An agenda built through deep collaboration with our community to ensure every session delivers substance over soundbites. You’ll hear from true subject matter leaders via candid case studies, collaborative roundtables, and varied panel discussions —providing clarity on what’s driving success across the marketing landscape.
This session will be hosted by a Reuters journalist under the Trust Principles.
• Build structural resilience into global supply networks through supplier diversification, nearshoring strategies, strategic inventory buffers, and end-to-end visibility that protect service performance during geopolitical shocks.
• Strengthen risk management across Tier 2/3 suppliers with unified visibility tools and live supplier data that expose concentration risk, single-source dependencies, and early disruption signals before they escalate into operational failure.
• Deliver a flexible, responsive network architecture by connecting fragmented data, aligning functions across the business, and enabling rapid shifts in sourcing, fulfilment, and logistics to maintain continuity through prolonged volatility.
• Accelerate enterprise adoption by building trusted data foundations and integrating AI agents into daily workflows, to deliver measurable improvements in forecasting, planning, and operations.
• Ensure safe, scalable implementation by embedding human oversight, governance, and explainability into AI-driven processes, to drive confidence and adoption across supply chain teams.
• Unlock ROI from digital transformation by moving beyond pilots and establishing clear metrics for success, to secure sustained investment and demonstrate value to the business.
Tariffs, Trade Wars, and Regulatory Shocks: How to build adaptable supply chain & logistics operations
• Anticipate and quantify risk by stress-testing logistics networks against tariff, border, and regulatory shifts to achieve supply continuity.
• Translate scenarios into action by rapidly rerouting flows, rebalancing inventory, and shifting suppliers or modes as conditions change, maintaining service levels.
• Enable adaptability with strong governance, data, and decision frameworks - aligning compliance and control towers for resilient, agile operations.
• Deliver faster, more accurate decision-making across the end-to-end supply network by integrating AI agents into demand sensing, supplier risk management, and logistics orchestration to improve responsiveness at scale.
• Equip supply chain teams with the roles, accountability frameworks, and workflows that AI-augmented operations demand to strengthen execution without eroding human strategic judgment.
• Unlock workforce productivity at scale by designing human-machine collaboration models that amplify supply chain expertise to increase efficiency without displacing critical talent.
• Improve planning accuracy and execution performance by identifying and prioritizing the master and transactional data defects that most distort forecasts, inventory, lead times, and capacity assumptions, to focus remediation on the issues that deliver the greatest planning impact.
• Strengthen cross-functional accountability for planning data by establishing clear business ownership, governance, and shared definitions across functions and regions, to embed trusted data discipline into day-to-day planning decisions.
• Enable scalable, AI-driven decision-making by building a minimum viable, standardized, and governed data foundation that connects fragmented data to operational context, to support explainable, closed-loop decisions in real time.
• Translate strategic intent into financially aligned planning decisions across the enterprise by harmonizing strategic, operational, and financial plans around shared cross-functional objectives, to reduce volatility, protect margins, and improve service, inventory, cost, and revenue performance.
• Strengthen the link between planning and execution by establishing tighter S&OE cadences, clearer handoffs, and decision rights by planning horizon, to reduce delays, limit escalations, and improve execution consistency across day-to-day operations.
• Modernize IBP for faster, more complex environments by applying AI-driven scenario modelling, cloud-based collaboration, and integrated data across demand, supply, finance, and sustainability, to enable continuous planning, faster response, and more resilient trade-offs as conditions change.
• Improve forecast accuracy and responsiveness in volatile markets by combining AI-driven demand sensing, predictive analytics, and multiple demand signals, to reduce bias, shorten reaction times, and better anticipate shifts in customer demand.
• Optimize inventory across the network without sacrificing service by applying advanced inventory optimization techniques that account for demand uncertainty, lead-time variability, and service targets, to reduce excess stock, prevent stockouts, and free up working capital.
• Enable faster, more effective planning actions by embedding AI-driven insights into demand and inventory workflows, to help planners prioritize exceptions, respond earlier to change, and improve service, availability, and inventory outcomes at scale.
• Detect and respond to disruption in real time by deploying AI agents that monitor, analyse, and act across the global logistics network to minimise operational impact.
• Empower teams to make faster, smarter decisions by combining human expertise with AI-driven recommendations for exception management and dynamic rerouting to improve response speed and accuracy.
• Drive ROI from digital transformation by enabling closed-loop, automated decision-making to deliver measurable gains in service, cost, and resilience.
• Deliver cost reductions through rigorous benchmarking and operational discipline, to uncover hidden value in optimised logistics networks.
• Strengthen the case for investment through evidence-based business cases grounded in real-world performance, to build credibility and secure buy-in.
• Equip senior logistics leaders with practical frameworks, to identify hidden value and drive measurable cost improvement.
• Transform reporting tools into real-time logistics intelligence through live data and predictive insight, to drive faster, action-oriented decision-making.
• Deliver measurable business impact through digital twin-enabled scenario planning, risk mitigation, and network optimisation, to improve resilience and efficiency at scale.
• Equip operations leaders with the tools and capability to move from reactive problem-solving to proactive logistics command, to strengthen control and network performance.
Execute Transformation at Scale: Align people, technology & operations for end-to-end supply chain successÂ
• Align cross-functional teams around shared transformation goals by establishing unified KPIs, accountability frameworks, and communication channels – to accelerate execution and sustain momentum across planning and logistics.
• Integrate digital tools and human expertise by embedding AI, automation, and data-driven workflows into daily operations - so teams can act faster and smarter, without sacrificing strategic judgment.
• Embed transformation into operating rhythms by designing scalable pilot-to-enterprise rollouts, continuous improvement cycles, and feedback loops - to ensure change sticks and delivers measurable impact across the supply chain.
• Equip supply chain leaders with commercial frameworks and board-level narratives, to position the function as a driver of growth and competitive advantage.
• Deliver strategic influence by translating operational performance into boardroom metrics, to secure sustained investment in resilience, technology, and talent.
• Build cross-functional relationships and governance structures, to give supply chain a permanent seat at the strategy table.
• Accelerate team performance by equipping operations teams with digital tools, real-time data, and agile workflows, to drive faster, more accurate execution across the supply chain.
• Foster workforce engagement by blending generational skillsets and upskilling for AI and automation, to build a culture of adaptability and continuous improvement.
• Strengthen operational resilience by embedding change management and practical enablement strategies, to ensure teams can respond effectively to disruption and deliver consistent results.
• Equip leadership teams with proven frameworks to attract and retain digital-native talent, to prevent capability gaps from constraining operational ambition.
• Drive cultural transformation by embedding agility and cross-functional ownership into global supply networks, to build a more responsive operating model.
• Strengthen organisational resilience by developing the next generation of supply chain leaders, to close capability gaps before future disruptions emerge.
• Build orchestration architecture that replaces linear supply chain management with dynamic, multi-directional networks, to meet evolving market and customer demands.
• Deliver enterprise agility by connecting supplier, logistics, and customer data into a real-time intelligence layer, to respond before disruption spreads.
• Accelerate commercial performance by deploying digital platforms across the supply network, to turn fragmented relationships into coordinated value-generating ecosystems.
