Total visibility: the catalyst for a new era of rail and river freight movement

Given the cross-border complexities, gaining visibility of Europe’s rail freight infrastructure is particularly challenging – even more so when connected to an ocean or road journey.

To solve this challenge, organisations need direct access to comprehensive insights from inland freight infrastructure, including real-time data around scheduling, routing, and position – particularly at an individual rail wagon level.

After all, accurate multi-modal ETAs require end-to-end visibility into individual rail carts. However, most visibility vendors can only offer limited insights – providing rail wagon data from a few wagon lenders, or offering limited operator, pickup, and haulage data from specific ocean carriers. In short, inland movements remain a mystery for a significant number of rail shipments.

Visibility technologies must therefore include inland location data – such as event status updates, dwell time, stop statuses and other important insights – to provide a complete picture of a shipment’s journey. For optimal results, internet of things technologies should be integrated with real-time freight infrastructure data, providing granular end-to-end visibility down to individual rail wagon level.

Additionally, combining machine learning and self-learning capabilities with these rich data sets will help companies to proactively prepare and respond to any issues that may affect carriage, providing resiliency in an increasingly complex environment.

Crucially, these technologies can also harness data from other transportation modal segments, such as ocean and road freight, to provide the most accurate ETAs for global shipments.

Credit: SkedGo | MOTIONTAG

Complementing rail strategies, barges are an environmentally friendly and cost-effective transit option. However, switching between barge and other modes has previously created gaps in visibility for shippers and 3PLs.

These visibility gaps bring their own challenges, causing complex routing systems that are informed by inaccurate predictions on water levels, as well as patchy scheduling and identification information. This visibility is critical, as issues with barge arrival and departure can have a significant knock-on effect for inland transport.

Suppose a barge shipment that’s travelling via the Pearl River Delta is delayed due to a flood. In that case, the shipment may not make its vessel departing Shenzhen to arrive in Rotterdam, resulting in costly delays for the supply chain professionals involved.

Fortunately, barge freight infrastructure is following rail’s lead and is undergoing its own digital transformation. It is now possible to provide highly granular and accurate visibility of the inland waterway segments of a shipment’s journey.

Advanced machine learning techniques leverage real-time satellite and localised waterway data to dynamically model routing and water depth, and automatically identify the barge vessel associated with a customer’s shipment. This ultimately results in more accurate ETAs for multi-modal journeys and their barge segments.

It is evident that any corporate sustainability plan must include more rail and barge cargo. Beyond that, the priority should continue to be on providing an open and trustworthy client experience throughout.

Modern visibility technologies make it simpler than ever to optimise operations and eliminate bottlenecks in a way that is more sustainable for both the provider and end-user, helping all stakeholders to achieve ESG goals.

It is clear that implementing a multi-modal supply chain strategy is essential to lowering scope 3 emissions, but we must make sure that we have the data and visibility necessary to guide sustainable decisions for all modes.