100 % visibility? The transport industry continues to strive for this very goal

100 % visibility? The transport industry continues to strive for this very goal

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Marian Pufahl

Marian Pufahl

CEO and CO-founder Synfioo GmbH


100 % visibility? The transport industry continues to strive for this very goal

A fully transparent supply chain does not yet exist on a broad front. But the progress made in recent years has been remarkable. In this endeavour, it’s crucial to filter out the right information from the enormous flood of data and pass it on to everyone involved. In this regard, the use of AI and ML is an additional driver for more supply chain visibility.

Not too long ago people would usually only rely on their own eyes when waiting for a tram, bus or train – and visibility ended at the next corner. At the most, a more or less precise announcement from a creaking loudspeaker at a train station or central bus terminal was available regarding the punctuality of a chosen connection.

However, since the beginning of the digital age, mobile devices have given travellers the chance to see an overview of the situation themselves. This usually works very well but is often imperfect.

Parallel to these developments in passenger transportation, the freight business has also been upgrading from an IT perspective in recent years. This applies both to the hardware, which enables data transfer from land, air or waterways, and to the software. However, it is only those who take an intelligent approach to handling data, or who are able to prepare information in a meaningful way, who can create real added value for their customers.

Beneficial data analysis

At Synfioo, we have set ourselves the goal of minimizing the factor of uncertainty in the end-to-end monitoring of cargo flow. Of course, this is of great importance especially for the recipients of the shipments. They need to know when the goods arrive in order to be able to carry out the next step in the transport chain as efficiently as possible.

In order to generate reliable predictions for arrival times, for example, we link current location information from trains, trucks, aircraft and ships. In addition, more than 70 data sources on potential disruptive factors are included in our calculations.

These can include traffic jams, weather phenomena or organizational hurdles, for example at congested border crossings, as well as other key figures. This brief list alone shows how complex the impact of the most diverse factors on the reality of everyday transport can often be.

This is especially true in international supply chains, which are the rule rather than the exception in a globalized world economy. Completely trouble-free transports over several hundred or thousand kilometres using several modes of transport are more wishful thinking than reality.

No perfection needed to succeed

Of course, companies like Synfioo are striving to broaden their database and want to shed even more light on areas of supply chain management that have not been illuminated by information technology yet. The more knowledge available, the better these developments can be managed.

100% transparency in the data flow is certainly desirable for the aforementioned added value for our customers. But of much greater importance are the following two points that characterize Synfioo’s offer in this area of logistics IT; the application of artificial intelligence (AI) and machine learning (ML). This is because these tools make it possible to generate very accurate predictions with incomplete (live) data.

Since learning is done from every previous calculation and recurring patterns are quickly recognized, the quality of the predictions along the timeline increases with every use of the algorithms. In this field of application, we can thus benefit from the fact that our solutions are further optimized step by step for a particular customer.

To put it bluntly, although source data does not yet guarantee 100 % transparency, it will nevertheless provide very high accuracy for ETA prediction.

Photo credit @ Mark Ellem/ Flickr

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