Business Transformation for Software-Defined Vehicles

What exactly is the transformative nature of software-defined vehicles (SDV)? This article explores transformation from a product development-perspective in three layers:

  • automotive business including business models of various traditional and new players
  • product from a "simple car" to smart connected SDV
  • engineering processes, methods and tools for SDV development

Note: the article is based on my presentation at the "2023 Tokyo Systems Engineering Summit".

What is SDV?

There are many definitions of SDV. I will work with the following from the Eclipse SDV Working Group: "The term software-defined vehicle refers to a transformation where the physical and digital components of an automobile are decoupled (HW / SW separation) and features, functionality, and operations are defined through software. In a fully programmable car, digital components—such as modules for safety, comfort and infotainment, and vehicle performance—would be regularly developed and deployed through over-the-air updates."

The Business Case for SDV

For OEMs, the business case is pretty clear: SDVs enable additional revenue over the lifetime from a large fleet of connected vehicles by selling SW-based services and subscriptions, features on demand or data as a service. With large fleets such as in Volkswagen Group or Stellantis, this leads to expectations of 10-20 Billion Euro additional SW-enabled revenue annually by the end of this decade per OEM.

Business Transformation in a System-of-Systems

The value proposition of SDVs is a seamless integration into the digital lifestyle of customers. Connected cars have established a lot of basic components for this with a focus on connectivity to a proprietary OEM backend. The software-based services of an SDV require even more integration with non-automotive industries such as banking, insurance, utilities, telco and of course tech companies.

From a product development perspective, this demands systems engineering with a system-of-systems approach. The system-of-interest is no longer only the car, but the mobility system including services from providers in the system context. The system boundary and the interfaces to the service providers need to be actively developed.

Choosing the right standards – and increasingly open source initiatives – is a key to decouple the SDV from changes in the context. The right use of standards also increases the monetizable fleet across car lines and model generations.

Automotive companies need to build new business capabilities to develop and operate SDV. Please find more information on our EAM (Enterprise Architecture Management)-based approach including our NTT DATA business capability model in this article on Business Transformation Management.

SDV Product Transformation: Shift-North

In traditional E/E architectures, each function had it's own ECU. Developing functions on 100+ distributed ECUs becomes prohibitively complex and expensive. This led to E/E architectures with fewer domain controllers and/or zonal controllers on high-performance computers (HPC), running multiple functions in parallel on one device. Standardized operating systems and middleware provide the hardware abstraction that enables this shift.

SDVs continue this "shift-north" to upper layers of the stack, i.e. implementing functions on edge or cloud computing resources instead of incar devices.

This is the critical SDV product transformation because it allows the development of software independent from the hardware, resulting in:

  • delivery of new SW-based functions and frequent updates over the air (OTA)
  • very high scalability for resource-hungry applications such as AI and entertainment
  • seamless digital user experience across channels and interfaces such as HMI, voice, web, app

Engineering Transformation: Shift-Left

Shifting activities to earlier phases of the engineering process, where change is faster and cheaper, is no new concept. Replacing hardware prototypes with simulation models has been a key concept of virtual product development for many years including the evolution of model-based systems engineering. SDV however continues this evolution with cloud-based virtual engineering workbenches, providing simulations of ECUs with binary parity and of the HMI, resulting in an improved developer experience for globally distributed teams.

Platforms and modular architectures have also been used as a "best practice" in product development for quite some time. For SDV, the physical platform of mechanical and E/E hardware is connected to a software platform in the cloud / backend. The business case of SDV, i.e. the size of the monetizable fleet, depends mainly on the number of SW-based services sold to as many cars as possible. Ideally, all brands, product lines and generations of cars are served by one software platform. This is enabled by another "shift-left", the investment into architecture & platform development.

The V model for systems engineering has been another "best practice" in product development for quite some time. The SDV adds agile BizDevOps concepts to the traditional V model:

The main transformation here is the extension of the V model from product development to the operations phase – hence BizDevOps. Software needs to be maintained over the lifetime. This is not only required by regulations such as UNECE R155 / R156 for software-update and cyber-security management. It is also the basis of the SDV business model of selling software-based services after the initial purchase of the car. Monitoring of the fleet including collection of monetizable data and management of cyber-security threats is a required capability for the SDV business model.

The cloud-based software functions are typically not as safety-critical and real-time-sensitive as the embedded ECU functions e.g. in body or powertrain domains. For speed and efficiency, these cloud-based software functions do not require the complete rigor of the V model and can be developed according to modern, agile software engineering practices. In true DevOps fashion, the ALM environment (Application Lifecycle Management) provides continuous integration and deployment (CI/CD), so that changes can be tested quickly with test automation and deployed into the fleet with OTA.

Conclusion: Truly a Transformation

SDV transforms the automotive business model, the actual product and the engineering processes, methods and tools for SDV development. It promises substantial software-enabled revenues, but also requires massive investments into new business and technology capabilities.

NTT DATA offers comprehensive support for the SDV transformation int the automotive industry:

Automotive Consulting

  • Business Strategy & Transformation Consulting
  • Systems Engineering
  • Production & Aftersales
  • Cybersecurity

Technology Services

  • SW Development (Embedded & Cloud-native; Apps & Backend)
  • Infrastructure (Hybrid Cloud / Data Center; 5G)

Please find more information under Industry page Automotive.


NTT DATA Group Corporation
Global Marketing & Communication Headquarters
Shinsuke Yoshinaga, Ayaka Matsuzawa

Jens Krueger
Head of Global Automotive Engineering, NTT DATA

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