The 2024 International Data Maturity Benchmark Industry Report found that when it comes to their Data Architecture and Modelling strategy only 15% of manufacturing and logistics participants have reached the optimised level, with most responses clustering in the intermediate defined and managed levels, suggesting that companies in this sector still need to consolidate their data architecture to enhance efficiency and production management. Panellists will share insights on creating a single source of truth, integrating legacy systems with cutting-edge technologies, and balancing standardization with customization and explore the critical role of data architecture in driving innovation and efficiency. Hear different opinions on the best ways to overcome common challenges and build the architecture that supports your organization's strategic goals.

·       Gain valuable insights into strategies to improve data architecture, enhance decision-making capabilities, and drive business value through effective data management.

·       Understand how integrating legacy systems with modern data platforms to meet evolving expectations can bridge the gap

·       Evaluate the pros and cons of different data architecture models and their suitability for various organizational structures and scales

·       Discover the best way to solve the standardisation dilemma to find the right balance between standardisation and customization in data architecture 

Compare and contrast the efficiency of traditional long-term planning with the more agile, short-term approaches 

Cloud adoption is transforming the M&L industry, enabling companies to enhance operational efficiency, drive innovation, and gain a competitive edge. Explore key trends and best practices in the M&L sector, providing attendees with actionable insights to accelerate their digital transformation journey.

·       Discover the challenges and opportunities of cloud adoption in manufacturing, including concerns about operational technology data and machine control software dependencies

·       Learn how to develop a robust cloud-based data architecture that supports a single source of truth while enabling data synchronicity across diverse manufacturing systems

·       Understand the role of cloud platforms in enabling data unification, fluency programs, and advanced business intelligence for manufacturing and logistics operations

Debate strategies for holding cloud vendors accountable and ensuring their solutions deliver real value in the complex landscape of manufacturing and logistics 

This session explores the critical role of data and analytics in implementing effective predictive maintenance strategies. As manufacturers collect vast amounts of sensor data from machinery, they face significant challenges in data management and analysis. Discuss practical approaches to overcoming these hurdles, leveraging advanced analytics and AI to transform raw data into actionable insights that prevent downtime and optimize maintenance schedules.

·       Examine the architectural considerations for handling high-volume, high-velocity sensor data.

·       Discover approaches to building a robust data infrastructure that supports real-time analytics and enables rapid decision-making for maintenance operations

·       Explore the applications of machine learning and AI techniques for developing accurate predictive maintenance models

Discuss the best methods for quantifying the impact of predictive maintenance initiatives and demonstrating ROI to stakeholders

Approaches to building a robust data infrastructure that supports real-time analytics and enables rapid decision-making for maintenance operations 

In an era of tariffs, 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

Seamless data integration across the supply chain is no longer a luxury—it's a necessity. This session explores how leading organizations are overcoming legacy system challenges, breaking down data silos, and leveraging advanced analytics to create a unified view of their supply chain. Examine real-world case studies, discuss practical strategies for improving data quality and completeness, and explore how emerging technologies like AI and cloud computing are reshaping supply chain data management. Join us to learn how you can transform your supply chain data into a powerful asset for driving efficiency, resilience, and innovation.        

·       Explore strategies for integrating data from disparate legacy systems across the supply chain.

·       Discuss the challenges of harmonizing data from multiple countries and business units, and share successful approaches to creating a centralized data lake that can support advanced analytics and decision-making

·       Examine practical methods for improving data quality and completeness across supply chain operations

Discover innovative approaches to incentivize data accuracy, implement quality controls, and hold data owners accountable for the integrity of their data assets