Industry Voices | Reinventing the Automotive Value Chain for Next-Gen Mobility
While we’re seeing supply chain resilience initiatives with some automotive customers, efforts are not yet collectively executing at scale, which is coming through in risk scores.
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The automotive industry is on the cusp of a major transformation, one that is defined by the rise of software defined vehicles. As we work toward the transformational opportunities next-generation mobility offers, it is crucial to assess the readiness of our industry’s supply chain to meet the demands of this new era.
The industry’s recovery from the global supply crisis is converging with the profound importance of semiconductors to next-generation mobility. According to BCG, chip content per vehicle will continue to grow by approximately 7% annually, reaching 1.5-2 times the current level by 2030. Yet KPMG’s survey data shows that 45% of automaker executives outside of China expressed extreme concern about access to semiconductors.
Challenges and Risks Facing the Automotive Industry
Flex’s recent analysis of supply chain trends, along with proprietary cross-industry data from our Joint Risk Management application – which leverages AI/machine learning and information from 5 million components – reveals that the automotive industry’s supply chain risk score is over two times higher than other industries.
To shed light on the automotive industry’s challenges, it might be helpful to draw a parallel with the AI-driven growth of the hyperscale data center industry. Both industries are undergoing technology transitions driven by high-performance silicon, which are transforming their respective landscapes.
Generative AI’s rapid adoption is boosting demand for hyperscale data centers, with McKinsey forecasting 10%-12% CAGR growth through 2030, led by major players like Google, Microsoft, Amazon and Meta. The power requirements for a typical data center rack is significantly higher, growing from 16 to 20 kilowatts today to potentially 250 kilowatts soon.
The rise of the software-defined vehicle follows a similar trajectory, with BloombergNEF estimating that for an EV equipped with L4 highly automated self-driving, up to 46% of its power consumption is from the compute hardware – a sharp increase from 5% for L3 systems. Both software defined vehicles and AI data centers require new architectures to manage this need for scalable, powerful compute – which also requires us to rethink the impact on the supply chain.
Our data point to several critical areas where automotive is falling behind data centers. While we’re seeing supply-chain resilience initiatives with some automotive customers, efforts are not yet collectively executing at scale, which is coming through in risk scores.
In a side-by-side comparison of 90,000 parts across data center providers and 70,000 for automotive, these metrics have the biggest gap:
Stockout (25% higher risk): Uses real-time distributor data to check if current stock is available for parts.
Availability (15% higher risk): Measures historical data of similar parts within the same commodity to predict likelihood of future shortage to occur.
Lead time (10% higher risk): Measures the variability of lead times benchmarked across different parts within the same commodity group.
Adopting the Cloud Industry’s Supply Chain Best Practices
There are three key levers we believe the industry can adopt from cloud to make meaningful progress toward building resilience: regionalization, multisourcing and collaboration. While these solutions are not new to the automotive industry, the data underscore that we are not executing at the speed required to avoid the next supply crisis.
Regionalization: Manufacturing in-region is becoming table stakes to overcome risks to business continuity arising from supply chain disruptions, tariffs and geopolitical tensions. Regionalization is much more than a defensive strategy; it also offers benefits such as improved responsiveness to regional customer demand and reduced carbon footprint.
Multisourcing: Our data tell us automotive is multisourcing at less than half the rate of other industries. The impact of this lack of multisourcing is evident when comparing the component level of an enterprise compute rack from a leading hyperscaler to a central compute model from a global OEM, with the availability risk being 35% higher for the automotive product. Maximizing a smart multisourcing strategy across the bill of materials enables automakers to increase agility and resilience, resulting in fewer line stoppages, competitive pricing and faster time-to-market. While it may involve upfront costs and effort, the benefits far outweigh the drawbacks and serve as an insurance policy for automakers.
Collaboration: Just as data center companies have accelerated their innovation curve through an evolved approach to partnering with their supply base ecosystem, automakers must do the same. The automotive ecosystem needs to accelerate cooperation much earlier in the cycle – by years, not months. Partnering early in the product development lifecycle will empower us to assure on-time launches, supply-chain readiness and robustness, and enhance our ability to respond faster to shifting market conditions to deliver at scale.
Working Together to Pave the Way for a Successful Future: The automotive industry is at a critical juncture as it prepares for next-generation mobility. To deliver on this unprecedented market opportunity, our industry must work as an ecosystem to build a more resilient automotive supply chain, because no single player can make it across the finish line alone. By adopting best practices from other industries, such as regionalization, multisourcing and collaboration, we can reinvent the automotive supply chain and deliver on next-generation mobility.
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