Wholesalers and retailers have trended away from large distribution centers, moving instead to leaner drop-ship operations. To achieve this nimble speed to market, suppliers have been forced to use small package carriers as opposed to LTL or FTL carriers. Drop-shipping has allowed suppliers to move product with added speed; however, racing the product directly to its final destination has come at a cost.
There must be a way to drive down cost with the same flexibility as drop-shipping.
In the break bulk arena, NVOCCs and forwarders have examined and optimized the placement of cartons in containers. What if this same technology was applied at the parcel level? We discovered that a similar application rolled out at the parcel level would yield the same proven results as ‘tried and true’ carton-container optimization. Packaging optimization is an essential technology that must be tapped in order to reduce costs in the burgeoning drop-ship market.
Small package carriers charge customers a per-package rate based on the carton weight and the distance between origin and destination. The cost of shipping per-pound is proportionately more expensive for lower weights and decreases significantly with weight increase.
Savvy shippers have taken advantage of these lower rates and have started packing larger quantities into cartons. In addition to reducing shipping costs, parcel consolidation also helps to reduce the number of charge-backs. No retailer likes to receive a deluge of small parcels – it is extremely labor intensive to unpack and shelve the items. It is simply more efficient to receive larger consolidated items.
It’s All in the Details
The consolidated cartons must stay within the dimensional weight range determined by the small package carrier. If all the smaller packages could be placed into larger containers and stay within the defined dimensional weight, they could also take advantage of volume discounts.
Dimensional weight is simply the length x width x height. If the total is less than 5184 cubic inches, the resulting charge is based on the actual weight of the carton. If the total is over 5184 cubic inches, the shipment is then assessed the dimensional weight based upon a negotiated dimensional factor (currently a factor of 166). For example, if a carton is 24” x 18” x 11” and weighs 20 lbs, the total is 4,752 cubic inches. This carton would be shipped at a 20 lbs rate. If the carton is 24” x 18” x 13” and weighs 20 lbs, the total is 5,616 cubic inches. Based upon dimensional weight, that same package would be shipped at a 29 lbs rate— an increase of 31% in the shipping rate when compared to the actual weight of the carton.
This calculation-heavy process is clearly an ideal scenario for technology to step in. The resulting process is called Packaging Optimization.
A Game of Tetris
In order to achieve effective cost savings, the contents should be effectively arranged within the parcel to fit into a smallest size carton. Workers were under pressure to place as many cartons into an overpack as possible. However, we found that productivity slowed tremendously as they tried to determine the best way to pack cartons together in a master carton. On average, master cartons were only 60% full. Far too much air was being shipped.
Through a series of complex algorithms, we were able to engineer an effective software solution that determines the most efficient way to load a package.
The process is very much like a three-dimensional game of Tetris– simply tell the program what products should be shipped and the software generates a guide explaining where the ‘pieces’ should go. In this analogy, the ‘guide’ is the automatically generated pick-tickets. Workers place the items into the overpack as instructed.
Naturally following, since the workers have a visual road map to steer them, accuracy is also significantly increased. The goods simply would not fit into the overpack if an incorrect SKU was selected from inventory, and the technology would not allow the worker to move on to the next step until the correct bar-code was scanned. With the Packaging Optimization process in place, order accuracy was increased to 99.9%. In addition, the labor required to assemble the packages was also optimized by nearly 150%. In order to further drive down cost, the application also ensures that the consolidated rate is less than the cost of the individual shipment.
Conclusions
Consolidated parcels can be shipped at a significant discount– up to a 40% savings in shipping cost. This adds up to major savings when multiplied repeatedly across the entire supply chain.
The competitive advantage is clear. In an industry where each cumulative discount directly correlates to the bottom-line, such cost-saving measures are essential to come out on top.
Tom Zinner is Director of Supply Chain Software at transportation software provider, IES, Ltd.
There must be a way to drive down cost with the same flexibility as drop-shipping.
In the break bulk arena, NVOCCs and forwarders have examined and optimized the placement of cartons in containers. What if this same technology was applied at the parcel level? We discovered that a similar application rolled out at the parcel level would yield the same proven results as ‘tried and true’ carton-container optimization. Packaging optimization is an essential technology that must be tapped in order to reduce costs in the burgeoning drop-ship market.
Small package carriers charge customers a per-package rate based on the carton weight and the distance between origin and destination. The cost of shipping per-pound is proportionately more expensive for lower weights and decreases significantly with weight increase.
Savvy shippers have taken advantage of these lower rates and have started packing larger quantities into cartons. In addition to reducing shipping costs, parcel consolidation also helps to reduce the number of charge-backs. No retailer likes to receive a deluge of small parcels – it is extremely labor intensive to unpack and shelve the items. It is simply more efficient to receive larger consolidated items.
It’s All in the Details
The consolidated cartons must stay within the dimensional weight range determined by the small package carrier. If all the smaller packages could be placed into larger containers and stay within the defined dimensional weight, they could also take advantage of volume discounts.
Dimensional weight is simply the length x width x height. If the total is less than 5184 cubic inches, the resulting charge is based on the actual weight of the carton. If the total is over 5184 cubic inches, the shipment is then assessed the dimensional weight based upon a negotiated dimensional factor (currently a factor of 166). For example, if a carton is 24” x 18” x 11” and weighs 20 lbs, the total is 4,752 cubic inches. This carton would be shipped at a 20 lbs rate. If the carton is 24” x 18” x 13” and weighs 20 lbs, the total is 5,616 cubic inches. Based upon dimensional weight, that same package would be shipped at a 29 lbs rate— an increase of 31% in the shipping rate when compared to the actual weight of the carton.
This calculation-heavy process is clearly an ideal scenario for technology to step in. The resulting process is called Packaging Optimization.
A Game of Tetris
In order to achieve effective cost savings, the contents should be effectively arranged within the parcel to fit into a smallest size carton. Workers were under pressure to place as many cartons into an overpack as possible. However, we found that productivity slowed tremendously as they tried to determine the best way to pack cartons together in a master carton. On average, master cartons were only 60% full. Far too much air was being shipped.
Through a series of complex algorithms, we were able to engineer an effective software solution that determines the most efficient way to load a package.
The process is very much like a three-dimensional game of Tetris– simply tell the program what products should be shipped and the software generates a guide explaining where the ‘pieces’ should go. In this analogy, the ‘guide’ is the automatically generated pick-tickets. Workers place the items into the overpack as instructed.
Naturally following, since the workers have a visual road map to steer them, accuracy is also significantly increased. The goods simply would not fit into the overpack if an incorrect SKU was selected from inventory, and the technology would not allow the worker to move on to the next step until the correct bar-code was scanned. With the Packaging Optimization process in place, order accuracy was increased to 99.9%. In addition, the labor required to assemble the packages was also optimized by nearly 150%. In order to further drive down cost, the application also ensures that the consolidated rate is less than the cost of the individual shipment.
Conclusions
Consolidated parcels can be shipped at a significant discount– up to a 40% savings in shipping cost. This adds up to major savings when multiplied repeatedly across the entire supply chain.
The competitive advantage is clear. In an industry where each cumulative discount directly correlates to the bottom-line, such cost-saving measures are essential to come out on top.
Tom Zinner is Director of Supply Chain Software at transportation software provider, IES, Ltd.
