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Rethinking Automotive. Data and Digitalization as the Driving Force Behind New Use Cases

The digital transformation is defining everything that is happening in the automotive industry right now. A key part of this trend is a data revolution that is turning the entire ecosystem upside down. Vehicles are no longer simply ‘manufactured’ at a plant, but assembled module by module from smart components. As a result, customers’ needs and wishes can be identified and implemented swiftly, especially with the help of data, analytics and some AI. Every product detail is transparently documented. 

The automotive industry is a true staple of the German economy. Nevertheless, it has some catching up to do in the digital world. Focusing consistently on integrated, software-supported EV architectures, Tesla, Polestar and Nio are off to a head start. To remain competitive with these development leaders, the German automotive sector will need to prioritize digital services.

The need to go digital also applies to supply chains, production and logistics. AI and automation are helpful tools, not only to raise efficiency but also to cut production and material costs, a major factor in ensuring global competitiveness. At the same time, the industry has to put great efforts into handling a variety of societal and regulatory issues, especially ESG compliance.

Data-Driven Value Chain

The new, highly complex ecosystems come with both benefits and drawbacks. Going beyond traditional supply chains requires companies to take their entire value chain digital. The goal: to improve value creation and supplier relationships alike. In doing so, intelligent data management impacts all stakeholders, from suppliers and manufacturers to distributors, dealers and service providers.

3 Trends Currently Changing Your Industry

Digitalization and Connectivity

Vehicles are no longer differentiated solely by their physical specifications, such as engine output or energy consumption. It also makes a big difference to what extent they are digitalized and connected: these days, an increasing number of models are equipped with sensors that continuously collect data. Via Vehicle-to-X technologies, this data is shared with the cloud and other devices in the environment, taking functions such as real-time monitoring, traffic flow optimization, personalized service offers as well as diagnostics and maintenance to a new level.

Integrated Architecture

With the increased digitalization of our vehicles and especially concepts like connected cars, the demand on databases has dramatically increased. Via data transmission, connected vehicles receive information on current traffic or the nearest gas station as well as over-the-air updates. But developing software-centric vehicles requires secure IT architecture and governance structures

Industrial Internet and the Digital Twin

The digital twin is an essential element of the Industrial Internet. By digitally modeling entire production chains, they can be optimized with the help of data management and analytics. Sensor data is fed into AI models to improve capacity utilization and production processes at factories. Moreover, data also provides information on how to improve ESG performance, for instance by cutting carbon emissions.

Industry Voices

“Software-related issues are a bigger challenge for the automotive industry than the transition to electromobility.”*

Data Leadership For Experts

Thank You, Managers. From Here On, It Gets Boring…

Or simply more specific (however you like to see it).
The experts among you will probably appreciate that we also provide insight here
that goes well beyond the necessary basic understanding. So, let’s go!

Technology Issues in the Industry

For Experts Only: Tech Trends in Automotive and Vehicle Construction

Smart Factory 

No forward-looking strategic agenda can afford to ignore current automation topics, such as robotic process automation, IoT and AI. To ensure the successful implementation of such features, a secure and stable IT and data infrastructure across the entire production pyramid is key. Data pools tend to be large, heterogeneous and often unstructured; but smart cloud systems and data & analytics solutions help you make the most of them. They take care of cleaning input information and improve the informative value of analyses.

Next-level operational efficiency for recurring manual processes in production and administration requires automation. Data & analytics solutions provide clear information on orders, inventory levels, delivery times and production capacities in real time. And thanks to centralized data storage, business units in Marketing and Sales benefit as well.

Data Strategies and Data Governance

The great significance of data is particularly evident in on-board IT systems such as driver assistance features. Every level of autonomous driving brings new requirements for the central data management and spot analysis of data to make the right decisions. The safety and reliability of these applications needs to be guaranteed at all times; and this means you must have full control, both in day-to-day operations and at a strategic level. 

Master data management (MDM) allows you to manage master data on vehicles, parts, retail partners and customers as well as standards and regulations with required certifications correctly and consistently. Within the structure, data governance determines who has access to which data, and what data is subject to more stringent control. It also ensures compliance with external standards set out by industry associations, authorities and other stakeholders.

MDM and data governance improve data quality and facilitate AI-based analyses. MDM also supports you in integrating information from different sources, as it streamlines the often very heterogeneous input data. The result is a holistic picture of your business assets, allowing you to respond quickly to changes. Efficient master data management is one of the best tools to keep you competitive.

The EU’s Digital Product Passport (DPP)

Companies that intend to sell products on the EU market need to be greenlit to show they meet the legislative requirements set out in the new Ecodesign Regulation. The Battery Regulation was the EU’s first directive to stipulate a Digital Product Passport (DPP). The battery passport now serves as a precedent to champion a circular economy. The DPP impacts manufacturers in several ways: while it can boost their reputation, it also requires a specific level of transparency and compliance. Initial steps include linking product passports to a unique product identifier, complying with ISO/IEC 15459:2015, using the GS1 Digital Link for user-product interaction and setting up GS1 EPCIS repositories for sharing traceability data.

Customer Experience and Data Analytics 

To truly understand your markets and customers, you need sound evaluations. These build on the availability of meaningful data in sufficient quantity, clarity and quality across manufacturers, dealerships, financial services and other service providers. Business intelligence and analytics tools use the raw data to generate valuable insights. Market research, product development or customer service may take this approach one step further: predictive analytics tools provide projections based on vast amounts of data, making sure that decisions are based on facts and not just a gut feeling. Deciding without the right data & analytics tools is like driving in the dark with no headlights. On top of all other benefits, a data-based strategy also allows you to address customers and prospects in a customized approach for each target group. 

With markets fluctuating and regulation becoming more and more complex, the industry is under a lot of pressure. In these challenging times, strategic decisions must have a solid foundation, and data-based recommendations are the best way to convey credibility and trust. 

Data Literacy and Upskilling

The demand for data experts in the automotive industry is growing, and there is no limit to the number of job ads looking for specialists in the development, maintenance and optimization of complex systems. The ability to read and communicate data within the context is a high-demand skill, which includes everything from an understanding of data sources and data collection to data management and analytics. Data literacy is required in a broad variety of fields, ranging from marketing to software development and cybersecurity. Finding the right people to fill these positions remains one of the biggest challenges for companies. At the same time, job profiles are changing and the ability to collaborate in interdisciplinary and diverse teams is becoming increasingly important.

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