The connected truck puts the driver at its centre

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Walter Rentzsch, Wilfried Aulbur, Frank Pietras and Thomas Fang explore some of the key issues surrounding commercial truck data-related services

The promise of capturing vehicle data and turning it into profitable new services and business models has driven significant investments in the commercial vehicle telematics space by truckmakers and suppliers alike. However, despite significant investments in IT platforms, in-vehicle technology and service innovations, achievements are falling short of projections. Significant opportunity remains to be tapped.

There are many key challenges and questions for OEMs and suppliers. With many sensors that can be put on vehicles and a large amount of data that can be collected, it is imperative to put a data collection strategy in place. Players need to understand which services create value from a fleet or owner-operator perspective, how this translates into a dataset to be collected, how sufficient data quality can be ensured to define baselines and which sensors can be effectively deployed to collect the relevant data.

How to collect sufficient data to design value-add services requires truckmakers to work with platform and service providers, a challenge in itself as OEMs often perceive these players as competitors rather than partners. Finding the right engagement model, collaborating on service design and potentially co-creating services together with fleet customers is the need of the hour. All this with the backdrop of protecting core businesses around predictive maintenance and dealer integration, for example, in service activities.

The central element that enables fleet productivity and profits continues to be the driver. Driver availability and escalating driver costs are top-of-mind for many fleets globally

With an exponentially increasing amount of data, the question of platform architecture becomes paramount. In an environment, where bandwidth issues limit the capability of centralised, cloud-based systems to provide near real-time analysis, architectures need to become edge-based.

In addition, players face a major challenge in moving from a product-based to a service-based organisation. This change in business model strains aspects including capability, organisational structures, processes and systems. For example, often sufficient talent to ensure data and cyber security is missing and headcount for the implementation of large IT projects insufficient. Understanding of new business models and skills for key competencies such as innovative pricing models are in short supply as well.

Long-standing partners are disrupted by this shift in business model as well. The question of how to integrate dealer partners in new business models, how to determine fair revenue and profit sharing models, etc. is crucial yet not always simple. Changes in management must go beyond the boundaries of the company and include external agencies such as dealer bodies as well.

It is hardly surprising that many truckmakers find it challenging to execute and overcome internal resistance. Often, this leads to placing new initiatives in organisational units that are not subject to the influence of the traditional product-centric power structures.

Data-backed protection

From a fleet perspective, the central element that enables fleet productivity and profits continues to be the driver. Driver availability and escalating driver costs are top-of-mind for many fleets globally.

Making the job of a driver more attractive is a key challenge. Ways to address this are increasing cabin comfort and convenience, leveraging the right communication technology in the vehicle, and providing the right environment in terms of software and app support to drivers both from a work as well as a leisure perspective. Telematics plays a role in all these areas.

The connected truck puts the driver at its centre
Truck connectivity can benefit a range of use cases, ranging from ADAS functionality to enabling driver creature comforts

Starting from a safety and security perspective, traffic accidents involving trucks are a major issue for all road participants. In some markets, such as the US, litigation has become a major cost item in the fleet P&L due to an aggressive litigation culture. Technology that documents a crash, such as via a video camera that tracks the environment and the driver, can provide vital evidence in legal trials. Beyond this application, basic breakdown service that communicates the severity and location of the crash as well as informing the emergency services is a clear benefit.

While subject to different national regulations, driver health tech tracking heart rates, stress levels, and glucose levels can contribute to improved road safety. In emergency situations, such as a heart attack, the vehicle can take over and execute a safe emergency stop. For drivers with pre-existing conditions, a likely perspective due to an aging workforce, nearby hospitals could already be informed ahead of time regarding allergies or past treatments, improving care outcomes for drivers even when they are far from home.

Unseen hazards

Environmental factors need to be monitored to improve driving safety. ESP data, front camera sensor data, rain sensors, wiper usage, cloud cover are all are data points that can be collected and analysed to provide insights on hazardous driving conditions such as slippery roads, low visibility or black ice.

Real-time based navigation helps truck drivers navigate roads safely. Driving a truck is challenging due to physical restrictions like vehicle height, width, length, weight, as well as legal restrictions and various environmental concerns such as steep gradients and dangerous corners. Getting this information early supports drivers in getting freight from origin to destination safely.

ADAS innovations such as lane departure warning, blind spot detection, and self-parking have a measurable positive impact on road safety. In addition, data on braking and acceleration can be leveraged both for cost optimisation and improved driver performance via focused trainings.

Predictive maintenance, statistical analysis of workshop activities and their integration in predictive maintenance workflows, OTA maintenance, among others, are close to an OEM’s business and have the potential to generate profits either via increased revenue or via reduced cost

On driver welfare, interior memory settings are used to adjust factors such as seating or mirror positions to meet driver needs. Radio stations and apps can be pre-selected as well as POIs ranked according to driver preferences. These could include gas stations, restaurants or hotels. The business side of a driver’s life can be optimised as well. Condition-based or predictive maintenance enhances uptime which is good for fleet managers but also for drivers who, as in the US, are paid per mile driven.

Automated workflows and information about dock congestion reduces paperwork hassle and the time spent loading and unloading the vehicle. Over the air (OTA) updates dramatically reduce time and money spent per vehicle repair. It is a critical enabler of many of the points discussed above and reduces overall dealership visits while increasing overall completion rate of updates and software-related recalls.

First rewards

For many of the data-related services discussed, it is not yet clear whether they will become significant profit contributors or table stakes for OEMs. However, predictive maintenance, statistical analysis of workshop activities and their integration in predictive maintenance workflows, OTA maintenance, among others, are close to an OEM’s business and have the potential to generate profits either via increased revenue or via reduced cost. While there is still plenty of opportunity to be explored, first investments in technology are starting to bear fruit for key players in the value chain.

About the authors: Walter Rentzsch is a Principal in Roland Berger’s Detroit office while Wilfried Aulbur, Frank Pietras and Thomas Fang are Partners in Roland Berger’s Chicago, Berlin and Shanghai offices respectively

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