No Match Found
Software continues to be a focal point of differentiation for the automotive industry. About 100 million lines of code underlie the operation of a modern car. Compare that with a passenger jet running 14 million lines of code, or a fighter jet with about 25 million. Automotive software, a $22 billion industry with a 13% compound annual growth rate, powers three principal vehicle-innovation trends.
Original equipment manufacturers (OEMs) are increasingly investing in electrification of vehicles and semi-autonomous/autonomous technologies. Meanwhile, nearly 80% of consumers in the US are willing to pay a premium for semi- or fully autonomous vehicles, and many companies are targeting that market. For example, many automotive OEMs and their ecosystem of tier 1 partners are planning to offer new on-demand features that customers can upgrade, such as a hands-free driving system or improved handling. CASE (connected, autonomous, shared and electric) technologies do not stop there. Additionally, automotive OEMs and tier 1 partners that have adopted a software-focused model have adjusted their processes and their value chains to align with the technology, such as predictive maintenance both on the shop floor (e.g., minimizing unplanned downtime) and in the vehicle.
Given the unabated threat by hackers and data breaches, leaders in the traditional software industry are bolstering the security of both internal systems and connected products. On average, implementation of an end-to-end cybersecurity management system takes 2.5 years, demonstrating the auto industry's commitment to protecting cyberattack surfaces. Increased connectivity can potentially usher in great cyber risks, including those surrounding driver information and vehicle safety. PwC’s Global Automotive Cybersecurity Management System Survey found that 100% of companies anticipate a significant uptick in vehicle cyberattacks in the future, with 90% of OEMs believing that advanced security within the vehicle’s platform is a competitive advantage.
As more software is integrated into vehicles, it is becoming clear that cybersecurity is no longer the sole responsibility of the auto OEM. With most vehicle manufacturers procuring software and related technology from third-party suppliers, cyber protection is now a shared imperative spanning the automotive ecosystem. Leveraging a robust approach to establish internal and external controls is essential to achieving automotive data security.
The next generation of vehicles has led to the emergence of new revenue-generation channels stemming from a proliferation of data available to OEMs and their suppliers. Automotive data monetization is expected to soar over the next decade to about $20 billion in 2030. Additionally, we see an increase in the adoption of the software-as-a-service (SaaS) business model throughout the industry, with the rise of software providers that provide a cloud-based subscription for over-the-air software updates to drivers.
Many companies experience challenges adjusting to the new demands of implementing software technology and, as a result, find it difficult to capture the full benefits such implementations can yield. Companies across sectors can experience two key areas of difficulty in software research and development (R&D): first, organizations struggle to balance project demand with available skill sets; and second, improving the return on investment of software projects continues to be a common pain point.
The auto industry has yet to fully integrate software as a core competency, often outsourcing to fill this gap, especially in software R&D. To compound matters, the industry competes with technology and similar sectors for the same talent pool. Moreover, coding in the industry has yet to fully adopt leading practices, leaving many auto companies with monolithic architecture and designs that can bog them down with complexity and waste. The typical system consisting of multiple electronic control units (ECUs) is still predominantly used in today’s vehicles. This is becoming problematic on several fronts: untenably high volumes of software code, validation complexity, lack of integration and supply chain risk. Solving these challenges is top of mind for leading automakers, who are not only rethinking the role of the OEM, but also of technology partners. We are observing leading practices including emphasizing workforce upskilling, prioritizing tech roles in recruiting, and partnering with leading technology enterprises — all to create unique, software-powered, next-generation vehicles.
While there is room for improvement in executing and increasing return on investment (ROI), reading the market and understanding customer preferences and needs also hold opportunities for software-supported innovation in the industry. Many companies that lead in software development tend to share two strengths: cultivating an in-depth knowledge of customer needs, and systemic research and forecasting of changing consumer demand. Automotive software leaders distinguish themselves by prioritizing next-generation digital and connected products to drive growth and satisfy customer needs. The wider value chain can — and ought to be — used to drive that growth. For example, one new electric vehicle (EV) maker has partnered with a video gaming company to embed a human-machine interface into its vehicles, providing a game-like simulation to enhance driver experience. This software-enabled feature, along with numerous others, differentiates the brand as customer-centric.
Automotive OEMs can transform their organizations, keep pace, and meet customer demands through the development of an expansive and extensive software innovation program. To achieve that, we offer the following recommendations.
Recommendation 1: Build a software center of excellence and carefully assess opportunities to innovate both internally and through external partnerships. As vehicles become more software-centric, OEMs should consider changing how to platformize their vehicles and how to build and integrate software functions into their traditional organization. These changes represent the core competencies of a software center of excellence (CoE). A software CoE should also help streamline an enterprise’s software capabilities, objectives, processes and talent mix. Having a CoE can also help create a cohesive and unified vision for the organization’s strategy and approach to software.
Working with suppliers, whose role in the auto ecosystem is constantly evolving, will also be critical for OEMs, as they anchor their strategies to build software as a competency. Tier 1 suppliers also need to excel beyond hardware capabilities and should be assessed by the value they bring to a software-centric model. Incorporating technology partners to complement an OEM’s software CoE can exploit synergies that can help deliver next-generation vehicles.
A luxury car manufacturer is building in-house software capabilities to step closer to the goal of bringing its own operating system to market. To accomplish this, the company is hiring more than 3,000 new employees and outsourcing non-core software capabilities to suppliers. The company is demonstrating how to weave newer, software-dominant functions — such as software engineering, product management, and user experience — into the traditional OEM organization. Examining this approach to building a more software-focused operating model requires the right organization structure, team building, and supply base.
Recommendation 2: Modernize and platformize software development that helps enable the OEM-supplier relationship to drive collaborative innovation. Leading cloud service providers and top players in the high-tech industry have led the way in modernizing their software development capabilities. Similarly, automotive companies should transition to microservices-based, cloud-integrated, containerized architectures for software applications, both embedded and standalone. They also need to adopt iterative development practices, continuous code integration and deployment (CI/CD), and security integrated development–operations. Bolstering these capabilities could help increase velocity that can be deployed via over-the-air updates from the cloud to the vehicle. As a priority, companies should level up vehicle connectivity via adoption of an API (application programming interface) -first approach, which requires embedding API competencies within the skills mix. With APIs as the ultimate digital integrator, development teams can focus on software reusability and scalability.
OEMs do not have to go it alone — engaging with experienced providers to enhance internal software capabilities can typically accelerate transformation more swiftly than a “homegrown” approach.
The electric vehicle (EV) manufacturer has partnered with a leading hyperscaler cloud provider to utilize a combination of cloud-based offerings to establish an agile software development program. Acquisition of this technology to build agile capabilities has enabled virtual collaboration, improved iteration speed and software performance, and reduced waste in the development process.
Recommendation 3: Invest in data science and security to build better, more secure products. Software provides auto manufacturers with an abundance of data to leverage and better engage with the market. To build vehicles that deliver high-quality and improved customer experience, data science and analytics should be leveraged to yield the most powerful insights. For example, there continues to be a lack of consistency in the industry surrounding cybersecurity. This pressures auto manufacturers and tier 1 suppliers to invest in leading security practices and earn customer trust regarding the security of their data. OEMs should already be taking actions to set up initial system architecture across the entire value chain. Standing up a functioning architecture is key to providing software to customers with a desired level of security assurance.
As a supplier of software to the automotive industry, a leading chip vendor is using multiple technologies embedded within its programs, including deep learning and AI to collect data in self-driving vehicles. The design of its software allows for the machine to process and react to the collected data while protecting both the vehicle and the driver’s privacy.
Recommendation 4: Reorganize to support new business models. A shift in the software development operating model to drive new features and subscription-based monetization could bring about changes to neighboring functions. Such knock-on effects should be planned and accounted for to support a streamlined and effective software development pipeline. Automakers should evaluate support areas (e.g., finance, operations, customer success, supply chain) and processes (e.g., order-to-cash, training, financial reporting, make-versus-buy) to determine where adjustments in capabilities and workflows are needed. With software as the main focus, the talent mix and available training will also be critical to an organization’s success surrounding new vehicle launches and improvements. A robust software operating model will also impact the larger value chain, confirming that suppliers and partners are integral parts of bringing software to the forefront — and are not hampered by obsolete practices.
As part of its new EV-centric business unit stand-up, a leading OEM is dividing its organizational structure into two components: EVs and traditional vehicles. A key process impacted by this split is financial reporting. By having an EV-centric division, the company can manage its P&L in a way that best fits this new technology, rather than retrofitting an existing process that has insufficient synergies, such as material costs and R&D expenditures.
The transformation from hardware-focused to software-focused is an arduous journey, requiring significant commitment from leadership and financial perspectives. Both suppliers and partners have at least as much vested interest in becoming software innovators as traditional OEMs — they are integral players in bringing software front-and-center to automotive. Despite the challenges this transformation brings, the potential benefits far outweigh the costs. For automotive OEMs and partners that wish to better engage with the market, provide cutting-edge vehicles and generate new revenue streams, legacy models should be challenged to bring software to the core of innovation.