Using Location Intelligence to Solve the Container and Chassis Problem
5/15/23
Companies that provide logistics services to the supply chain have a business model of converting productive assets into revenue. Those assets include a wide range of equipment that moves- like ships, trucks, containers and chassis - and static assets- like warehouses, yards and cranes. One item that enables the utilization of all these assets is the application of labor. Labor requires training and tools to make the most efficient use of those assets. In the world of logistics, the application of technology to enhance utilization of these assets has not kept up with current capabilities, particularly in the area of location intelligence and in the sharing of data across supply chain service providers.
Two groups that could see great benefits through the application of location intelligence are the owners of containers and the owners of chassis. Knowing the location of these assets and having the ability to reposition them to where the demand is, helps to maximize utilization, enabling the conversion of these assets into revenue-generating activities.
Chassis
In the case of chassis, having a platform that uses location-based sensors to geolocate (determine the geographic location of) their position provides the following advantages:
1. Optimized Chassis Positioning: Position chassis to a place of demand to ensure higher levels of utilization and revenue-generating activities. For example, moving the asset from one ocean terminal to another.
2. Possession Visibility for Maximum Revenue: Determine who is in possession of the chassis for more accurate billing, enhancing the ability to collect usage fees.
3. Loss Prevention: Help avoid lost chassis, thereby reducing the cost of replacement for ones that go missing.
4. Asset Management: Giving the customer the ability, in the case of a long-term chassis lessee, to manage their fleet of chassis more effectively through matching a truck to the real-time location of the chassis under lease, thereby increasing utilization.
As indicated in the chart below, the effective chassis utilization rate is 70% in the Pool of Pools at the Port of Los Angeles / Long Beach. That simply translates into an asset that is not “productive” or “revenue generating” 30% of the time. This is an obvious use case for location intelligence, integrated with demand data, that would allow owners to position those assets to increase utilization and return on investment. A great example of using integrated datasets to aid in asset utilization is the airline industry. Today airline passengers rarely have an empty seat next to them. That is the result of effectively using integrated data sets to maximize utilization of what, in that case, is a seat on an airplane.
Containers
The movement of a chassis, typically between ports and warehouses, is a much more limited movement than containers. Containers can move from factories anywhere in the world. They are transported to ocean terminals by trucks/rail, loaded onto ships, and at the destination, are offloaded back onto trucks/rail to transport to the warehouse. This flow is a two-way movement; those same containers need to be loaded with goods to be exported or as empty containers and sent back through the process supply chain to factory. Any disruption in the flow of these containers can result in an imbalance that can freeze up the system. If there are not enough containers at the factory because they are stuck at a terminal or warehouse, goods stop moving.
Today less than 1.0% of containers have an intelligent brain. A container is considered to have a brain when it is outfitted with a GPS sensor, along with other sensors that monitor temperature, pressure, shock/sudden movement, and door tampering. There are many reasons why using sensor technology, providing the container with a “brain”, is important to shipping companies and to the owner of goods. Some of the reasons include the following:
ESP Container Security Screen
1. Reduction in Theft: Concealed shrinkage occurs when the number of transported goods at the destination is less than expected from the factory; in many cases, this is caused by theft from the shipping container during transit. Putting a sensor on a container door that alerts security when someone is attempting to steal goods is a high-value proposition for cargo carriers because it prevents profit losses from having to pay the cargo owner for the missing goods.
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2. Monitoring of Perishable Goods: Certain goods, like food or medications, need to be temperature controlled or may be shock sensitive. Having sensors on the containers that measure those characteristics and alert/report any events that go outside an acceptable range is a valuable tool to monitor and react (take corrective action) before there is a loss of goods.
3. Maintaining the Flow of Containers: Having GPS sensors on containers enables the geolocation of those assets, which provides for the efficient positioning and scheduling of labor to offload at the destination warehouse. It also allows the identification of empties for loading onto ships for sailing back to Asia, for example. Keeping a balance of container flow to and from factory to cargo owner is very important to maintain the overall flow of goods.
4. Giving Cargo Owner Visibility and Arrival Predictions: When cargo owners develop their merchandising plan, they set out the in-store/online dates when they need products to be available to meet their sales plans. When there is uncertainty about whether the goods will be available, that causes obvious issues. Being able to predict arrival is critically important, particularly for seasonal businesses that have time-sensitive materials (e.g., “back to school” goods). Location intelligence and prediction using GPS sensors help to ensure these businesses can continue to meet customer demand and maximize the sell-thru of goods at the point of sale.
5. Alerting of Unscheduled Offboarding and Onboarding: Without the use of geolocation on containers, owners of goods have little understanding if a container finalized the journey as intended. This presents a challenge with containers accidentally being offloaded at an unscheduled port without the knowledge of the cargo owner. When this occurs, the risk of the container being tampered with increases dramatically. By combining the geolocational data along with modern geospatial functionality, technology can monitor and alert on containers that have been offloaded unexpectedly or tampered with, saving millions in lost revenue and even minimizing the risk of contraband being loaded into the container.
In conclusion, applying location intelligence through technology has the potential for a vast array of benefits within the supply chain space- from higher asset utilization and ROI, and better labor productivity to less air pollution, to name a few. In addition, it provides an alternative to building or buying more costly infrastructure to meet business demands to get a 15-20% higher yield and, therefore, capacity out of existing infrastructure assets.
AUTHOR
Dan Pimentel, President & Chief Financial Officer
Dan is the Co-Founder of ESP Logistics Technology and Managing Director / CFO of Saybrook, a Private Equity firm that invests in logistics and supply chain assets. Dan’s experience includes 10 years of supply chain logistics strategic and operational planning and global ERP systems implementation.
About ESP
ESP was created by combining over 20 years of supply chain and logistics expertise with technologists that have focused on the science of location and location analytics, the practice of layering geographic data along with business data to extract valuable insights. The advantage that our customers have with ESP is the ability to access and capitalize on a continuously growing infrastructure that enables more focused location-based analytics, helping the supply chain become smarter. ESP has designed a Space and Time Network which enables data (real-time, historic and near real-time) to be consumed, analyzed, viewed, and translated into action. Critical to our customers’ success, our network enables the analyzation of data sets that are beyond typical supply chain data, resulting in more accurate and actionable information.