Stellantis: People and collaboration to drive future automotive supply chain strategy
Carlos Vazquez, vice-president of global purchasing and supply chain, StellantisSource: ALSC Europe 2026
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.
(L to R) Stellantis' Benoit Gaucherand, senior manager for enlarged Europe aftersales transport network design and cost control, and Carlos Vazquez, vice-president of global purchasing and supply chain, speaking at ALSC Europe 2026Source: ALSC Europe 2026
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.
Benoit Gaucherand, StellantisSource: ALSC Europe 2026
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.