Agenda

This panel cuts through the promise of digital transformation to advise how to actually drive change on the ground. Gain senior manufacturing leaders’ experience in implementing decision-making, KPI alignment and governance once new systems and AI enter the process. Expect plain talk and lessons learnt when managing control and management shifts, and genuine insights into how successful manufacturing leaders run their operations day to day. 

Expect practical lessons in how to: 

• Manage the transfer of decision-making from people to digital systems and automation and decide where human judgement still needs to sit. 

• Translate shop floor operational improvements into business-level outcomes that demonstrate the value of transformation to senior leadership. 

• Determine whether a process is sufficiently understood, stable and mature before applying AI. Hear lessons learnt from rolling it out when it isn’t. 

• Establish clear accountability when automated systems increasingly influence or make operational decisions. 

Manufacturers are moving beyond isolated digital initiatives and focusing on connecting enterprise systems, operational technology, asset management, and frontline work across multiple plants. But scaling digital transformation requires more than deploying ERP, MES, MOM or CMMS platforms independently. It demands a connected digital thread where operational data is standardised, contextualised through shared semantic models, and accessible across the organisation. 

Join manufacturing leaders as they share practical lessons from integrating business and plant systems to create a unified digital backbone. Hear how organisations are standardising processes, breaking down data silos, and improving visibility across operations to support AI, predictive analytics, and continuous improvement.  

Expect insights into the governance, change management, and technology decisions that have enabled successful enterprise-wide scaling, along with the challenges they’ve faced and the key takeaways for manufacturers looking to build a connected, resilient, and future-ready manufacturing operation. 

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. 

Expect to learn:

• The concrete difference between classic data integration and a continuous foundation built for Physical AI 

• How to integrate AI applications, new machines and use cases without stopping the line 

• Understanding the data infrastructure Physical AI needs to read live machine state and write back to equipment in real time and securely 

• Bringing IT deployment practices (testing, versioning, rollback) and cyber security to the shop floor without putting the OT side at risk 

Sertec’s Smart Factory recognition wasn’t won by a single automation investment. It came from lots of small initiatives and a manufacturing execution system (MES) designed and built in-house by the team that uses it. 

Carl Milbourne shares how Sertec approached developing its own MES rather than buying one, how small initiatives added up to recognised results across its operations, and how developing talent in-house, including two consecutive CBM Apprentice of the Year winners, gave the business the capability to do it. 

Leave with practical strategies to: 

• Identify when building your own MES beats buying one, and what it takes from your team to do it 

• Turn small initiatives into measurable operational gains rather than waiting for one large investment to change everything 

• Make technology decisions that fit your operations instead of reshaping your operations around a vendor’s product 

• Build the in-house capability, including through apprenticeships, that lets you own your systems rather than rent them 

Silver Sponsorship Presentation

A pilot that works in one factory is no guarantee of a capability that works across a plant network. Digital maturity varies site by site, data models built for one factory don’t transfer to the next, and the gap between what was designed and what operators experience on the line is where trust in a programme is won or lost. 

Drawing on smart factory programmes across three global manufacturers, Sofia Karlén shares how to take digital transformation from local pilot to global standard, and why the biggest risks aren’t the technology but knowledge walking out the door with third parties, shifting definitions of success, and business cases that don’t hold up. 

Leave with practical strategies to: 

• Set data foundations that scale: contextualised data, harmonisation layers and master data management that let models replicate across sites rather than being rebuilt for each one 

• Understand what belongs in your data lake, and how data quality decisions made early determine what’s possible later 

• Close the disconnect between digital design and factory reality before it undermines adoption on the line 

• Make governance work at each stage from proof of concept through pilot to industrialisation and scale, so you know when something’s genuinely ready 

• Learn how to retain knowledge in your factories rather than losing it to vendors and third parties when the project team moves on 

Digital transformation stalls when people don’t come with you. Announce fewer machines and the shop floor hears fewer jobs. Push digital design without conversation between teams and parts arrive that don’t fit together. The technology works; the change around it is where programmes succeed or fail. 

Join a panel of manufacturing leaders as they share how they’ve won buy-in for change on the shop floor, reframed investment as upskilling rather than headcount risk, and kept people talking to each other as processes went digital. 

Topics include: 

• Turning fear of headcount cuts into buy-in by positioning investment as upskilling 

• How to create trust before decisions are made by sharing the remit and involving teams from day one 

• Rolling out digital processes and revealing, then closing, handover gaps between design and manufacturing before they affect production 

• Making change stick by giving teams local ownership of what works for them 

Three manufacturers each present a current business challenge or question from their digital transformation journey to the ‘Manufacturing Board’ made up of leaders from UK facilities and industry advisors.  

Expect practical, peer-led advice that tackles genuine business challenges faced by manufacturers today. Hear tried and tested solutions and actionable ideas they can apply within their own organisations. 

Format:
– 1 x manufacturer presents a real-world business or transformation challenge (1 minute)
– The Board gives tried and tested solutions from their experiences (5 minutes)
– Audience participation with comments and further contributions (2 minutes)

Many organisations understand that technologies such as AI and Digital Twins rely on a strong data foundation to deliver meaningful results. Yet knowing this and successfully building that foundation are two very different things. Without the right data, connectivity, security, and operational alignment in place, even the most promising digital initiatives can stall, underperform, or create additional complexity. 

Join Steve Mason and a UK Major Automotive OEM as they share candid lessons from the successes and setbacks of delivering multi-million-pound digital transformation programmes. Discover what worked, what didn’t, and how to reset your roadmap to accelerate value at scale. 

Leave with practical strategies to: 

• Laying the data foundation needed to unlock value from AI, Digital Twins, and advanced analytics 

• Align IT and OT teams to reduce friction, accelerate deployment, and avoid costly operational disruptions 

• Make the right connectivity and cybersecurity decisions from the outset to prevent expensive rework and delays 

• Standardise digital capabilities across sites while maintaining flexibility for local operational needs 

• Turn pilot projects into scalable, enterprise-wide transformation programmes