Details
Join us for an engaging webinar on how AI and trusted data are redefining supply chain management in an era of intense competition, evolving ESG regulations, and rising demands for real-time responsiveness.
Learn how a strong data foundation can drive resilience and innovation across manufacturing and retail—from powering digital twins and AI-driven forecasting to optimizing sustainability and efficiency.
You’ll gain practical insights and inspiration to elevate your data strategy and a clear roadmap toward a smarter, more connected supply chain.
Speakers
Post-event summary
The webinar titled “Reimagining Supply Chains with AI and Trusted Data,” was hosted by EDM Association and Informatica and explored how modern supply chains can be re-engineered through strong data foundations, AI, and enhanced transparency. Speakers included:
- Christian Farra, Global Supply Chain Practice Lead, Informatica
- Kyle Morton, COO, EDM Association
Kyle opened by emphasizing the EDM Association’s mission of helping organizations trust their data, setting the stage for Informatica’s Christian Farra to examine the growing complexity facing global supply chains. Christian explained that organizations are under increasing pressure from disruptions to “plan for the unplanned”: consumer behavior spikes like viral social trends, environmental crises such as hurricanes, geopolitical tensions, tariffs, and events like COVID-19. These challenges require end-to-end visibility across suppliers, raw materials, production, and distribution. Yet, most organizations lack this visibility; studies cited show that only 9% of companies are prepared for transparency regulations and 45% have no visibility beyond Tier 1 suppliers.
Christian stressed that fragmented data systems—PLM, ERP, CRM, e-commerce, sourcing platforms—create silos that block true oversight. Within these systems live three critical data types: master data (products, suppliers, customers), transactional data (orders, shipments), and analytical data (dashboards, KPIs). Master data is the foundation, yet it degrades rapidly; suppliers change, products version, and duplicates proliferate. Without clean data, organizations risk operational failures, misinformed analytics, and inability to meet regulatory requirements such as Digital Product Passports, hazardous materials restrictions, and sustainability reporting. As Christian noted, many organizations overlook this foundational work: “AI will always give you an answer, whether it’s correct or not — and that’s the problem.” Trusted master data is essential before AI can be leveraged reliably.
The session highlighted two real-world scenarios demonstrating the stakes: product recalls and supply chain disruptions. Product recalls across industries, from automotive to food, are rising due to increasing product and supply chain complexity. Effective response requires accurate traceability across components, batches, suppliers, and manufacturing locations. Likewise, disruptions from wars, resource shortages, natural disasters, strikes, and technology failures demand rapid access to data on sourcing alternatives, lead times, and risk factors.
The final portion showcased a practical example of Agentic AI for supply chain operations: an AI agent that merges master data, transactional data, and metadata to answer operational questions such as pending orders, product structures, supplier details, and risks. This illustrates how AI can assist supply chain teams, but only when underpinned by accurate and unified data. Christian outlined a pragmatic adoption strategy: start with small MVPs, validate data quality, and gradually build agent capabilities once data governance and MDM foundations are solid.
