The growth of e-commerce has been meteoric, and the trend lines keep pointing up. Forrester Research is forecasting that by 2018 total e-commerce sales will approach $415 billion. That means in just three years more than 11% of all expected retail sales will happen online and then need to be shipped.
That's a problem for a shipping industry still trying to figure out how to handle the amount of parcels it's already seeing. Specifically, companies are trying to figure out how to get those parcels in and out of a distribution center both efficiently and cost effectively.
Some of these companies are turning toward automation to solve the problem, and it's a smart move. On its own, automation can provide several advantages, one of those being the ability to track the travel path of a package throughout the delivery process, something customers are increasingly demanding.
Using Data to Identify Efficiencies
Automation provides these companies with more than the ability to track packages. It's also giving shipping providers the ability to use their piece tracking system architecture to increase handling efficiencies. For example, in the United States, many companies, including heavyweights FedEx, DHL and UPS, have divisions that provide parcel delivery services that utilize the United States Postal Service (USPS) for the final mile of delivery via work share discount programs. These work share programs not only offer a potentially less expensive product delivery alternative for the parcel delivery companies, but also, by utilizing final mile delivery vehicles already on the roads, they provide the additional green benefit of a reduced carbon footprint. By using the data already required for the manifesting process, those companies can optimize the parcel sorting process to increase efficiencies and lower handling costs.
Traditionally, companies have relied on historical data to create static sort plans that they then use for months at a time to manually sort parcels. They weren't using dynamic data to make sorting decisions; instead, there were human readable sort indicators on the labels applied to parcels. That required manual sorting into logical containers for finalized sorting based on a best guess of what the optimized sort levels may be.
For example, if a parcel needed to be sorted to one of, let's say, 1,600 potential destinations, it would first be sorted into one of 40 initial bins. After the initial sort, each of the parcels in those bins gets manually scanned and sorted into a second set of 40 individual bins or bags until the 1,600 (40 x 40) logical destinations are finalized. It's an inefficient process, but that's how many companies are still doing it today.
Knowledge derived through the years in the high-speed letter-sorting marketplace is now being implemented to increase efficiencies in the historically manual parcel sorting market. While many parcel sorting companies are benefiting from the advantage of the work share discounts offered by the USPS, they aren't dynamically optimizing the level of savings via the combination of looking at both the presort or available logistics discounts because they either don't have the data or don't use it to do a dynamically optimized level of sort.
Data can help target the optimal sort/drop level
In the USPS work share programs, two types of discounts are offered, Presort and Logistics.
Presort relates to sorting parcels to logical containers and offers various discounts based on the value of internal work reductions by the USPS. For example, sorting to a mixed group (multiple ZIP Codes) offers the lowest discount, while sorting to a 3-digit sort level group (360 for example) offers additional discounts, and a 5-digit sort level group (36015 for example) offers the highest presort discount allowed.
Logistics discounts relate to shipping, or "dropping," to a USPS facility. The closer the facility is to its final delivery point, the higher the discount afforded. Dropping to a network distribution center (NDC) will earn one level of discount for the shipping company. Dropping to a sectional facility center (SFC) will earn even greater discounts. And dropping to a destination delivery unit (DDU), or the local post office that will deliver the parcel, will earn the largest discounts.
The key to optimizing profit when using the USPS for the final mile is to presort to the highest level and drop those packages as deep into the delivery process as possible, while taking into consideration sorting and logistics costs. This process will require algorithms in order to expeditiously generate the most financially optimal sort plans with the least amount of human intervention.
Sorting to that level requires two things: at minimum, a semi-automated sorting process that can scan parcels for tracking and manifesting purposes and then software that can analyze that data before creating sorting plans.
By automating the process and then using the available data, companies may find out that despite historical data that says they don't have enough packages that go to specific ZIP Codes, they may have enough on an individual day to create a drop group to that post code level to provide additional presort discounts. They may also find that a new destination needs to be added due to additional volume for a particular postal facility or possibly move certain parcels to a less discounted facility due to the additional logistics discounts not covering the cost to ship. By combining the historical manual sort with automation selecting certain pieces via pre-planning, a "hybrid" solution most often will provide additional profits.
The Future of Data in Logistics
It's important that shipping providers start to get more comfortable using data and putting it to work, because the amount of data available will only increase in the coming years as the Internet of Things starts to connect everything from refrigerators to shipping containers to the Internet. Leading shippers are predicting that this will have a significant impact on the logistics industry.
Various vendors provide automation and sort optimization software products and support. That software can be used to cover the numerous delivery products for the USPS or private delivery market at a price model that should be considered versus creating in-house custom solutions, especially when taking into account the cost to build and, more importantly, maintain with the ever-changing parcel delivery marketplace.
James Curgus is Chief Financial Officer for NPI — Fort Worth, Texas.
