Digital Freight Brokerage - The Future of Freight?

digital freight brokerage

Digital Freight Brokerage (DFB) takes Traditional Freight Brokerage (TFB) methodology and applies the latest database management software to it. This is done in an effort to better collect a wider range of real-time data. This data is pulled from a mix of shippers needing to move goods and carriers with the resources to move those goods.

Essentially, digital freight brokerage is faster and more encompassing than the traditional methods of manual collection. Furthermore, it is able to achieve this in a single sweep - using "what if" comparisons as an integrating algorithm. This type of algorithm produces digital load-boards and automated "on-demand" brokerages. And in the process, it creates a more efficient "multi-pickup/multi-drop" route map in the process.

It does all of this in half the time and with half the stress as the traditional brokerage model.


Will Digital Freight Brokerage Ever Replace the Traditional Brokerage Model?  

The now many and varied connected devices in trucking, when fed through software, can have valuable data extracted in just a few simple steps. This software can then provide everything from simple load listing/tracking to advanced instant load/carrier selection, pricing and bidding functionality based around that aggregated data.

Using such technology, the DFB can produce details about shipping capacity and nearest-route availability incorporating "immediate status/location" of transport. 

Until recently, the standard model of Freight Brokerage has been based on traditional methods that utilize the experience of a "middle man" in conjunction with a list of traditionally/regularly used reliable carriers. These parties are generally selected based on historical data such as past experiences working with that same carrier.

Low margins in the trucking industry often arise from commercial long-haul trucks in the region. Typically, these trucks are operating with about 25% empty miles. When this is combined with lengthy asset-idle times, the result is a 56% load efficiency. Empty miles account for a staggering 25-40 percent of total road-freight miles every year in North America. This translates to fuel waste, more emissions, lost driver hours, inflated operational costs and unnecessary road congestion.

Such empty miles primarily arise from the opacity and unwieldiness of traditional brokerage processes. The traditional brokerage process is challenged by the sheer size of over 100,000 shippers and 16,000 brokers supplying over 240,000 small-medium carriers plus owner-operators.

An old business saying goes "Don't work harder, work smarter!". To succeed, digital freight marketplaces must equal or surpass the performance characteristics that shippers have become accustomed to, and expect from traditional methods.

If DFBs can do this at a lower price, while incorporating critical services and features, then we may start to see disruption that is repeatable, scalable, and profitable. By itself, load matching is a commodity, and DFBs must offer much more value beyond load-matching. Global and regional digital freight brokerage market research targets customer's needs and wants to report on how effectively a company can meet their requirements. It does so by collecting data about customers, marketing strategies and competitive information.

To succeed, a DFB must build and maintain a multi-sided platform in the marketplace that performs four functions;

  • First, it must build a large audience of shippers and carriers who have an interest in transacting with one another.
  • Second, it must successfully match shippers and carriers with one another for the purpose of transporting freight. 
  • Third, it must provide, or allow other partners to provide complementary tools and services that are important for facilitating and removing friction from the on-going value exchange between shippers and carriers. 
  • Fourth, it must develop, maintain, and enforce rules of behavior for participants of the platform.


Final Thoughts 

The digital brokerage industry is growing rapidly and will generate at least $11.5 billion in revenue in North America by 2025. Freight Brokerage is a business that has traditionally relied on personal relationships and trust. Despite low rates per mile, carriers and shippers don’t focus only on rates. They also analyze payment assurance, cargo safety, service continuity, and rate negotiation leverage.

While the highly fragmented freight brokerage market will digitalize, it must also consolidate,  otherwise delivering on promised efficiency improvements remains uncertain. 

As shippers' expectations and needs keep evolving in managing much larger audiences of customers, DFB must also continually develop, even to the point of AI, whilst remaining visible and transparent.

Shippers, carriers and brokers are spread across thousands of digital platforms, and the trucking industry cannot achieve the type of efficiency improvements envisaged without unification of systems. Transporting freight is a complex business. Often, freight shipments must be transported via different modes of transport between origin and destination giving rise to a coordination problem between different counterparties, not yet totally achievable with software, with numerous regulations which carriers and shippers must adhere to. Things go wrong all the time when freight is being transported over relatively long distances, presently requiring human intervention to resolve, employing Traditional Broker Initiative, Intelligence, Experience, and INSTINCT which at the moment are not all achievable by technological artificial intelligence. Progress in this area continues steadily, and that is not to say AI will eventually be able to make the decisions to rectify all problems as they arise. 

Traditional freight brokerages are characterized by comparatively large numbers of people who understand shippers’ needs and work as intermediaries between shippers and carriers, performing a function that cannot yet be entirely replicated with software or AI. For example, when one of your TFB older and experienced individuals come to retire or leave, the skill set, knowledge and customer rapport he has accumulated over the years go with him.

The software, in comparison, retains that accumulated knowledge and integrates it quickly and more efficiently than more traditional models.