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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

August 12, 2015

Logistics News: Understanding Multi-Channel Order Processing Challenges

Can Different Order Picking Models Co-exist in the Same Operation?

Holste Says:

Mixing order processes models within the same system operation is a risky business.
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Previous Columns by Cliff Holste

Sorting It Out: Shippers Looking To Increase System Capacity Are Surprised To Find It May Already Exist!

Sorting It Out: For Shippers - Benefits Of Real-Time Control In The DC Are Huge!

Sorting It Out: Shippers Looking to Improve Operations Choose Customer Centric Approach

Sorting It Out: Productivity is a Crucial Factor in Measuring Production Performance

Sorting It Out: Packaging Construction Impacts on Logistics Operations


The challenge logistics companies face when adopting new marketing channels, especially those that require quick response capabilities (same day shipping), is supporting vastly different customer order profiles and shipping schedules within the same order fulfillment system. This can be especially challenging if the original system planning did not take multi-channel order fulfillment into consideration.

Retail Order Picking & Sorting Model

In this model, SKU quantities are summarized across a batch of orders. Then, individual pickers pick a portion of each order containing those SKUs. This batch picking model greatly increases the rate and productivity of individual pickers. Picked product is transported via a network of conveyors to an automated sorting and order consolidation system. There are of course, dozens of “rules” involved governing how batches are constructed. But, having a sufficient amount of customer orders in advance is the key to constructing efficient and productive batch sizes.

This model is most efficient and productive when the average customer order includes medium to large quantities of mixed SKUs, and the shipping schedule allows sufficient time for the Warehouse Management System (WMS) to accumulate and construct several large batches of orders prior to releasing them to the picking system.

Direct to Consumer E-Commerce Model

Although encompassing many of the same SKUs, the e-commerce model is very different from the above. To start with the frequency of customer orders tends to be very high while the individual orders are characteristically small and shipping is required within 24 hrs or less of receipt of order. Another difference is that because these orders are typically for one or two line items, they are more suited to discrete order picking methods. Therefore, as individual e-commerce orders are received in the DC they are immediately processed by the WMS and released to picking on a continuous basis.

Processing Batch & Discrete Picking Models in the Same DC

One solution is to setup two separate order picking systems, batch and discrete, both driven by the same WMS. In the discrete order picking model, incoming e-commerce orders are allowed to accumulate in the WMS for a short period of time (say 15 to 30minutes) prior to being released in small clusters to individual pickers using RF equipped pick carts. Then, based on order profiles and SKU characteristics, automated picking machines such as an A-frame, and/or Goods-to-Person equipment such as horizontal carousel, vertical lift module (VLM), mini-load AS/RS, can be deployed in conjunction with a pick-and-pass system configuration that feeds completed orders directly into order verification, packing, and shipping.

Optimum Facility Considerations for E-Commerce Operations:

The above describes how both types of order fulfillment operations can share the same facility, business management and IT support systems while their physical orders are processed within distinctly different systems. Another approach is to segregate e-commerce operations into separate facilities. This approach allows for the deployment of smaller DCs that are strategically located to reduce shipping cost and time. Due to the abundance of small to medium spec buildings currently available on the market, this may be an attractive option. The following lists a few desirable e-commerce building characteristics to look for:

More building depth with the first interior row of columns set back 60 to 70 feet will greatly improve fork truck traffic on the dock. Column spacing greater than the normal 40 x 40 grid is most desirable. Clear height may not be as critical, as inventory is primarily held in pick locations that are accessed manually. This makes existing buildings with low to moderate ceiling heights viable alternatives.


The building should be equipped with a roof truss supported Early Suppression Fast Response (ESFR) fire sprinkler system. This type of system allows maximum equipment layout flexibility because storage and picking systems can be configured and re-configured independent of the sprinkler system.


Sufficient floor or mezzanine space to allow easy access to pick locations and to accommodate horizontal carousels, pick-&-pass systems, or AGVs.


Look for high flow-through capability – receiving docks on wall opposite from shipping docks. This arrangement facilitates the high inventory turnover rate and short product life cycle associated with e-commerce marketing. Reserve inventory needs be stored close to active pick locations.


Adequate facility power with back-up generators to provide uninterrupted operations during critical shipping days.


Temperature control - not just for product sensitivity, but to keep workers comfortable and productive in a fast-pace environment. Air conditioning in the workplace is expected and required in some locations within the U.S.

Final Thoughts

When considering new or additional marketing channels, first understand how it will impact on the current operation. Mixing order processes models within the same system operation is a risky business. The result could be to dilute the output of the entire operation, leading to a result that may not satisfy overall company objectives.



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