Stellantis: People and collaboration to drive future automotive supply chain strategy
Stellantis leaders Carlos Vazquez and Benoit Gaucherand outline a shift from cost-driven logistics to AI-enabled, multimodal and human-centric supply chains, with resilience and partner collaboration at the core.
Automotive supply chains are entering a new phase defined by collaboration and partnership, rather than solely leaning on AI and digitalisation, according to Stellantis leaders. Speaking at ALSC Europe 2026, Stellantis’ Carlos Vazquez, vice-president of global purchasing and supply chain, and Benoit Gaucherand, senior manager for enlarged Europe aftersales transport network design and cost control, describes a journey from lean, cost-focused logistics to today’s AI-enabled, “anti-fragile” networks that learn and adapt in real time.
Vazquez explains that each era of best practice in automotive supply chains has led to growth and learning. In the 1980s and ‘90s, best practice focused on lean and cost optimisation. “We were on a hangover from the first oil crisis, and focus at the time was to produce and produce cheap,” he says. “From there we moved to the ‘90s to 2000s and at that time the focus was on ERP, to have visibility of stock and orders, and to set up S&OP processes. There was a need to focus on the future, to anticipate and plan and work on the ‘what if’ scenarios.’
Then, the 2000s were driven by customer centricity. “So, it was really a period of agility that has changed completely the way we move,” he says. “This agility changed when Covid arrived.” Vazquez says that with the arrival of the pandemic, “resilience moved from a PowerPoint in a boardroom to every single day meetings and activity”. He says this caused Stellantis to come up with its “anti-fragile” approach, which he describes as being able to fail, learn and grow on an incremental approach.
AI is a core part of this “anti-fragile” era that the OEM is currently in, using the technology to map the supply chain through digital twins, to predict, anticipate and prescribe through predictive AI, and to improve efficiency through AI-powered automation. But he asks: “What is the next frontier in best practice in the supply chain? What is the future?”
The future era of the automotive supply chain
“When AI has all the answers, what is really important is the question,” Vazquez says. While AI is a must in today’s supply chain, he explains that without people and cooperation, its benefits cannot be fully reaped. “The moment that AI has all the answers, what we put in the centre is the people who will ask the questions, and the cooperation across companies and across the value chain, because we’re all working in AI siloes in our own companies,” he adds. “Technology is a must, but it is only an enabler.”
Stellantis is moving into this new era through a framework developed by the supply chain and purchasing teams, known as the Engaged Program. The programme runs over the course of a year and involves teams across the OEM’s value chain consistently meeting and sharing learnings.
Gaucherand explains how the programme builds trust and collaboration with Stellantis’ supply chain partners. “We have an evolving market with new challenges every day and new crises, it’s complex and competitive, but can we do it alone. We are humble and we know we can’t do it alone; we need our partners because they have skills and experience and they can bring a critical view on what we are doing.
“We need to meet more regularly and face-to-face like we are doing now, we need to better understand our constraints and processes to exchange our way of working, to codesign and bring value all together,” he says.
The first stage starts with a remote townhall, where a short review of the previous year’s learnings is shared. Then, targets and expectations for the coming year are shared, including trends and expected volumes, key projects, and any potential impacts on partners. Partnerships are also reviewed with RFQ to give visibility and build trust.
Throughout the year, operational reviews will be completed, with regular KPI discussions.
And finally, Booster Days are a key part of the programme, where Stellantis and members of its supply chain partners meet in person at one of the OEM’s plants or warehouses. Gaucherand says these Booster Days are the most important part in the Engaged Program, explaining what they consist of.
“These days are based on four pillars,” he says, with the first being a short presentation of any new information that is valuable to the partners. Then, they are given a discovery tour, so that Stellantis’ partners have a better understanding of what the OEM is physically doing on the shop floor, including how parts are picked and prepared for shipping. Individual meetings with purchasing and operations then take place, with the aim of improving together and being more efficient. And the days close with networking, allowing relationships to be strengthened. “I think this part is the main point, because we can have all the AI we want but if we don’t have the people behind it, then what is AI,” he says. “Knowing each other and coming together can bring value."
Automotive supply chains in Europe: Stellantis, Volvo Cars and DSV on AI, data and resilient logistics
In a panel, Vazquez joins Sean Bricknell, head of performance office, supply chain at Volvo Cars, Jost Hock, vice-president of global key accounts automotive, commercial management at DSV, and Tobias Fenzl, global director, key account at DP World to further discuss how to be more connected, collaborative and strategic to meet the needs of a changing European automotive industry.
Industry challenges and the need for change
Supply chain instability: The panel agree that traditional supply chain models and sourcing methods are insufficient in the current environment. The industry needs to adapt to constant change and model it effectively.
Data and information flow: There is a need for good, trusted information that flows freely between partners. The current data analytics phase is intense during RFQs but often stops afterward, leading to gaps in ongoing processes. Data cleansing remains a significant challenge, consuming most of the time in data analytics.
Mid-term planning gap: There is a "U-shape" situation with abundant data for the present and past, and long-term future (5+ years), but a significant gap in reliable data and visibility for the mid-term (1-2 years). This gap complicates building relationships and common futures with partners.
Anticipation in a VUCA world: In a market characterised by volatility, uncertainty, complexity and ambiguity (VUCA), the range of scenarios is wide, making it difficult to prepare for unforeseen events like the Suez Canal blockage. The challenge lies in anticipating effectively and maintaining the energy to plan, even when plans may need to be rewritten.
Strategies for resilience and agility
Ecosystem approach: Volvo Cars envisions a living, self-evolving network that integrates all players. This ecosystem relies on trusted information shared among partners.
Orchestrating the present: The focus should not only be on predicting the future but also on mastering the orchestration of the present.
Collaboration and data integration: Collaboration needs to be lived better, moving beyond theoretical discussions. A common source of truth, supported by AI and IoT, is essential for building trust and ongoing data models. LSPs possess significant data (e.g., DP World's ports and terminals data) that needs to be collaboratively integrated for more resilient solutions and better pricing.
Digitalisation and data-driven decisions: Digital signals must replace large buffers to achieve resilience affordably. Information from partners is crucial for flexibility in replanning and maximising output. Volvo Cars invested heavily in a data transformation journey in late 2022, establishing a strong foundation of standardised, governed, AI-ready data.
Moving supply chain "left" in product strategy: Supply chain teams are increasingly involved early in product strategy, influencing part design for logistics, future cycle plans, and location studies for new car manufacturing. This early involvement helps shape sourcing, manufacturing, and investment strategies, protecting margins and strengthening competitiveness. Volvo Cars is systemising this process to ensure all players consider supply chain impacts on future products and automate data usage for faster, better decisions. Stellantis also aims to anticipate and be involved in early stages, focusing on packaging design for transport and network design for resilience.
AI and technology adoption
AI as a support tool: AI supports data analysis but human first responders remain crucial in guiding operations during crises. AI brings data analytics into hyperscale, but data cleansing still takes the majority of the time.
Proof of concept and continuous learning: Testing and proof of concept are vital, as unexpected values can be discovered even in failures. An example from 2013 involved a control tower for container monitoring, which initially aimed to notify customers of delays but later revealed the value of a clean database for network modeling and understanding challenges.
Trust in AI results: There is a need to build trust in AI-generated results, as people tend to question them more than human-derived analyses. Education is necessary to help people accept and utilise AI outputs effectively.
AI upskilling: Volvo Cars is investing heavily in mass AI upskilling across all employee levels to federate AI and empower teams for future industrial operations.
Business-driven AI: AI and data initiatives need to be driven by business needs to leverage their full potential. A mix of business expressing needs and IT bringing ideas is essential for successful implementation.
Partnership and collaboration
Win-win relationships: Partnerships must be mutually beneficial for both OEMs and LSPs. The challenge is to measure this win-win over the long term, balancing daily, weekly, and quarterly results with future revenues.
Transparency and information sharing: Trust is built on transparency, requiring partners to share more information than historically. Identifying a set of historically hoarded data and sharing it both ways with a partner can open future opportunities.
Constant partnership approach: The partnership should be continuous, extending beyond the RFQ phase and initial contract. It involves constant adaptation and preparation for changes and crises.
Mindset shift: A resilient and anti-fragile mindset is needed on both sides to understand the constant need to evolve and adapt. This mindset fosters collective intelligence and collaboration.
Outcomes of Stellantis’ Engaged Program and Booster Days
The new programme is already bringing evolution to Stellantis’ supply chain and shaping operational and logistics decisions. Stellantis now moves 34% of its outbound volume by rail, part of a wider push to shift towards lower-emission transport modes across Europe. “We are very committed to shift as much as we can to low emission transport modes,” Vazquez says, highlighting the role of modal balance in reducing the environmental impact of vehicle logistics. Following the Booster Days, a takeaway was that transport modes need to be thought of carefully. “Knowing we have a lack of drivers, CO2 reduction targets, and we need to improve our costs, it means we need to think outside of the box and find a new way to transport our goods,” says Vazquez. “We are asking our partners to propose multimodal solutions, even if it doesn’t meet all our criteria.”
While artificial intelligence is rapidly transforming visibility, prediction and automation, both Vazquez and Gaucherand stress that technology alone will not define best practice. Instead, the next frontier lies in combining AI with stronger human collaboration, deeper supplier integration and more flexible, multimodal logistics solutions in an increasingly volatile market.
