vp, Data & AI, Value Chain
- Define and own the multi-year Value Chain Data & AI product vision and roadmap, aligned to global supply chain, operations, and sustainability priorities.
- Serve as the primary Data & AI partner to the Chief Value Chain Officer (CVCO) and value chain global leadership teams .
- Act as the data and AI owner for the end-to-end value chain operations, including:
- Demand and supply forecasting, scenario planning, and deployment analytics
- Manufacturing performance, capacity, yield, and quality intelligence
- Procurement, vendor performance, and cost optimization analytics
- Inventory, logistics, fulfillment, and service-level decision intelligence
- Operational sustainability and EHS analytics
- Maintain fluency in the value chain technology landscape (e.g., SAP S/4HANA, Kinaxis, Anaplan, MES), while partnering with system/platform owners to ensure data readiness and integration.
- Represent Value Chain Data & AI priorities in enterprise forums, governance bodies, and investment reviews to align business and data strategies globally.
- Translate value chain data and AI strategies into defined OKRs, operational KPIs, financial impacts, and P&L outcomes.
- Collaborate with emerging technologies teams to assess and introduce new ML, optimization, and decision-intelligence capabilities into the value chain roadmap.
- Lead the end-to-end delivery of the Value Chain Data & AI product portfolio, ensuring solutions are designed for scalability, reuse, and cross-functional integration across global operations.
- The product portfolio spans:
- Planning & Forecasting Intelligence - demand and supply modeling, scenario planning, deployment analytics, and operational visibility.
- Manufacturing & Quality Intelligence - production performance, capacity and yield analytics, quality and safety insights, and plant-level optimization.
- Procurement & Vendor Intelligence - supplier performance, cost optimization, and sourcing analytics.
- Logistics & Fulfillment Intelligence - i nventory optimization, distribution, service-level performance, and network visibility.
- Operational Sustainability & EHS Intelligence - sustainability metrics and EHS analytics.
- Oversee prioritization, funding, and execution and measure impact across global and regional value chain roadmaps
- Own the end-to-end data architecture and data quality strategy for value chain datasets, ensuring availability, trust, and readiness.
- Oversee the development, deployment, and lifecycle management of forecasting engines, optimization tools, agent-based automation, dashboards, and other data products
- Partner with the Build Organization (Engineering, AI/ML, Platforms) to align technical architecture, secure resourcing, ensure delivery excellence, and drive speed-to-value.
- Serve as the Data & AI representative within Value Chain leadership forums, guiding priorities and investments.
- Drive measurable adoption across regional supply chain, manufacturing, procurement, and logistics teams, ensuring data and AI solutions are embedded into daily planning, execution, and decision workflows.
- Foster cross-functional collaboration with Finance, Technology, Operations, and Sustainability partners to align analytics and AI initiatives to enterprise priorities.
- Champion education, enablement, and operating model change to increase data-driven decision-making across value chain functions.
- Advocate for responsible, ethical, and transparent AI usage in operational, forecasting, and optimization use cases.
- Ensure adherence to enterprise data governance, privacy, and security standards.
- Manage domain budgets, resource allocation, and OKRs in coordination with enterprise strategy and finance teams.
- Establish transparent reporting for leadership, including product performance dashboards, delivery milestones, and realized business impact.
- Partner with Governance, Architecture, and Strategy & Ops to continuously evolve operating models, tooling, and delivery maturity.
- 12-15+ years of progressive experience in data, analytics, product management, or technology leadership roles within supply chain, operations, or manufacturing environments.
- Deep understanding of end-to-end value chain ecosystems, including demand and supply planning, manufacturing operations, procurement, logistics, quality, and operational sustainability.
- Expertise in advanced analytics and ML use cases such as forecasting, scenario modeling, optimization, inventory planning, and operational performance analytics.
- Technical fluency in data platforms, integration frameworks, and modern cloud-based architectures (e.g., Azure, Databricks).
- Experience building and leading global teams and driving cross-functional digital, data, or AI transformation initiatives across operations and supply chain functions.
- Proficiency in Agile and product-centric delivery methodologies.
- Strong business acumen with experience delivering measurable improvements in service levels, cost performance, resilience, and operational KPIs through data and AI solutions.
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