Director, Global Logistics Data & Analytics

Essential Duties & Responsibilities

The following outlines the key responsibilities for the role:

Define and execute a multi-year Global Logistics Analytics strategy aligned to Logistics priorities, transformation goals, and regional needs.

Establish the roadmap for operational reporting, executive scorecards, predictive insights, data products, and AI-enabled capabilities.

Partner with senior leaders across Logistics, Technology, Finance, and Distribution to identify high-value analytics opportunities.

Translate business priorities into measurable analytics initiatives with clear outcomes, owners, timelines, and value realization measures.

Lead analytics across the end-to-end logistics flow from supplier origin through distribution, transportation, final delivery, and customer arrival.

Develop decision-support capabilities for transportation, freight cost, carrier performance, capacity, lead time, inventory flow, productivity, and network performance.

Connect logistics execution to enterprise outcomes including service, margin, working capital, inventory availability, and customer experience.

Drive predictive and prescriptive analytics to anticipate risks, identify cost opportunities, reduce variability, and improve planning decisions.

Serve as owner and strategic product leader for the Logistics Analytics data product portfolio including product ownership, support, analysis, development, and testing.

Define, develop, and execute the Analytics technology roadmap governance for logistics data products across transportation, distribution, inventory movement, shipment tracking, and cost performance.

Establish standards for certified KPIs, data definitions, metadata ownership, source-system traceability, and data quality management.

Partner with Data & Analytics and Technology teams to ensure logistics data assets are scalable, governed, secure, reusable, and sustainable.

Lead the AI and advanced analytics agenda for Global Logistics, including use case identification, prioritization, governance, adoption, and value tracking.

Champion practical AI applications such as predictive risk detection, document review, exception management, productivity automation, forecasting support, and executive summarization.

Partner with Data Science, Technology, and business teams to move high-value AI concepts from idea to scalable production capability.

Build AI literacy and adoption through education, governance, reusable playbooks, and business-led use case development.

Own the global logistics BI portfolio, including Power BI dashboards, operational scorecards, executive KPI views, ad hoc analytics, and scalable reporting products.

Modernize fragmented reporting into governed, reusable, self-service analytics capabilities that reduce manual effort and improve decision speed.

Develop executive-ready reporting that clearly communicates business health, risks, opportunities, and recommended actions.

Manage reporting intake, prioritization, backlog governance, user adoption, and continuous improvement.

Provide logistics analytics leadership for enterprise transformation programs including SAP S/4

HANA, cloud analytics platforms, Azure data products, and data marketplace initiatives.

Represent Logistics in technology design, data migration, reporting modernization, platform selection, architecture, and change management discussions.

Ensure new capabilities align to logistics business needs and preserve data quality, KPI continuity, operational visibility, and business ownership.

Partner with IT and external providers to deliver analytics capabilities with strong governance and long-term sustainability.

Lead, coach, and develop a global analytics organization spanning managers, analysts, engineers, product owners, consultants, and delivery partners.

Build a high-performing culture focused on business partnership, ownership, curiosity, analytical rigor, communication, and measurable impact.

Strengthening capabilities in analytics strategy, BI, data engineering, AI, product ownership, governance, and supply chain domain expertise.

Establish clear roles, decision rights, prioritization routines, delivery standards, escalation paths, and cross-regional collaboration.

Manage analytics operating and capital budgets, including project investments, managed services, consultants, software, and platform-related spend.

Build business cases for analytics, automation, AI, and platform investments with clear value assumptions and measurable outcomes.

Lead vendor relationships from strategy and SOW development through delivery, governance, issue resolution, and value realization.

Prioritize the analytics portfolio based on…