These extreme variations challenge logistics managers to plan processes that are efficient for each, and yet can be scaled up or down based on volume.

Normally, material handling system designers and planners use historical data to establish capacity requirements for each separate process and then design the processes, system flow, and staffing accordingly. If the data is very granular, you can spot extreme peaks in demand. But, planning and staffing each process for its most extreme peak provides considerable excess capacity most of the time, and can be very difficult to cost justify.

An alternative approach is to establish criteria for a theoretical “design day” based on an average day during the peak order processing period (week/month in a better than average sales year) plus a growth factor bump-up. The theoretical design day approach is actually a compromise between planning for peak or average periods which are both wrong most of the time. Using this approach system capacity and staffing levels can be scaled up or down to match daily volume fluctuations.

While staffing levels are relatively easy to adjust, system operations may be less flexible. For example, take into consideration the following:


Be cautious of highly automated processes whose efficiency depends on running at full speed. They may not be so efficient or cost effective when volumes are low, and you still have the capital investment to amortize.

In a mechanized or semi-automated system along with adequate buffering provide a path for continuous flow (re-circulation). This will reduce backups and premature system shutdowns.

Create a mini-DC operation that includes an independent line of flow (like a “slapper” line) for orders and/or customers that have common characteristics. These might include a small sub-set of specific product lines; single lines or single units; the same value added shipping package and/or compliance labeling requirements; or the same carrier. Also, this mini-DC operation may feature workstations for picking and packing as a single-step process.

Consider a separate conveyor line for ecommerce orders to keep the high-volume flow of small cartons from clogging-up the primary system.

Design workstations that have the capability to perform a variety of tasks and locate them so that they are easily accessed from different points in the primary line of flow. These might be configured to support several activities. And cross-train employees so that as the mix of work requirements change, they can be quickly re-deployed.


Final Thoughts

No doubt managing volume fluctuation efficiently is a major challenge. But, you don't have to be victimized by it. By knowing the capacity of each process staffing adjustments can be made so that peaks and valleys can be smoothed-out and operating efficiency maintained.

 

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