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:
Smart Factories, Connected Knowledge: What It Takes for AI to Scale
Many manufacturers have invested in smart factories, MES and predictive maintenance. So why do costly quality issues and slow launches keep happening? Often, product, material and process knowledge reaches production incomplete, spread across disconnected systems, spreadsheets and a few experts. This roundtable puts leaders in the same room to define a practical path from lab or design to production.
TABLE THREE:
Beyond Dashboards: Why Is Operational Visibility Still a Challenge?
Manufacturers have more data, systems and dashboards than ever, yet gaining a clear picture of operations remains a challenge. Why is critical information still fragmented across departments and systems? What prevents organizations from turning available data into shared operational understanding?
TABLE FOUR:
Which Decisions Are Too Important to Guess?
A practical Think Tank discussing how strategic and operational decisions cannot be made on gut feel alone, and how simulation based digital twins can help decision makers move from instinct-based to evidence-based decisions, bridging the gap between uncertainty and certainty. During the session, we will explore real challenges faced by those at the table, and how outcomes may have been different by combining their experience with digital solutions.
TABLE FIVE:
Predictive Maintenance: Minimising Downtime
Implement predictive maintenance strategies to improve reliability.
TABLE SIX:
Workforce Transformation in the Digital Age
Prepare your workforce for the demands of modern manufacturing.
TABLE SEVEN:
Advanced Robotics and Automation
Explore the integration of robotics into manufacturing workflows.
TABLE EIGHT:
Data-Driven Decision Making in Manufacturing
Leverage data analytics to inform strategic decisions.
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
From one pilot to every plant: turning industrial data into operational intelligence at scale
European manufacturers are under pressure to get more output from existing capacity, maximize uptime, control energy and operating costs, and hit production targets consistently across plants in different countries, many of which still running on legacy systems.
AI and analytics can help, but they only hold up in production when industrial data is systematically turned into trusted operational intelligence that people and systems can act on. This session shows how manufacturers can build a reusable foundation that connects operational data, gives it context, continuously analyzes what is happening, and puts the resulting intelligence to work across the organization.
Key takeaways:
- Connect operational data across machines, legacy systems, and sites for organization-wide visibility
- Standardize context and meaning so people, systems, and AI can trust and reuse the data
- Spot a line losing performance while there’s still time to act, with a recommendation ready for your team to review
- Scale proven improvements across plants instead of leaving value trapped in isolated pilots
Shashank Sharma, Director of Product Marketing, HiveMQ
Meeting session 2
11:50 – 12:15
CASE STUDY
Predictable Assembly in a Complex World: E2E Deliverable Tracking & Predictive Disruption Modeling
In complex discrete manufacturing, the Final Assembly Line (FAL) traditionally bears the cumulative weight of upstream delays, incomplete engineering releases and design non-quality. This use case reframes the FAL from a passive recipient of these issues into an active Operational Enablement Hub.
With a unified data feedback loop across Product Configuration, Design Engineering, Manufacturing Engineering (ME) and Quality, the FAL team gains predictive visibility into upstream deliverables, long before work orders reach the shop floor and parts are missing.
Meeting session 3
12:20 – 12:45
DATA OPTIMISATION CASE STUDY
What if you could ask your factory? From scattered data to Physical AI
Your factory knows why scrap increased on line 3 and which machine will fail next. However, the answers are scattered across machines and IT systems. AI can find those answers in seconds. Once live data from manufacturing processes is available, Physical AI can act on it.
We demonstrate how leading manufacturers have built this foundation without halting production, and explain how your plant can do the same.
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
CASE STUDY
Lean and Digitalization in the Search for Perfection: How Leadership, Connection and Culture Decide Between Transformation and Failure
Key Takeaways
- Lean and Digitalization: From apparent competitors to powerful allies.
- Leadership: Transformation starts with leadership commitment and clear direction.
- Connection & Culture: Technology creates value only when people, processes, and information are connected.
- The BIG MISTAKE: Why Europe is failing in this transformation?
Erasmo Mateos, Global Head of Manufacturing Operations, Robert Bosch Power Tools
Meeting session 9
16:35 – 17:15
PANEL DISCUSSION
Moving Manufacturing AI Pilots Successfully into Production: What Actually Scales
Why the AI pilot-to-production gap is an infrastructure, not an AI, problem: 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?
Panellists:
Frank Harter, Global Client Director & Sales Germany
Mo Alloul, Strategic Account Executive EMEA North
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
Driving Adoption: Getting People On Board with Digital Change
TABLE TWO
Target architecture: A pragmatic approach and how to bridge the gap with today’s reality
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
Scaling Industrial AI: From Pilot to Plant-Wide Deployment
TABLE EIGHT
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
From factory floor to cloud: Enabling scalable interoperability for AI
Key Takeaways
- 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 standardized semantic and MCP servers for AI driven value
Stefan Hoppe, President, OPC Foundation
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 Fragmented Information to Operational Context
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 Takeaways
- 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
Tiina Hietajavi, Principal Industry Advisor, M-FILES
Meeting session 13
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
Data Doesn't Deliver Results. People Do. Why the missing link in digital transformation is execution.
Manufacturers have more data, dashboards and AI-powered insights than ever before, yet many continue to experience the same losses, recurring issues and performance gaps. The challenge is no longer collecting data, it’s turning that data into action and action into both results & value.
This panel explores why organisations become data-rich but action-poor, what separates digital visibility from business value, and how leading manufacturers combine technology, frontline capability, accountability and problem-solving to deliver measurable performance improvement.
Discussion points:
- Why are manufacturers collecting more data but not always achieving better results?
- How do organisations avoid becoming data-rich but action-poor?
- What role does frontline problem-solving play in digital transformation success?
- Why do recurring losses continue despite being highly visible in digital systems?
- How do leadership, accountability and execution discipline accelerate performance?
- What separates organisations that use technology to report performance from those that use technology to improve performance?
Darren O’Connor, Director of Business Development, Milliken
Raibel Alvarado, Director, Operational Excellence, Forbo
Raffaella Zavattaro, Chair and co-owner, GEFIT
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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