The German automotive industry has been shaken to its core by the combined effect of two disruptive forces—decarbonisation and digitalisation—which are simultaneously impacting the industry and instigating major changes. As new business models and partnerships emerge, how will the major automotive companies adapt and survive?
The German automotive industry
For over a century, the German automotive industry has set international standards in automobile manufacturing. It was an era in which German automobiles became the epitome of top-quality workmanship worldwide. Volkswagen, Mercedes-Benz, BMW, Porsche, and Audi were known for their finely tuned combustion engines and powertrains. The German car was at times considered “the car” par excellence. This era is now coming to an end.
The German automotive industry consists of original equipment manufacturers (OEMs) and a three-tier supplier network. According to Statista, there were a total of 933 companies active in the German automotive industry in 2021; German-based OEMs Volkswagen, Daimler, and BMW were among the top 10 car manufacturers worldwide. In the 2010s, companies achieved one sales record after another. However, the 2020s will be marked by a longer-term structural change.
Decarbonisation and digitalisation
The impacts of decarbonisation and digitalisation are giving rise to major changes in the industry. The decarbonisation of the transport sector and the associated switch to alternative drive systems and fuels are taking place in parallel with advancing digitalisation, with effects on vehicle production and mobility offerings.
In 2016, Daimler created the acronym, CASE — connectivity, autonomous driving, shared services and electric mobility — to address the technology and market trends faced by the automotive industry. Digitalisation is often seen as the trigger for these “megatrends,” each of which has the potential to destroy the existing business models (Figure 1) and turn the entire industry upside down.
Digitalisation is having repercussions on how automotive industries function, notably in the production area. “Smart factories” combine a variety of the so-called “Industry 4.0” technologies, such as robots connected to the Internet, and the use of high-performance computers for machine learning and data analysis.
Looking to the future, the Industrial Internet of Things (IIoT) will be deployed to network production facilities worldwide. IIoT devices will regulate the flow of data between plants and control all logistics for parts, procurement, production and distribution. Digital twins will also use IIoT devices to monitor and support production in real-time. Siemens and Daimler are cooperating on the development of a fully digitised model factory for the Mercedes plant in Berlin-Marienfelde, which is to become a pioneer for all 30 Mercedes plants worldwide.
A new era in automotive development
These changes are forcing Germany’s flagship automotive sector to invest considerable resources in attaining new knowledge through research and development, and to partner with the big tech players. Recent research has examined how the industry is changing its sourcing strategy accordingly. Nvidia and Qualcomm are dominating the provision of chips for the central on-board computer, and are increasingly offering software for automated driving (Figure 2).
There have been a number of initiatives to create cross-industry platforms involving major tech players.
In 2019, BMW and Microsoft founded the Open Manufacturing Platform based on Azure cloud. The objective is to create an industry-independent and standardised production platform based on open-source software. Knowledge, data, new technologies, and everything that drives the development of innovations can thus be shared more easily. Similarly, Volkswagen has been working with Amazon AWS and Siemens to develop an industrial cloud that will connect all 122 of its plants to further invest in factory automation and use a large amount of technical data.
The industrial cloud is based on AWS technologies in the areas of IIoT, machine learning, data analytics, and computing services. The solution is being developed as an open industry platform that other partners from industry, logistics, and sales can use as well. This is intended to create a steadily growing global industrial ecosystem.
New relationships within the automotive supply chain are also being forged. Volkswagen and Bosch recently announced a partnership to develop and launch highly automated driving functions in all VW vehicle classes, also making them available to other manufacturers. Both companies declared this as a paradigm shift in the cooperation between an OEM and a tier-1 supplier. This partnership is seen as a challenge to the involvement of US technology companies in car operating systems. Bosch aims to become the leading supplier of application-independent vehicle software in the future.
In summary, the car has become a complex IT product, with leading companies now specialising in vehicle-related computer programmes and mobility services. Software is increasingly becoming the key differentiation criteria in the automotive industry. The automotive companies will need partners, due to a lack of expertise in software development for connected cars, and thus value-adding sourcing is of particular significance.
The industry is now entering into a series of strategic partnerships in connection with “Car IT” and automated/autonomous driving. As recently noted by Wiegand and Brautsch, “The established companies are faced with a multi-dimensional disruption initiated by new technology leaders.”
“This will radically change existing business models by establishing a new culture of use for the automobile, based on new digital networking and operating platforms. Future success will depend more on capabilities in the field of digital product features and connectivity, than on developing and producing cars,” they added.
Felser, K., & Wynn, M. (2020). Digitalization and Evolving IT Sourcing Strategies in the German Automotive Industry. International Journal on Advances in Intelligent Systems, 13(3-4), 212–225. https://eprints.glos.ac.uk/8670/