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Towards a driver-less world? Autonomy and its impact on the fleet business

Autonomy has major profit potential in the transportation industry, with per-mile savings in a transfer hub model of up to 40%, write Dr Wilfried Aulbur and Dr Walter Rentzsch

As the world works its way through the current pandemic, one thing seems clear: rather than generating new trends, the current COVID crisis is acting as a catalyst for societal change that was long in the making. From work-from-home to telemedicine, predictive maintenance to autonomous over-the-road and last-mile applications, the crisis has given us the incentive to explore new, technology-enabled approaches to handle our life and transact business.

Special report: How will autonomous driving transform fleet management?

To be sure, technology will not dominate every aspect of our life in a post-COVID new normal society. Children will still go to school, in-person business meetings will still be held (albeit less frequently), people will still visit doctors and get treated in hospitals. Yet, the crisis has shown the art-of-the-possible and with it changed our attitudes towards technological opportunities.

In the logistics industry, autonomous trucks hold the promise of securing supplies even in times when people seek to minimise inter-personal interaction, be it for last mile delivery of groceries or deliveries of truck loads at docks. Fleet businesses have seen the advantages of autonomous driving for some time. Potential safety improvements would help reduce fatalities in truck-related accidents and keep legal fees under check. Improved asset utilisation would help improve financial performance. Mitigation of the driver shortage problem would allow revenue gains while reducing overall fleet operating costs. Eliminating long, cross-country journeys would enable truck drivers to spend evenings at home rather than at truck stops and improve their quality of life.

Several autonomous business models are currently being explored such as autonomous platooning, tele-operations, the transfer hub and the dock-to-dock model (see Figure 1). While the implications on the business model of fleets differ, all address the driver shortage in the industry, albeit to a different degree.

Take the transfer hub model as an example. Here a driver in a conventional truck takes a trailer to a transfer hub close to a highway and hands the trailer off to an autonomous truck. The autonomous truck drives the trailer from the starting transfer hub to the end transfer hub, where it relinquishes the trailer to a driver-operated conventional truck that delivers it to its final destination. The long, over-the-road portion of the journey hence does not require human intervention, but drayage operations at both ends will still require human drivers. In the US, due to the high average age of drivers, this model still requires more than 1 million drivers to enter the business over the next ten years assuming relevant penetration levels.

Roland Berger autonomous fleet mgmt slide

What does this mean for fleet businesses? The overall mix of the driver pool (highly paid long-haul vs regional/drayage drivers) changes and the overall number of drivers for a given freight volume will come down. Pressures on driver shortage will be reduced (but may not be fully eliminated) and HR practices will need to be adapted to a changed driver mix. One barrier of entry into the business, i.e. the management of a large driver pool, may become less relevant, allowing others to look more carefully at an entry into the business.

In and of itself, this change is hardly substantial enough for fleet owners to lose sleep. However, the technological disruption via autonomous trucks has more ramifications than a lower number of drivers alone. In addition, the digitalization of the logistics business is chipping away at other fleet core competencies.

As we have seen in the transfer hub example, the logistics business model is changing. For example, transfer hubs introduce a significant real estate component into the business. Managing transfer hubs is similar to managing intermodal terminals that are currently run by railways. Running autonomous trucks on long-haul routes without any driver involvement could be interesting, involving players outside the industry, such as automakers, start-ups, truck leasing companies, railways or others. These players may be willing to explore capacity-as-a-service models, i.e., bypass carriers by directly offering autonomous truck capacity to shippers.

In addition, digital freight matching and predictive maintenance technology attack core competencies of modern fleets beyond driver management. Taken together, these changes introduce sufficient uncertainty in the transport ecosystem such that fleet operators should take a hard look at what their future holds and where in the value chain it lies.

Fleets need to look carefully at which customers and routes could benefit from autonomous trucking and when such services might be launched. They need to understand their customers’ needs from an end-to-end perspective as well as the changing competitive environment that may play out in an autonomous future. Value chain participation models along transfer hubs and intermodal business models need to be understood, and the opportunity to expand existing digital solutions to a capacity-as-a-service model needs to be analysed.

The profit pool that autonomous technology unlocks in the transportation industry is large, with savings per mile in a transfer hub model of around 20-40%. First movers in this space are likely to profit from a winner-takes-all environment, at least in the initial years of technology penetration. As business models have become clearer over the last few years, so has the understanding of where value can be sustainably captured. For fleets, finding the right business model and the right timing for investment is crucial. Fortune is likely to favour the brave.

About the authors: Dr Walter Rentzsch is a Principal and Dr Wilfried G. Aulbur is a Senior Partner and Member Supervisory Board at Roland Berger

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