Distance + Prioritization + Pick Venue = Location:
Optimizing the pick area for shipping operations
By Howard Klein
It’s not as frightening as it seems… read on…
Shipping and distribution are essential to any company’s profitability. Efficiencies gained in these areas can reduce costs, speed products to market and increase customer satisfaction. Unfortunately, because shipping is often viewed as a non-value added activity, the analysis of what happens (or doesn’t happen) to select, pack and transport goods often gets short shrift during a company’s lean improvement initiatives.
Over the past few years we’ve helped improve shipping operations, electronics companies, and restaurant supply distributors. One element that’s essential to improve each of these diverse businesses? Location, location, location. However, I’m not talking about the address of the facility, but the challenge of where to place the products that will be shipped within its walls.
Reducing the number of feet or yards that shipping personnel travel within a facility to select items for fulfillment is one key method to achieving improvements. How do we do this?
Compress the distance:
First, we determine the items we select most. This is commonly referred to as a Hits analysis. This is different from an ABC, or sales velocity, analysis.
Why is this important? If we sell 1,000 units of an item, it would receive a certain ABC designation. But that item might have been ordered by 1,000 different customers, or there may have been one order for all 1,000 units. The answer will result in a different placement of that item or items within the pick area: one in a high usage area, the other in a lower usage area. The ideal location is somewhere between these two extremes. The trick is to determine where.
Prioritize your effort:
One of our clients had over 30,000 SKUs. A maintenance support client had over 10,000 SKUs. A consumer electronics client had over 8,000 SKUs. What if your organization could more effectively ship to a majority of its customers with more effective placement of a much smaller number of SKUs? Choosing the most frequently selected (and thus, should be most easy to access) items can seem a daunting task.
Pareto’s Law suggests that 20 percent of items, the “A” items, make up 80 percent of sales. This approach can also be used to analyze customer rankings, costs, revenues, activity levels and many other applications.
Pareto, however, should not be followed blindly. Here is one example of how we abandoned Pareto’s Law for a more pragmatic Pareto’s Guideline.
One client had 30,000 SKUs and they considered 10,000 to be “A” items because that number made up 80 percent of sales. Imagine if you had 30,000 SKUs! Trying to reorganize even 10,000 SKUs posed a daunting task, especially while the client was trying to maintain excellent customer service levels during the transition. We found that the top five percent were picked once a day or more. We asked the client “What if we could reduce pick activity by 50 percent by focusing on only five percent of the SKUs? Because 1,500 SKUs is a lot more manageable than 10,000, this sounded like a more reasonable approach.
Select the picking venue:
Once you have selected the SKUs to focus on, the next task is to determine the picking venue. Should it be bulk storage? Pallet rack? Decked racking? Static shelving? Flow racks? Carousels? The best solution is probably a combination of these access solutions.
Part of the Hits analysis is the physical volume of the product movement. Some items may be physically large. Others may be small. Some may be sold only as full cases, others may be sold as individual pieces, and still others may be sold both ways.
One method of determining the physical size and type of pick venue is to decide the method and frequency of replenishment for these key pick locations. The less frequently you replenish, the larger each pick location must be.
You may consider picking from pallets, either in pallet racks or from bulk floor locations for your largest physical volume sellers, and static shelving or decked rack for the smallest physical volume sellers. Flow rack is best used for higher volume sales of individual pieces. Carousels require sophisticated software to function efficiently.
Once you have employed the above approach to determine how many and which SKUs to focus on, and have determined the most applicable pick venue, you can determine where to place this concentrated operation within your facility.
Numerous factors impact this decision. Is this for a new facility? If yes, the process of determining pick venue will be much easier than trying to retrofit an existing operation.
Of course, any potential changes to existing shipping operations must weigh costs of implementation with cost and efficiency benefits. Each company has its own guidelines for this decision making process.
The results each company achieves in re-tooling their shipping operations will depend on their baseline efficiency levels and the trade-offs I’ve discussed above. When retrofitting its operation, our maintenance support client saved an additional full-time equivalent person above our conservative estimates. The distributor of restaurant supplies reduced travel within the facility by 40 percent for the fastest moving SKUs. The packing and shipping layout we designed for our consumer electronics clients in their new facilities supported their aggressive five-year growth plans.
About the Author:
Howard Klein has more than 35 years of management and design experience in distribution center and manufacturing floor installation and operations, including startups, re-engineering existing space and multi-site build-outs. Howard helps clients streamline their processes and reduce cycle times, design and install highly efficient work environments, turn around underperforming operations and teams, align operational goals with business strategies, and develop and install new warehouse management systems to improve logistics.
Mr. Klein received a Masters’ degree in industrial engineering from New York University, and a Bachelor’s degree in industrial engineering from The Pennsylvania State University.