Tesla senkt die Preise drastisch – VW, Ford, BMW und Co. reagieren unterschiedlich. „Alle kommen aus dem Verknappungsparadies“, meint Jan Burgard von Berylls, „jetzt aber haben wir wieder Überkapazitäten und die Lieferketten haben sich entspannt. Der Wettbewerb spielt sich im Volumensegment ab.“ Der Vorsprung im batterieelektrischen Zeitalter ist nur mit dem richtigen Timing möglich. „Make or break!“ Ist Elektromomilität Chance oder Sargnagel für die Unternehmen? Burgard rät: „Grundsätzliche Strukturen in Frage stellen, sonst kommt man ins Hintertreffen – unabhängig von der Antriebsform.“

• Berylls Equity Partners schließt seine dritte Akquisition ab und übernimmt die Anteilsmehrheit an Hatz Components mit Sitz in Ruhstorf an der Rott.
• Als strategischer Partner der Motorenfabrik Hatz wird Berylls die Führung bei der vollständigen Herauslösung und bei der Weiterentwicklung von Hatz Components als eigenständiges Unternehmen im globalen Markt für hochpräzise Komponenten für Industriemotoren übernehmen.
• Nach der Übernahme der MEKU-Gruppe und der Heinrich Huhn Gruppe erwirbt Berylls ein weiteres Unternehmen mit einem zukunftsträchtigen Produktportfolio und einem nachhaltigen Wachstumspotenzial.

INTRODUCTION: CIRCULARITY IN THE AUTOMOTIVE INDUSTRY

Rising cost for raw material, insecure supply chains and ever-increasing pressure on sustainability goals: The need and the upside for sustainability in the value chains are increasing drastically. Recalibrating the value chains and transforming towards a circular economy becomes a must for those who want to last.

Four pillars define the circular economy in the automotive industry: Refurbishment, Remanufacturing, Reuse and Recycling. These 4Rs differ according to the product level which they address (vehicle, module, or parts) and the respective activities: All allowing for a better utilization of resources. To make the different elements work two aspects are critical: A functioning ecosystem and suitable products.

While refurbishment is a powerful lever on the vehicle-level and recycling is the way to go when it comes to raw material on a part-level, remanufacturing and reuse are in scope when considering the module or component-level. While reuse is often applied to second-life applications and parts where a certain wear is acceptable, remanufacturing is a powerful approach when modules lose certain performance characteristics over time but can be reconditioned to return to their original purpose.

For automotive supply chains, the past few years have been exceedingly volatile, with varied shocks overlapping. The impact of Covid-19 and the semiconductor crisis seem to have passed, however shortages of raw materials (particularly those used in battery-making) and geopolitical risks including the ongoing war in Ukraine, have not gone away.

In addition to external shocks, the supply chain is also being fundamentally reshaped by the transformation of the auto industry itself. As vehicles become increasingly software-enabled and electric, the balance of power between OEMs and suppliers has shifted. As we set out in previous articles in this series, true collaboration is essential starting in the development stage, and selecting the right supplier can make the difference between success and failure.

Effective risk detection and risk mitigation strategies are therefore becoming increasingly critical for both OEMs and suppliers to ensure their long-term resilience and success. When the next crisis inevitably hits, how will the supply chain hold up? Too many mitigation strategies still address only short-term and obvious risks. Rarely do either OEMs or suppliers think more radically, taking steps such as buying a mine to ensure supply of a key mineral, acquiring lower-tier suppliers or designing more value-creating components in-house.

Here, we look at how automotive companies can first harness the power of data to identify risks at every level of their supply chain. Armed with a clear and detailed picture of the risk landscape, they must then act to stop problems arising, typically in three categories: with the supplier, with their own product requirements, and with their own organizational processes.

Risk detection: Know your supply chain

As described above, risk has increased in automotive supply chains as companies have been simultaneously hit by external disruption and the industry’s own technology changes. Electrification and a greater share of software in vehicles demand new suppliers, new raw materials and new types of supplier relationships.

As the number of suppliers increases, the risk of production stoppages increases, because disruption to one link in the supply chain may bring the entire production process to a halt. At the same time, the increasing product and process complexity means automotive companies are working with new technology suppliers that enjoy a near-monopoly position in some technologies. This has created greater dependency by OEMs, which cannot reduce their risk by having multiple suppliers.

The result of all these factors is that early risk identification and analysis is essential. Data holds the key: as Figure 1 below shows, there are eight steps across three layers to follow, starting with data collection (internal, external and historic), followed by analyzing and classifying the data, and lastly using it for risk assessment:

ACCESS RISKS OF CRITICAL SUPPLIERS
After identifying and ranking the most critical suppliers, risks are assessed in a risk matrix for further measure definition.

Figure 3: Eleven key supply chain risk mitigation measures

Here we take a more detailed look at how OEMs and suppliers can apply one of the key measures in each of the three action areas:

Supplier: b(u)y passing the Tier-1 supplier

To ensure auto companies have adequate supplies of essential parts even in times of crisis, radical risk mitigation strategies must be on the table, even those which require a higher degree of capital tie-up and longer-term planning. These include buying critical Tier-n suppliers outright or taking a majority stake to gain direct to control. This may mean buying a raw material producer or a mine supplying a vital resource. Companies can also make non-cancellable and non-refundable committed purchase agreements to buy large quantities, of lithium for example, and act as a dealer by distributing the raw material to their Tier-1 and 2 suppliers. Contracting directly with the manufacturer of a high-value part for which a Tier-1 supplier usually does the integration, without an agreed purchase quantity, is another option. The overall aim is to be a priority customer for deliveries, with an increased level of confidence in securing the necessary components, even during times of crisis.

We expect strategic co-development partnerships, as well as co-investments and joint ventures, with critical subcontractors to become increasingly common as OEMs and large suppliers prioritize stable supply chains. These measures are out of the comfort zone of most automakers, which have established arm’s length supply arrangements over decades in the search for ever-greater efficiency. But change is now unavoidable.

Supplier relationships have long been critical for auto manufacturers. OEMs that can work in partnership with suppliers to deliver innovation, quality and cost control are the companies that thrive.

Yet the industry crisis that accompanied the Covid-19 pandemic showed the weaknesses in many automotive supply relationships. Companies that had already built collaborative relationships with suppliers of key software and electric technologies passed through the crisis relatively unscathed, and even thrived. However, companies that relied on older inflexible supply models based on rigid contractual obligations lost production volumes and market share.

This should have been a wake-up call that the established auto supply model was breaking down. Manufacturers need to rethink their supplier selection processes to adapt to a faster moving world with shorter innovation cycles.

Rethink the purchasing skillset

Supplier selection is often determined by the skills and assumptions of the OEM purchasing function – and in many cases these skills have not changed for years. There is firm evidence that purchasing managers in traditional OEMs continue to lack the cultural and technical skillset needed to build new technology supplier relationships, while emerging OEMs are more likely to ensure their purchasing staff have a new technology background and an understanding of these suppliers.

This is confirmed by our analysis of more than 100 job descriptions for OEM purchasing roles which shows that among newer OEMs, around 50% of roles specify new technology experience, while no more than 25% of established OEM job postings specify knowledge of these technologies. New technology OEMs are also more likely to emphasize technology rather than automotive experience, while established OEMs are likely to focus on automotive purchasing experience alone.

With a typical short job rotation period in established OEM purchasing roles, it is unsurprising that supply managers do not have time to fully absorb and understand new automotive technologies, and lack the motivation to make long-term changes to collaboration strategies.

The result is that established OEM supplier selection and management is optimized for a world that is disappearing. Existing supplier selection principles are designed to reduce risk – but they cannot respond to the new risk of losing the capacity to innovate in new automotive technologies.

The Berylls Group has joined the Eclipse Foundation and will support the Software Defined Vehicle (SDV) Working Group in particular. The Eclipse Foundation is dedicated to supporting open source projects where the source code of the software is available to the general public and is jointly developed, maintained and improved by the contributors.

Founders of the SDV Working Group include Microsoft, German suppliers Bosch, Continental and ZF. For Berylls, a leading company in the field of digitalization and innovation in the automotive world, it is an important step to contribute its own expertise to one of the most renowned open source organizations worldwide.

Christian Kaiser, Partner at Berylls Strategy Advisors adds: „We are convinced that the exchange of knowledge and experience within the Eclipse community will play a crucial role in shaping the digital future. We already see leading technology companies using more than 50 percent open source code, but the automotive industry is still struggling with this trend. This is something we as Berylls Group would like to actively change.“

Dr. Matthias Kempf, Partner at Berylls, said, „By joining the Foundation, we want to help drive collaboration in a cross-industry open source community, and accelerate progress in digital technologies in the automotive sector.“

As part of the Eclipse Foundation, Berylls will focus specifically on developing solutions for the automotive industry. We aim to play an intermediary role between all those companies working on SDV issues. As a neutra-les Eclipse member, Berylls can play an important role in maximizing parallel efficiency and mutual collaboration. In numerous projects with leading OEMs and suppliers, Berylls has defined the value-added contributions, software architectures, and delivery and control models of modern SW organizations and put them into practice in large-scale transformation projects. The topic of Open Source Software (OSS) is the next logical and consistent step to drive transformation not only in iso-lated projects with individual companies, but with and for the automotive industry as a whole.

Berylls believes that the greatest leverage for incumbents lies in larger-scale collaboration rather than pursuing isolated strategies in fields with low differentiation potential and scarce developer resources.

Currently and in the past, Berylls has worked with a number of different Foundation members, including: AVL, Bosch, CARIAD, Continental, Elektrobit, ETAS, IAV, LG, Luxoft, MBTI, MSFT, Toyota, T-Systems, Vitesco, VW, ZF. Berylls‘ membership in the Eclipse community will further deepen this collaboration in the future.

When times get hard, you find out who your real friends are – and automotive suppliers did not receive as warm a welcome as they might have expected when they sought higher prices from OEMs in the face of lower sales volumes and a jump in costs last year. With a shortage of components for new cars, OEMs focused on higher-margin vehicle sales and protected their profitability, but declined to pass their pricing power down through the supply chain. Figure 1 below shows the difference between supplier and OEM margins in 2022 as a result:

Procurement: The hunt for cost efficiency and the right partnerships

The automotive industry has faced significant external challenges over the past three years, starting with the pandemic and followed swiftly by the chip crisis, the war in Ukraine, and inflation. Unfortunately, many automotive supply chains were ill prepared to handle these severe and sometimes sudden challenges. However, to deal with the disruption, we have seen a move away from purely transactional relationships between OEMS and suppliers, and toward strategic collaborations and joint requirements engineering. Greater pricing flexibility within contracts will become increasingly necessary and work in both directions, to enable companies to adapt to the ever-changing market conditions.

To detect potentially critical situations earlier and jointly find solutions, it has been important to increase visibility over the financial and operational performance of lower tier suppliers. In addition, divisions between development and purchasing have been broken down, bringing in new cross-functional ways of working.

The benefits have been to reduce procurement costs and improve quality. Cost efficiencies can be achieved by integrating supplier knowledge into the product specification, and quality improves by considering design-for-manufacturing with the input of suppliers. Both elements change the competitive focus in the bidding process from price alone, to the development of concrete improvement proposals.

Building a collaborative procurement network means OEMs playing a role in the design of the supply chain through all the various tiers of suppliers, to ensure the availability of materials and components. All parties should champion flexibility to ensure cost efficiency and a resilient supply chain. Drawing on the knowledge of each partner also avoids risk and unnecessary spending. Transparency is the responsibility of everyone and becomes a virtuous circle – if OEMs don’t exploit supplier transparency, it becomes an opportunity rather than a burden for suppliers, which in turn makes them more inclined to be open.

The lessons of the past three years have highlighted four key steps to enable collaborative risk management and crisis response in procurement:

• Joint risk assessment: OEMs should work collaboratively with their suppliers to identify and assess potential risks in their supply chains, to develop a shared understanding of the potential issues they face and work together to mitigate them. Digital industry platforms are already the ideal starting point 
• Contingency planning: Collaborative contingency planning to prepare for potential crises and minimize their impact means developing alternative sourcing strategies, identifying backup suppliers, and implementing supply chain risk management tools.
• Early warning systems: Early warning systems can help companies detect and respond to potential risks and crises before they escalate. 
• Loyalty and partnership: Furthermore, do not devalue your Investment in a long-term cooperation by choosing another partner for a new variant and starting all over again

In the transition to electromobility that is already underway, traditional automotive suppliers are among the businesses most at risk from disruptive change. With limited resources, they must engage with new technologies. They must prepare for some specialist component manufacturing to become vertically integrated in OEM operations. And they must cope with a new business model where much of the value in automotive manufacturing moves away from hardware to software.

All of these challenges demand proactive approaches to their relationships with capital markets, considered cost-reduction strategies, and a new emphasis on partnership for innovation.

“ChatGPT is a large language model developed by OpenAI, capable of generating human-like responses to natural language input. It is trained on a vast amount of data and can be used for a variety of applications, such as chatbots, language translation, and text completion.”​

This is how ChatGPT describes itself when you ask the artificial intelligence (AI) chatbot “what is ChatGPT?” It’s pretty accurate – although the description covers only a limited part of the tool’s range of uses. It is also out of date – it doesn’t mention, for example, that the latest version, which uses the GPT-4 language-processing model, can also extract information from images to produce answers.

Without a doubt, ChatGPT exemplifies the potential that AI has to revolutionize the way we live and work. But what specifically does this type of generative AI has to offer the operations teams of automotive OEMs?

Our view is that there are at least two big advantages: firstly, the language model can be trained with huge amounts of information, identify trends invisible to the human eye, and can “interpret“ the results, to make recommendations or draw conclusions on its own.

Secondly, it has an easy-to-use interface because it deals with natural language. ​It can therefore be used by engineers and operations specialists with no background in AI to make informed decisions in real-time. In addition, the ability of newer versions to analyze information in the form of images as well as text, offers limitless potential in automotive operations.

In this article we will look at six potential Operations use cases for generative AI tools. However, it is also important to sound a note of caution about the risks posed by using machine learning algorithms. Like all forms of artificial intelligence, the quality of the information provided, or decisions made, relies on the quality of the data it is trained on. And even if every single piece of training data is correct, the AI could still come to the wrong conclusions because of the way it combines them. Currently ChatGPT, for example, does not highlight different levels of assurance in the results it delivers.

Complex production issues will therefore still require human expertise and intuition. Knowing the cases in which such human expertise is required is unfortunately not easy, as it needs precisely the subject matter expertise that a user of ChatGPT may not have.

Another disadvantage is the potential security risk – we would not recommend integrating sensitive product and production data with generative AI on a public cloud service.

As a result, OEMs and suppliers must ensure that employees are aware of the risks involved in leveraging the technology, and have the appropriate data classifications, security measures and usage rules in place to protect confidential information.