Manager, Supply Chain Analytics and Business Insights

At Duke Health, we're driven by a commitment to compassionate care that changes the lives of patients, their loved ones, and the greater community. No matter where your talents lie, join us and discover how we can advance health together.

Lead Duke Health Supply Chain’s analytics and business insights function by building, maintaining, automating, and improving the reporting tools that allow leaders to see performance, manage value, and act on opportunities across the enterprise. This manager owns Power BI dashboards and related business intelligence products for sourcing, shared services, IT, facilities, indirect spend, economic mobility, and other supply chain verticals. The role converts data into usable insight, trains leaders to use analytics tools, and creates new analysis solutions as business needs evolve.

• Strategic Leadership:
  Lead the analytics and business insights function for Enterprise Supply Chain with clear ownership for reporting products, dashboard reliability, and actionable data interpretation.
• Solution Design:
  Translate executive, sourcing, operational, shared services, and economic mobility needs into practical analytics solutions that support decision-making and measurable value creation.
• Reporting Environment:
  Create a disciplined reporting environment where leaders can distinguish activity, opportunity, projected value, realized value, risk, and performance trends.

• Dashboard Creation:
  Create, maintain, and continuously improve Power BI dashboards for sourcing, shared services, IT, facilities, indirect spend, economic mobility, and other Supply Chain verticals.
• Reliability:
  Ensure dashboards are reliable, current, user-friendly, and aligned to the metrics and operating cadence used by Supply Chain leaders and stakeholders.
• Governance:
  Maintain data definitions, reporting logic, refresh cadence, dashboard governance, and version control so reported information remains consistent and trusted.

• Process Automation:
  Automate data collection and refresh processes that feed Power BI dashboards and other business intelligence tools.
• Pipeline Development:
  Identify manual reporting processes that can be replaced with repeatable data pipelines, standardized templates, automated extracts, and controlled reporting routines.
• Cross-Functional Partnership:
  Partner with technology, operations, sourcing, finance, and other data owners to improve data quality, reduce rework, and increase reporting speed.

• Custom Solutions:
  Create net new analysis solutions as needed for each Supply Chain vertical, including sourcing, operations, shared services, technology, facilities, purchased services, contracting, economic mobility, and university-facing work.
• Performance Tracking:
  Develop tools that support savings pipeline tracking, spend segmentation, supplier concentration, contract adoption, cycle time, project performance, inventory indicators, service metrics, and stakeholder reporting.
• Data Translation:
  Convert complex data into clear narratives, visuals, and recommendations that help leaders understand the issue, decision point, expected impact, and next action.

• Tool Training:
  Train Supply Chain leaders and teams on available analytics tools, dashboard use, interpretation, and appropriate application of business intelligence products.
• Operational Support:
  Support leaders in using analytics during operating reviews, QBRs, executive briefings, initiative tracking, supplier discussions, and performance management routines.
• Adoption Improvement:
  Improve analytics adoption by making tools intuitive, decision-oriented, and connected to the work leaders are accountable to manage.

• Team Management:
  Lead three analytics analysts responsible for data preparation, dashboard maintenance, ad hoc analysis, reporting support, and business intelligence product development.
• Process Standardization:
  Establish standard work for intake, prioritization, dashboard development, data validation, documentation, release management, user training, and ongoing support.
• Culture Building:
  Build a high-accountability analytics culture that is service-oriented, technically capable, curious, responsive, and focused on decision usefulness rather than reporting volume.