CLMs vs. GPS: Finding the Best Solution for Rail Shipment Visibility

There has been recent buzz in the rail industry regarding shipment visibility, Car Location Messages (CLMs), and the deployment of GPS. While GPS has garnered deserved excitement, many misperceptions persist concerning the robustness of the network of scanners providing CLM updates. Let’s look at what both CLMs and GPS provide in tracing a shipment, their respective strengths and weaknesses, and what might represent the best present solution for effective tracing of your shipments.

A CLM is derived from a reported rail event that happens at an Automated Equipment Identification (AEI) scanner or is entered by a rail crew or clerk. The CLM provides the data that says this car or container received this event type, at this place (defined by a SPLC - Standard Point Location Code), at this time, on this railroad with this loaded or empty status. A CLM is created by adding additional information to the event such as the location name, the event code description, the waybill destination, the bill of lading number, or any number of other elements to provide valuable information to the reported event.

Event

CLM

Equipment number/Car ID Everything an event provides, plus other context such as:
Event type Location name
SPLC Event code description
Time of Event Waybill destination
Reporting Railroad Bill of lading number
  and more
Comparison of Key Data Provided by CLMs vs. Individual Rail Events.

 

The number of CLMs/events generated and received is entirely a function of which railroad is reporting and how many scanners exist along the railcar’s route. There is a common and quoted misconception that, on average, customers only receive a CLM every two-and-a-half days. Railinc data, however, shows that the industry average (including all shortlines) is six reported events per day. For the western Class Is, a customer would receive an update every hour approximately 75% of the time while their shipment is moving. In the majority of trips, there are several CLMs generated per day.

More importantly, by their nature, CLMs represent what has happened to the equipment. They tell a story about the shipment up to that point in time, as soon as the CLMs are reported. CLMs provide excellent context, but no information as to what is currently happening and if the car is still moving.

GPS technology has now been around for years in other industries and has been a game-changer in everything from how we drive our cars to providing live movement information about when our pizza will arrive. In rail transportation, GPS also provides excellent telematics (temperature, excessive force, etc.) on the equipment as well as live information on when, where, and how fast the equipment is moving.

From an equipment tracing point of view, a GPS “ping” by itself is a point in space. When the point in space is moving, it provides up-to-date information about the location and speed of the shipment. It can also provide information around when the asset has entered a geo-fence established around geographic locations (such as a customer rail yard, an intermodal facility, or a portion of either).

But what happens when the point in space stops moving? What’s happening with the equipment? GPS cannot provide context on whether the equipment, for example:

  • has arrived at an in-transit yard (starting its dwell time),
  • has been bad ordered for a mechanical reason,
  • has been held for some reason,
  • has been constructively placed near its final destination, or
  • has been actually placed at its final destination.

With only GPS, there is no context provided around what might have happened to the equipment.

The key word here is “context.” The current best solution is the combination of using GPS to have a live view of when equipment is moving in combination with a CLM that provides context around what has happened to the shipment. In fact, that is the very combination of data that initiatives like Rail Pulse and other providers are using today.

At some point in the not-too-distant future, GPS and telematics will become smart enough to tell us the whole story, and more. But at least for the near future, the usefulness of the CLM will continue.

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