BRIDGING LEGACY & INNOVATION:
MASTERING DATA TO BUILD RESILIENT SUPPLY CHAINS
MASTERING DATA TO BUILD RESILIENT SUPPLY CHAINS
Agenda Day 2
8:30 am - 8:40 am
OPENING REMARKS FROM THE CHAIRPERSON
John Wernfeldt -
Managing Director - Data, Analytics and AI,
Northridge Analytics
8:40 am - 9:25 am
PANEL DISCUSSION: DATA TO $ - UNLOCKING DATA’S TANGIBLE VALUE
Nicolas Nikula -
Director - Analytics, Processes, Systems & WFP,
Fiskars Group
Richard Clayton - Head of Data Science & Systems, Pilgrim's Europe
Ådne Brunborg - Chief Data Officer, Seatrans Group
Arqum Ahmad - CTIO Digital Solutions, Leonardo
In an era of tightening budgets and heightened scrutiny, data leaders face mounting pressure to demonstrate concrete returns on data and AI investments. Hear about battle-tested strategies for translating data initiatives into measurable business impact. Learn how to navigate common pitfalls, secure buy-in from sceptical executives, and implement practical frameworks for quantifying and communicating the value of your data projects.
- Explore techniques for aligning data initiatives with strategic priorities and setting clear, measurable objectives from the outset
- Discuss approaches to incrementally modernise infrastructure while delivering quick wins that build momentum and trust
- Discover different strategies for demonstrating the value of data in industries with entrenched systems and processes
9:25 am - 9:55 am
INDUSTRIAL AI AT SCALE - THE ROADMAP TO SMART MANUFACTURING
Esteban Remecz -
CIO VP Information Technology & Digital,
Maxion Wheels
11:45 am - 12:15 pm
CASE STUDY PRESENTATION: BEYOND DATA CATALOGUES - PRACTICAL GRAPH-BASED APPROACHES TO DATA GOVERNANCE
Martin Pasch -
VP Advanced Products & Services, Digital & Automation, Group Division Hydro,
Voith Hydro
While data catalogues are widely praised as essential tools for data management, they often impose rigid hierarchical structures that fail in complex real-world environments. In this provocative session, Martin Pasch, our expert speaker, challenges conventional wisdom by demonstrating how graph-based approaches offer more flexible and practical solutions to data governance concerns. Many knowledge graphs and ontology efforts attempt to create a complete, all-encompassing model of the world, which becomes so abstract that experts can't understand or use it effectively.
- Hear about a more practical approach that allows for easier understanding and implementation, rather than getting lost in a theoretical, all-encompassing model
- Discover a framework built on three key pillars: localised domain expertise, semantic context management, and the ability to adapt user interfaces dynamically (potentially using large language models)
- Understand how to eliminate costly migration scripts, reduce tool-swapping interruptions, and deliver significant cost savings—all while empowering domain experts to model their data effectively
Martin Pasch
VP Advanced Products & Services, Digital & Automation, Group Division HydroVoith Hydro
12:15 pm - 12:45 pm
FIRESIDE CHAT: BALANCING DATA ACCESS AND PROTECTION
Matúš Tomečko -
Data Domain Manager,
Škoda Auto
Mojmír Barák - Logistics Systems Coordinator, Škoda Auto
Techniques for classifying data sensitivity levels and implementing appropriate security measures without hindering necessary access. Explore how to create a culture of data responsibility while enabling innovation and operational efficiency
12:45 pm - 1:45 pm
LUNCH
2:55 pm - 3:55 pm
CLOSING PLENARY PREDICTION PANEL: (DON’T) BELIEVE THE HYPE– PREDICTING FUTURE TECHNOLOGY TRENDS
Thinking about what the future of data and analytics will look like is a challenge. Given the exponential acceleration of technologies like AI and AAI, we are already unable to envision anything beyond the next 6 months with greater clarity, making it difficult to plan out a 3-year investment road map. There is not much consensus among experts other than that the models will be bigger and more complex, so identifying opportunities early and differentiating them from. The hype could be the difference between being a trailblazer and falling behind. Data science is evolving from a craft to an industrial process. The future sounds promising, but what are the panel’s predictions for the natural evolution of data technology, ethics, and regulation? Join us for a short and intense prediction session as we delve into the use of quantum or edge computing integration to build continuously learning models with augmented intelligence.
