Logistics Expert Calls for Modernizing Cargo Transport

The bulk of cargo shipping companies are clinging to a logistics model that is more than 20 years old and missing out on the digital future.

That’s the view of Per Olof Arnäs, senior logistics strategist at Einride, during his digital, Electric & Autonomous – The Future of Freight presentation at Automotive Tech Week 2021 in suburban Detroit.

While admitting the model can still be effective, even during the global pandemic, it will, ultimately, limit the growth potential of the businesses applying it.

Proof of the companies’ reluctance to advance can be seen in the industry investment trends in the past decade. Arnäs says: “Between 2011 to 2019, all industries in Sweden increased their R&D spending by 25%. Automotive went up 50% and the service sector more than doubled their spending. Yet spending on transport and logistics went down by 80%, an extremely depressing list of statistics.”

Exploring the reasons for this stagnation, he points to the law of diminishing returns applied to the electric passenger-car sector where early adopters had to pay a lot for not much of a return on their investment. However, as the market grew, and accelerated during the pandemic, costs fell and growth was achieved. Yet, as the market matures, that growth plateaus and returns stagnate.

Arnäs suggests this puts off many companies who then cling to their proven old-school business models. He explains: “The haulage and transport industry have extremely low profit margins of, maybe, 1% to 2%. They have extremely large balance sheets having to invest a lot for low margins. So, in order to be profitable, and they can be profitable, you need to have 24/7 operations.”

This is compounded by a very fragmented industry with many companies made up of one owner driving his truck, resulting in a low uptake of digital technologies. Thus, these companies are more interested in improving what they already have rather than trying something completely new such as an electric vehicle.

Arnäs admits the old “1999” logistics model is extremely robust because it has stripped away complexity in what he called a process of reductionism – while at the same time, switching a fleet over from diesel to electric powertrains will greatly increase the complexity of a company’s operations.

He explains that when you plan for an internal-combustion-engine fleet, you assess the distance, the volume and weight, the time and the load factor and utilization. Going electric involves all those plus considerations of topography, weather, charging time and infrastructure, battery range and driving speeds.

Yet, there will be considerable rewards if companies begin adopting a “Digital First” mindset, Arnäs says. He explains: “You will then let your decisions be driven by data. You will not drive one mile unless the algorithms say that’s what you need to do to keep the system achieving its overall goal. There will not be any fixed ‘milk runs,’ no fixed delivery days, everything will be dynamic and extremely hard to do.”

He says this is where the improving power of computers will come in, having already increased in power by some 10,000 times in the past 20 years.

Arnäs continues: “To drive this change we have three pillars. The first is our freight mobility platform, the centralized brain that will decide everything that happens in our transportation system. This acknowledges that we humans are not as well equipped to handle the increased complexity that an electric fleet will bring.

“The second pillar is electrification of the transport system. For more than a year we have been transporting goods for our customers – no demonstrators, no pilots, just commercial traffic for real customers,” he says. “The third pillar is the autonomous electric transportation system, and these vehicles exist and work today. We embrace the complexity of these systems because if you oversimplify, an electric fleet will not be efficient.

“You need to be able to handle a vast amount of data, several new variables and you need to be able to act on the data in real-time or near real-time. This is not science fiction – we are rolling this out both in Europe and the U.S.”