How OEMs are using data, AI and collaboration to transform O2D
Audi, Aston Martin, Genpact, and MSC Germany are reshaping the order-to-delivery process through transparency, AI-driven decision-making, and cross-functional collaboration.
In today’s automotive market, success is increasingly defined by how well companies manage the full order-to-delivery (O2D) process. From balancing customer expectations with working capital and cash flow to navigating disruption, automotive logistics is becoming a critical strategic function.
At ALSC Europe 2026, leaders from Audi, Aston Martin, Genpact and MSC Germany explain how end-to-end visibility, AI-driven decision-making and closer collaboration are transforming O2D. The focus is shifting from siloed optimisation to integrated, data-led decision-making across the entire supply chain.
Unlocking visibility across the end-to-end supply chain
There is a strong emphasis on bringing transparency across the entire O2D chain, so that teams can see impacts end-to-end and make faster, fact-based decisions.
For Audi, O2D management is a central condition for effectiveness, ensuring end-to-end control of vehicle logistics from customer order to dealer arrival. The OEM’s process differs through a holistic strategy, consistently networking procurement, finance and sales along a common target line.
Thomas Gensberger, head of supply chain steering order-to-delivery at Audi, emphasises that without a holistic view, automotive companies risk optimising locally rather than strategically.
“Crises are the endurance test for value contribution, and O2D passes this test because it makes the end-to-end control structure manageable."
“O2D is an end-to-end process, unified and standardised in the entire process logic, centrally controlled across locations and business units,” he says. “Our O2D process development is the link between planning, control and implementation. This is how we break down silos.”
Gensberger says that through optimising O2D, Audi as a whole benefits. “It increases predictability, reduces costs and enables us to act when the market dips or supply chains come under pressure,” he says. “My clear message is that without an end-to-end view, there is no reliable control system, neither in normal operations nor in the event of crisis.”
By having this optimised process, Gensberger says that efficiency comes through correcting less, rather than just running faster.
He explains that crisis management is a standard at Audi, and is structurally anchored in the OEM’s O2D process. An established Audi crisis team led by supply chain focuses on security of supply as a permanent control element. Clear logics exist from identified bottlenecks to defined measures, escalation levels, roles, priorities and decision-making paths. Rather than being dependent on individuals, the setup is anchored in structure, process and responsibility.
“Crises are the endurance test for value contribution, and O2D passes this test because it makes the end-to-end control structure manageable,” he adds.
This emphasis on visibility is echoed by Frederik Wexel, commercial director at MSC Germany. The logistics provider believes that transparency is more about timely insight than perfect data.
“For us at MSC, transparency does not mean that you perfectly know everything,” Wexel says. “It's more about that we know what has happened, that we eventually know what will happen and then basically translate that into the supply chain and take a decision together."
However, visibility alone is not enough. Wexel and the other supply chain leaders agree that translating data into action requires clear communication, standardised operational language, and skilled teams capable of interpreting insights across functions.
Early identification of deviations and communication around that enables faster, more effective decision-making, even if those decisions are initially unpopular. “One opportunity, from our perspective, is to bring visibility into the entire supply chain as early as possible,” he says. “Whenever you are anticipating a deviation from the plan, bring that information into communication to allow faster decision-making. We experience that making an early, even an unpopular decision is much better than delaying a decision or not making a decision.”
AI and agentic tools: Driving smarter O2D decisions
Artificial intelligence is increasingly central to enabling faster, more accurate decision-making in automotive logistics. Digital toolkits, mathematical optimisation and AI and agentic capabilities are being introduced to evaluate options and accelerate routine tasks.
At Audi, AI is already being applied to predict installation rates and anticipate supplier quality issues, helping teams identify risks before they escalate into disruptions.
But as Tanguy Caillet, global supply chain consulting leader at Genpact argues, AI’s true value lies in how it reshapes processes. Rather than simply adding new tools, companies must rethink how decisions are made and where automation can remove non-value-added steps.
Caillet explains that the agentic and advanced technology solutions company sees the end-to-end view of supply chain data like a “single pane of glass”.
“It’s like if you imagine you have all the data available on a big screen and you would be able to actually navigate,” Caillet says. “I think everybody's looking for that.”
Supported by AI and advanced analytics, this visibility allows organisations to simulate scenarios, balance competing priorities, and optimise decisions across cost, service, and risk.
For Martin Corner, executive director of supply chain management and logistics at Aston Martin, the opportunity lies in integrated business planning. While AI in O2D is still in the early stages of adoption, the company sees clear potential in using AI-driven tools to optimise production sequencing, manage risk, and improve responsiveness to disruptions, with mature proofs-of-concept and interest in deployment.
The OEM’s priority is an integrated business-planning solution, starting with S&OP, that can be extended with modelling and AI capabilities.
While data quality is a concern for Corner, he favours starting and cleansing data iteratively rather than waiting for an ideal data set. “Our data still requires significant improvement,” Corner says. “But I like the idea of actually, don’t wait for perfection, because then you’ll never start. Just get going and cleanse the data as you go along.”
But across the board there is consensus that AI must remain human-centric. Decisions may be supported by algorithms, but accountability and judgement remain firmly with people.
Balancing complexity with customer value
One of the most persistent challenges in automotive supply chains is managing complexity. For luxury carmaker Aston Martin, this is amplified by ultra-low volumes, high levels of customisation, and a global supply base delivering highly specialised components.
Corner highlights how design decisions, such as sourcing large, complex assemblies from distant suppliers, can drive up total cost of acquisition, such as rising logistics costs, increased lead times, and tied-up working capital. These challenges are often locked in early during product development, limiting the ability of supply chain teams to optimise later.
The solution, he argues, is to embed supply chain considerations earlier in product creation. By influencing design, sourcing, and packaging decisions earlier, OEMs can reduce total cost of acquisition while maintaining the premium features that customers value.
At the same time, both Corner and Gensberger stress that not all complexity is bad. The key is to distinguish between value-adding complexity, such as customer-facing features, and unnecessary complexity that adds cost without improving the customer experience.
“The key point, though, is that I’m not saying reduce all complexity,” Corner says. “The right complexity that does drive value is really important as well.”
Collaboration is key: OEMs and 3PLs at the table
A key part of optimising O2D is through deeper collaboration across the supply chain ecosystem. While OEMs have traditionally designed logistics networks internally, there is growing recognition that logistics providers bring critical expertise that should be integrated earlier in the planning process. Corner acknowledges that involving 3PLs in product and network design could help avoid inefficiencies and improve overall performance.
“If it is true partnership and we see the supply chain as the OEM and the logistics providers, then really they should be at the table doing this with us.”
“We could definitely be better,” Corner says. “Actually, our logistics partners should be involved in this scoping, not just the internal teams, because of that modelling of the logistics flows and the opportunities on packaging and the implications of what we're designing for the transportation. Yes, we have in our case a couple of internal people looking at these things, but the real expertise actually is out with logistics providers.”
Corner adds: “If it is true partnership and we see the supply chain as the OEM and the logistics providers, then really they should be at the table doing this with us.”
From the logistics provider perspective, Wexel emphasises the importance of long-term partnerships built on trust and open communication. By sharing data and insights more effectively, OEMs and logistics partners can co-design more resilient and efficient supply chains.
“We put emphasis on open communication, trust, and long-term partnerships with our customers because we believe this is the right mindset that we need to manage these increasingly complex supply chains that we are seeing,” he says.
This collaboration extends beyond logistics to include procurement, manufacturing, and sales. Breaking down organisational silos and aligning incentives across functions is essential to achieving true end-to-end optimisation.
From data silos to a holistic O2D strategy
Despite progress in process integration, data fragmentation remains a major barrier. Many organisations still struggle to bring together information from multiple systems quickly enough to support real-time decision-making.
The shift towards integrated data platforms, supported by AI, is helping to address this challenge. By consolidating data and enabling faster analysis, companies can move from reactive to proactive supply chain management.
At Audi, this approach enables more precise production planning, better alignment with logistics constraints, and improved delivery reliability. For Aston Martin, it offers the potential to balance cash flow, customer demand, and operational efficiency in a more holistic way.
Ultimately, the goal is not just better data, but better decisions made faster, with a clear understanding of trade-offs and their impact across the entire value chain.
End-to-end O2D management, supported by visibility, AI, and collaboration, allows OEMs to navigate disruption, optimise performance, and deliver on increasingly demanding customer expectations. For OEMs that can successfully integrate these elements, O2D is a competitive advantage.
