Draft agenda
DAY ONE - Tuesday, 17th November 2026
08:00 – 08:45
REGISTRATION, REFRESHMENTS AND NETWORKING
08:45 – 08:55
Chairs Welcome and Opening Scene Setting
Sven Seipp, Senior Manager, Deloitte
THINK TANKS
Our Think Tanks give you the opportunity to discuss your biggest challenges with senior peers facing the same priorities.
Choose the three topics most relevant to your business and join a focused discussion with a small group of industry leaders. Share experiences, compare approaches, explore practical solutions and leave each session with ideas you can take back to your organisation.
09:00 – 09:25
Think Tank Challenge 1
TABLE ONE:
Moving Manufacturing AI Pilots Successfully into Production:
Explore what actually scales
TABLE TWO:
Building Resilient Operations in a Disruptive Landscape
Learn how to enhance operational agility amidst rapid industry changes.
TABLE THREE:
Enhancing Supply Chain Integration and Security
Discover methods to create connected and secure supply chains.
TABLE FOUR:
Industrial AI: Transforming Manufacturing Processes
Understand the practical applications of AI in manufacturing.
TABLE FIVE:
Digital Twins: Bridging Physical and Digital Worlds
Explore the use of digital twins to optimise manufacturing operations.
TABLE SIX:
Cybersecurity in Smart Manufacturing
Address the growing cybersecurity challenges in digital manufacturing.
TABLE SEVEN:
Data-Driven Decision Making in Manufacturing
Leverage data analytics to inform strategic decisions.
TABLE EIGHT:
Sustainable Manufacturing: Achieving Green Goals
Incorporate sustainability into manufacturing processes.
TABLE NINE:
Workforce Transformation in the Digital Age
Prepare your workforce for the demands of modern manufacturing.
TABLE TEN:
Leveraging IoT for Operational Excellence
Utilise IoT technologies to enhance manufacturing efficiency.
TABLE ELEVEN:
Predictive Maintenance: Minimising Downtime
Implement predictive maintenance strategies to improve reliability.
TABLE TWELVE:
Advanced Robotics and Automation
Explore the integration of robotics into manufacturing workflows.
TABLE THIRTEEN:
Cloud Computing in Manufacturing
Understand the role of cloud technologies in modern manufacturing.
09:30 – 09:55
Think Tank Challenge 2
Think Tanks Challenge topics repeated as above.
10:00 – 10:25
Think Tank Challenge 3
Think Tanks Challenge topics repeated as above.
10:25 – 10:50
NETWORKING AND REFRESHMENTS
10:50 – 11:15
OPENING KEYNOTE
From Pilot Purgatory to Plant-Wide AI: Why Data Availability, Not Models, Decides Who Scales
Most manufacturers do not fail at AI because of the models. They fail because the data the models need is locked in brownfield machines, fragmented systems and undocumented processes. Drawing on hands-on experience from series production at a global automotive supplier, this session examines why data availability is the real bottleneck on the path from GenAI pilots to plant-wide deployment, and what it takes organisationally and architecturally to remove it.
Key Takeaways
- Why the pilot-to-scale gap is a data problem, not a model problem, and how to diagnose it in your own plants
- Practical approaches to making brownfield data usable: connectivity, standardisation and semantics
- Where agentic AI realistically fits into series production today, and where it does not yet
Dr. Steffen Klarmann, Advanced Industrial Director, Valeo
Meeting session 1
11:20 – 11:45
OT/IT CASE STUDY
Unifying IT/OT systems with seamless edge data integration for an interoperable IIoT infrastructure
Key takeaways:
- Best practices for modernising outdated OT to enable secure and resilient IT/OT convergence.
- How to ensure the integrity and reliability of data streams from integrated legacy and OT systems for accurate insights and automation?
- What proven cybersecurity protocols mitigate escalating risks in interconnected IT/OT environments, considering evolving regulations?
- What network segmentation architectures are critical for a disruption-ready factory, safeguarding converged IT/OT systems?
Shashank Sharma, Director of Product Marketing, HiveMQ
Meeting session 2
11:50 – 12:15
CASE STUDY
Fixing the Line Before It Breaks: Making Final Assembly the Hub of Upstream Visibility
In complex discrete manufacturing, the Final Assembly Line is where upstream problems finally surface. Late engineering releases, configuration changes and design quality issues lead to missing parts, rework and schedule slippage.
This session explores how a connected data feedback loop across Product Configuration, Design Engineering, Manufacturing Engineering and Quality gives assembly teams early visibility of upstream risks. As a result, issues can be resolved well before work orders reach the shop floor.
Meeting session 3
12:20 – 12:45
DATA OPTIMISATION CASE STUDY
The blind spot in your AI strategy: If your factory is built to stop, you won’t get Physical AI to run.
- Most factories in 2026 must halt production to deploy a configuration change, an integration or an AI model. This can cost up to $2 million per stop.
- Physical AI raises the stakes: it consumes live machine state, in real time and bidirectionally. Physical AI cannot run on an architecture that needs maintenance windows.
- With the right data foundation, manufacturing leaders like Porsche and Miele continuously improve their production – tested, versioned, zero downtime.
Peter Sorowka, CEO Cybus GmbH
Meeting session 4
12:45 – 13:45
NETWORKING LUNCH
13:45 – 14:10
OPENING AFTERNOON KEYNOTE
How digitalisation can drive sustainable manufacturing practices
Key takeaways:
Regulatory initiatives like the EU Carbon Border Adjustment Mechanism and the U.S. Inflation Reduction Act are pushing companies to align with low-carbon goals. Technologies such as green hydrogen, closed-loop recycling, and energy-efficient production systems are being deployed at scale. So how can digital transformation drive sustainable, profitable manufacturing?
- Utilising IoT technology, advanced energy management systems, and predictive analytics to drastically cut energy usage and emissions
- Understanding the role of data optimisation in demand planning and sustainable manufacturing supply chains to create cost efficiencies
Meeting session 5
14:15 – 14:40
INDUSTRIAL AI CASE STUDY
Industrial AI in Practice: Lessons from Scaling AI Across Global Manufacturing Operations
The competition for skilled workforces is increasing, especially as manufacturers invest in advanced digital tools and smart manufacturing facilities
The primary concern for more than a third of 600 manufacturing executives in a 2025 Deloitte survey was “equipping workers with the skills and knowledge they need to maximize the potential of smart manufacturing and operations”
Learn how following a “build, buy, or borrow” framework for workforce planning could help manufacturers remain agile while continuing to build and strengthen their workforce for the future
Key Learnings
- Creating a single source of truth for engineering and operational information
Improving document governance, traceability and compliance - Making trusted information readily available to support AI and digital initiatives
- Reducing time spent searching for information while improving collaboration across the organisation
Meeting session 6
14:45 – 15:10
CASE STUDY
Closing Europe’s Competitiveness Gap with Autonomous Manufacturing
Engineering excellence alone is no longer enough to sustain Europe’s industrial leadership. As AI, robotics and intelligent manufacturing reshape global competition, manufacturers must accelerate digital transformation to remain competitive.
Giovanni Polosa, Global Manufacturing Director at Bonfiglioli, shares the company’s journey towards the Dark Factory, exploring how AI, IIoT and advanced automation are transforming production.
Key takeaways:
- Prioritising digital transformation investments
- Scaling AI and automation beyond pilot projects
- Modernising legacy manufacturing operations
- Building the capabilities needed for globally competitive, autonomous production
Giovanni Polosa, Global Manufacturing Director, Bonfiglioli
Meeting session 7
15:10 – 15:35
AFTERNOON NETWORKING AND REFRESHMENTS
15:35 – 16:00
CASE STUDY
Beyond Visibility: How Network Intelligence Enables Faster Resilience Decisions
Traditional resilience approaches provide valuable risk visibility but offer limited support for determining when interconnected networks may cross critical failure thresholds. This session shares how Nestlé is applying a network graph model with large-scale optimisation across tens of thousands of materials, suppliers and finished goods to examine disruption propagation and quantify potential business impact.
Key Takeaways
- Modelling disruption propagation across complex, interconnected supply networks
- Quantifying business impact and comparing feasible responses under operating constraints
- Identifying critical combinations of risk variables through scenario stress testing
- Examining how shared dependencies and correlated shocks compound over time
- Supporting cross-functional decisions on where flexibility is economically justified and which interventions protect the most value
Linda Farczadi, Supplier Intelligence, Data & AI Stream Lead, Nestlé
Meeting session 8
16:05 – 16:30
TECHNOLOGY CASE STUDY
Manufacturing Knowledge Without the Chaos: Creating Trusted Information for Faster Decisions, Compliance and AI
Engineering drawings, quality records, operating procedures and compliance documentation are often stored across multiple systems, making it difficult to locate trusted information when it’s needed most. As manufacturers accelerate digital transformation, effective information management has become critical to supporting AI, improving collaboration and maintaining compliance.
Key Learnings
- Creating a single source of truth for engineering and operational information
- Improving governance, traceability and regulatory compliance
- Making trusted information readily available to support AI and automation initiatives
- Reducing time spent searching for information while improving collaboration across the organisation
Meeting session 13
16:35 – 17:15
PANEL DISCUSSION
Moving Manufacturing AI Pilots Successfully into Production: What Actually Scales
The gap between AI pilots and production is often not an AI problem, but an infrastructure one. This session looks at where transformation budgets should really focus, and what it takes to run AI at scale across distributed OT infrastructure and smaller plants.
Discussion Points
- Identifying on which layer your transformation budget should focus
- The hidden cost of managing AI and compute across distributed OT infrastructure & smaller plants: service technicians, config drift, and dealing with security exposure regulators (CRA, NIS2, IEC 62443)
- IT/OT ownership in practice: who actually operates edge fleets once the pilot team leaves, and how should you structure that hand-off?
- Sovereignty and data residency as a scaling constraint, not a compliance checkbox: what changes when the factory can’t send data to the cloud?
17:15 - 17:20
CHAIR'S DAY ONE SUMMARY AND CLOSING REMARKS
Sven Seipp, Senior Manager, Deloitte
17:20 - 18:20
NETWORKING DRINKS RECEPTION
DAY TWO – Wednesday, 18th November 2026
08:00 – 08:45
REGISTRATION, REFRESHMENTS AND NETWORKING
08:45 – 08:55
Chair’s Day Two Welcome and Opening Remarks
Sven Seipp, Senior Manager, Deloitte
09:00 – 09:45
ROUNDTABLE DISCUSSIONS
Small group discussions tackling your most critical challenges
TABLE ONE
Integrating AI into Legacy Systems
TABLE TWO
Strategies for Effective Change Management
TABLE THREE
Enhancing Supplier Collaboration through Technology
TABLE FOUR
Implementing Digital Twins for Quality Control
TABLE FIVE
Cybersecurity Best Practices for Manufacturing
TABLE SIX
Optimising Supply Chain Visibility
TABLE SEVEN
Leveraging Data Analytics for Forecasting
TABLE EIGHT
Target architecture: A pragmatic approach and how to bridge the gap with today’s reality
Led by Martijn Verbrugghen – Consultancy Manager & Paula Gonzalez Digital Program Manager, AG Solution
TABLE NINE
Sustainable Practices in Manufacturing Operations
TABLE TEN
Training, Retaining & Upskilling a Digitally Skilled Workforce
09:50 – 10:15
OPENING KEYNOTE
Driving Operational Excellence with Real-Time Manufacturing Intelligence
Leading manufacturers are using live production data to optimise operations, improve quality and respond faster to changing conditions on the factory floor. This session explores how real-time manufacturing intelligence is helping organisations move from reactive decision-making to continuous operational improvement, delivering measurable gains in efficiency, reliability and performance.
Key Learnings
- Improving production performance through real-time operational visibility
- Using live manufacturing data to optimise quality, throughput and efficiency
- Enabling faster, more informed decisions across plant operations
- Turning operational intelligence into continuous improvement across multiple manufacturing sites
Raibel Alvarado, Director of Opperational Excellence, Forbo
Meeting session 10
10:20 – 10:45
CASE STUDY
Applying Agentic AI for Maintenance, Repair, and Operations (MRO) in Smart Manufacturing
Key Takeaways:
- Applying effective MRO lifecycle data in optimising hardware and technology performance across the manufacturing sector
- How are data quality issues undermining real-time asset management and maintenance workflows in manufacturing operations
- Uncovering agentic AI-driven tools which resolve reliability data gaps and improve margin gains
Erasmo Mateos, Global Head of Manufacturing Operations, Robert Bocsh Power Tools
Meeting session 11
10:45 – 11:10
REFRESHMENTS AND NETWORKING
11:10 – 11:35
SUPPLY CHAIN CASE STUDY
Inside Natra's Supply Chain: Where Digital Is Earning Its Place
Synopsis coming soon.
(Working title)
Xabier Lorenzo, Supply Chain Director, Natra
Meeting session 12
11:40 – 12:05
CASE STUDY
From factory floor to cloud: Enabling scalable interoperability through OPC UA
- Discover how OPC UA enables seamless IT/OT integration and supports scalable digital manufacturing architectures.
- Learn how the new OPC UA Cloud Initiative connects factory floor data with major cloud platforms and analytics tools.
- Explore real-world use cases showing OPC UA in action for digital twins, predictive maintenance, and edge-to-cloud deployments.
- Understand the role of open standards in modernizing legacy systems and unlocking long-term interoperability.
Stefan Hoppe, President, OPC Foundation
Meeting session 9
12:10 – 12:35
PILOT TO PLANT CASE STUDY
When the wind picks up, direction matters: From endless opportunities to leading with a clear direction to focus on impact generation
If one does not know to which port one is sailing, no wind is favorable. This quote from Sceneca the younger describes the start of the Product Supply (PS) AI journey. The winds were strong: Corporate initiatives, frontrunner pilots, bottom-up experimentation and AI agents created energy everywhere. Yet without a clear port, even the strongest momentum risked drifting into scattered efforts, duplicated work and limited impact.
That is why PS translated the corporate AI vision into a manufacturing- and supply-specific AI ambition: a compass that clarifies where AI can create the most value, which value pools matter most, and how scarce resources can be channeled towards creating impact. In addition, future leadership skills are assessed to enable steering of the future organization and to focus on what is human.
Key Learnings
- The story of moving from AI excitement to AI direction
- The approach from ambition to value pools and key results
- First insights on leadership capabilities needed to steer an AI-enabled PS organization
Moritz Fehrle, VP, Transformation & Strategy, Bayer
Meeting session 14
12:40 – 13:20
FUTURE FACING PANEL DISCUSSION
Creating Value from Manufacturing Data
Manufacturers have invested heavily in AI, analytics and digital transformation, but technology alone doesn’t create business value. Commercial reality determines whether new capabilities are adopted, scaled and sustained.
This panel separates genuine business value from technological promise. Senior industry leaders discuss where AI is delivering measurable operational improvements, why many initiatives stall beyond isolated use cases, and what it takes to prepare enterprise data for the next generation of intelligent manufacturing.
Discussion points:
- Where are AI and digital transformation delivering measurable business value today?
- How should manufacturers prioritise digital investments when budgets are tight and markets remain uncertain?
- How much investment in data quality and integration is really needed before AI can create value?
- What organisational changes are needed to scale digital transformation beyond isolated projects?
- How can manufacturers balance innovation with resilience, cybersecurity and regulatory requirements?
- What will distinguish the next generation of digitally mature manufacturers?
Raibel Alvarado, Director, Operational Excellence, Forbo
13:20 – 13:25
Chair’s Summary and Closing Remarks
Sven Seipp, Senior Manager, Deloitte
13:25 -14:25
FAREWELL LUNCH
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