We can divide the evolution of commercial transportation management into three high-level stages. In the pen and paper era, the process was entirely manual and dependent on knowledge from local resources. As a result, there was very little process standardization, visibility or optimization to speak of.
The advent of enterprise-level transportation management IT systems, such as SAP TM were a substantial step forward, as they allow us to standardize intricate procedures, eliminate much of the paperwork and monitor key steps in the transportation process.
However, the limitation of the IT TM solutions lies in the manual nature of the data collection process. Pure-IT transportation management systems provide little transparency into the transportation execution stage of the delivery process. They do not allow fleet managers to react against setbacks, such as unnecessary driver idle times and do not provide enough data for long-term optimization processes.
This is where the third stage in the TMS evolution comes in. By replacing manual information input with reliable feeds of constant IoT data, fleet managers can now leverage complete visibility in their operations to make better, faster decisions. Specifically, this applies to a number of areas:
Live truck location and inventory condition monitoring
With the presence of an IoT sensor, you can get a live feed of what/where/when: where are your trucks, what are they carrying and in what conditions? With the live information now available on a single dashboard, there are a number of concrete business benefits that can be derived:
- The ability to make sure that drivers use the agreed-upon routes and don’t deviate for any of the possible reasons;
- Idle time monitoring: since a long stop can signal anything from a long nap, a vehicle malfunction to a security issue;
- Ability to prevent inventory spoilage if the transport conditions change by re-routing trucks and conducting preventative maintenance for cold-storage containers.
Automation of execution monitoring
Rather than rely on the accuracy and integrity of manual event input from drivers, fleet managers can now get automatic updates in their TMS system about the current stage of a delivery which is in process. Do the geographic coordinates of the truck signal that the vehicle has entered the perimeter of the warehouse Yard? If so, the TMS system triggers a “final delivery” and registers the time stamp. Has the truck arrived at a warehouse door? An “unloading” event is triggered. The same idea applies for any part of the transport process by eliminating the need for manual information entry and leveraging sensor data to track all the stages of a delivery.
When it comes to both long and short-term transportation planning, IoT can be an invaluable source of information. For system-wide lane definition, IoT can provide an aggregate of trip durations that will allow you to define lanes with higher accuracy and thus provide an improved planning base line. At the same time, live truck location, coupled with traffic patterns and weather information, allow the TMS system to automatically adjust scheduled delivery times.
Finally, with all the accumulated data, IoT facilitates the review and optimization of company-wide transportation practices. In our experience, information such as total fleet utilization, carrier score cards involving real data for on-time deliveries and transport conditions, as well as route bottlenecks and idling times can lead to substantial improvements in company operations.
As with any IoT initiative, the value-add of IoT in the supply chain lies in the integration of sensor data with the sophisticated business logic of the transportation management system. Rather than being a competitor to “traditional” TMS solutions, we view IoT as the enabler of the already sophisticated business core. For a more detailed discussion on the topic, reach out to us.
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