Discover how automotive innovation is being powered by high‑velocity, harmonised data - enabling smarter vehicle design, dynamic pricing, enhanced supply chain resilience and real‑time decision-making across the industry.
The automotive data ecosystem encompasses a wide range of data sources, including customer data, vehicle data, supply chain data, and more. This data is collected, processed, and analysed using advanced technologies such as AI and ML to generate insights that can be used to improve vehicle design, manufacturing, sales, and service.
Today, with the Internet becoming more commonplace, and vehicles taking a modern turn with the incorporation of digital technologies, the automotive data ecosystem is set to capture more data than ever. Particularly, the connected car data is expected to create a successful automotive ecosystem, adding revenue streams, creating cost efficiencies, increasing customer satisfaction, building safer products, and enabling a safe driving experience. According to data by McKinsey, the connected-car-data-based services are likely to generate up to USD 750 billion by 2030.
Let’s look at some other trends defining the global automotive data ecosystem today.
There are three areas where the global automotive data ecosystem has been growing; connectivity, digitalisation and data integration. Some recent trends in this area include:
Like we mentioned earlier, connected car data is creating a successful automotive ecosystem by adding revenue streams, increasing customer satisfaction, and improving society. For example, the data can be used to offer personalised insurance policies based on driving behaviour, which can lead to lower premiums for safe drivers. It can also be used to provide real-time traffic updates, weather alerts, and other useful information to drivers. And, it can be used to predict maintenance needs, identify which services can be improved, which can enable the car to operate fully autonomously.
The second key trend is data integration, which is enabling a new future mobility ecosystem based on seamlessness, individualisation, safety, and on-demand. In other words, data integration is the process of combining data from different sources to create a seamless and personalised experience for the user while ensuring safety and on-demand services.
A Merit expert adds, "This trend is leading away from a mere product-oriented way of thinking to a flexible and agile digital era. Data integration is the key to bring these ecosystems to life."
In 2022, Gartner identified the top five technology trends for 2022 that CIOs need to consider to better prepare for the software, hardware and digital transformations occurring in the automotive sector. One of the trends identified was the adoption of open data and open-source collaboration models in the automotive sector. This trend is still relevant in 2024, as several major automakers are expected to launch their own open-source EV architecture soon.
The adoption of open-source vehicle architecture operating systems and open electric vehicle (EV) platforms allows automakers to collaborate with other companies and share their resources to develop new technologies and products. This trend is expected to continue in the future, as it enables automakers to reduce costs, improve efficiency, and accelerate innovation.
While data promises to provide multiple benefits to automakers, there are still challenges associated with its adoption and use. Let’s look at primary challenges and potential solutions to address them.
The automotive industry is facing two main challenges in the data ecosystem. One of the main challenges is the monetisation of data from connected cars. While connected cars provide a unique customer experience, most players have overlooked opportunities to monetise data from these vehicles.
A related challenge to the lack of monetisation, is the lack of data connectivity. Many OEMs have struggled with connectivity or related software developments, resulting in poor customer reviews and delayed start of production.
To address these challenges, companies can focus on providing end-to-end access to raw data per car each day to enable continuous product and service improvements. They can also focus on monetisation throughout the vehicle life cycle through recurring revenues from monthly subscriptions, such as those for premium connectivity services, and paid over-the-air (OTA) upgrades, which may eventually include those related to full-self-driving capabilities.
In addition, collaboration and partnerships across traditional industry boundaries will become more important than ever. By working together, companies can share resources and collaborate to develop new technologies and products. This approach will allow automakers to reduce costs, improve efficiency, and accelerate innovation.
The global automotive data ecosystem is undergoing a transformative shift driven by connectivity, digitalisation, and data integration. As connected car data continues to shape a successful automotive landscape, embracing open-source collaboration models and addressing challenges in data monetisation are pivotal for industry growth. With a focus on innovation, collaboration, and customer-centric strategies, the automotive sector is poised to harness the full potential of data, ushering in a future of enhanced efficiency, safety, and personalised mobility.
Merit Data and Technology excels in aggregating and harvesting automotive data using AI, ML, and human expertise. Our capabilities include:
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Connected Car Revolution: The integration of connected car data is driving a successful automotive ecosystem, offering personalised services, real-time updates, and predictive maintenance, contributing to increased revenue and customer satisfaction.
Data Integration for Future Mobility: The trend towards seamless, individualised, and on-demand mobility experiences is fueled by data integration. This shift from product-oriented thinking to a flexible digital era is crucial for shaping the future of the automotive industry.
Open-Source Collaboration: The adoption of open-source collaboration models in the automotive sector, identified by Gartner, remains relevant in 2024. Major automakers are expected to launch their open-source EV architecture, fostering innovation, reducing costs, and improving efficiency.
Challenges in Monetising Data: Despite the potential benefits, challenges such as the monetisation of data from connected cars and slow progress in connectivity persist. To overcome these, a focus on end-to-end access, continuous improvement, and collaboration across industry boundaries is crucial for success.
