Manager, Supply Chain Intelligence

Overview

Lutron Electronics Co., Inc. has an immediate opening for a Manager, Supply Chain Intelligence within our Operations Information and Action (OIA) group. In this role, you will lead cross-functional efforts to improve how our global supply chain makes decisions, takes action, and learns from outcomes. You will combine supply chain expertise, analytical and AI fluency, and change leadership skills to deliver practical, responsible, and measurable improvements in service, quality, resilience, cost, working capital, and productivity.

• Partner with Operations and enterprise leaders to identify, define, and prioritize decisions where Decision Intelligence (DI), analytics, automation, or AI can materially improve business outcomes.
• Maintain a transparent portfolio and roadmap that balances strategic value, feasibility, data readiness, operational risk, time to value, and organizational capacity.
• Build business cases and define outcome measures tied to service, cost, working capital, quality, resilience, productivity, responsiveness, employee experience, and customer experience.
• Guide high-impact initiatives from discovery and prototyping through deployment, adoption, sustainment, benefit tracking, and scale.

• Map critical decision workflows, including signals, context, tradeoffs, decision rights, actions, outcomes, feedback, and failure modes.
• Determine when a person, AI system, or human-AI combination is best suited to perform the work or make the decision.
• Design fit-for-purpose controls for recommendations and automated actions, including approval, reversibility, escalation, monitoring, auditability, and accountable ownership.
• Use experiments, prototypes, and operational evidence to validate decision quality and workflow performance before scaling.

• Represent Operations needs, constraints, risks, and priorities in enterprise AI planning and governance processes.
• Translate operational problems into clear use cases, user needs, data requirements, decision requirements, and measurable success criteria.
• Ensure Operations deployments comply with enterprise standards for responsible AI, security, privacy, architecture, approved tools, and technical sustainment.
• Coordinate across Operations, data/intelligence center of excellence, IT, information product owners, analysts, data professionals, vendors, and other delivery partners to move solutions into reliable use.

• Identify and recruit subject-matter experts from Operations functions and facilities who can contribute part-time to DI/AI initiatives alongside their primary roles.
• Define contributor expectations, working methods, sponsorship, learning paths, and recognition in partnership with functional and plant leaders.
• Coach contributors in decision discovery, problem framing, experimentation, responsible tool use, adoption, and outcome measurement.
• Create a community that shares reusable patterns, lessons, prototypes, and success stories across Operations.

• Develop practical education for Operations leaders, practitioners, and contributors on Decision Intelligence, AI capabilities and limitations, responsible use, and human-AI collaboration.
• Facilitate cross-functional conversations that make tradeoffs explicit, establish clear decision ownership, and convert insights into action.
• Lead workflow and role redesign needed to embed new capabilities into daily management and operational processes.
• Use clear narratives and decision-focused communication to build understanding, sponsorship, trust, and sustained adoption.

• Use approved analytics, automation, generative AI, and prototyping tools to test concepts and demonstrate value without assuming responsibility for all production engineering.
• Work with technical partners to define production requirements, integration needs, controls, testing, deployment, and support models.
• Monitor usage, decision quality, operational outcomes, unintended effects, and user feedback after deployment.
• Stop, redesign, or scale initiatives based on evidence; capture lessons-learned so the operating model improves with each cycle.

• Bachelor's degree required;
  Degree in Supply Chain, Operations Management, Engineering, Business, Analytics, Information Systems, or a related field preferred
• 12+…