L'Oréal - Clark, NJ
posted 3 months ago
We are seeking a Sr Manager, Supply Chain Data & Analytics with a passion for transforming data into actionable reports and insights to enable our goal of creating a more efficient and responsive supply chain. This role presents a unique opportunity to harmonize data from various sources, optimize inventory management, and drive strategic initiatives that will enhance agility and deliver great value to the End-To-End Supply Chain function of the LDB Division, currently representing $2.3B in revenue for L'Oreal USA. This role will also have an impact on the Global business of LDB, as it will also support the LDB Global S&OP team of the American DMI Brands. You will lead a team responsible for developing and implementing data-driven solutions that enhance supply chain visibility, forecasting accuracy, inventory optimization, and overall operational efficiency. This is a high-impact role with visibility across the organization as you will operate in a transversal scope of the Operations LDB team. As the Sr Manager, you will spearhead the development and implementation of comprehensive data & analytics tools for our US Dermatological Beauty Operations team, focusing on: Data Integration & Governance: Lead the assessment, integration, and standardization of data from diverse sources across our supply chain ecosystem, including SAP system, warehouse management systems, transportation networks, and external partners. Champion data governance and data quality initiatives to ensure accuracy, consistency, and reliability of supply chain data, laying a solid foundation for advanced analytics and reporting. Collaborate with IT and global data teams to optimize data infrastructure and ensure data accessibility. Inventory Optimization: Develop and implement analytics models to optimize inventory levels across the supply chain, minimizing costs while ensuring product availability and meeting customer service level targets. Enhance demand forecasting accuracy by supporting the team on their needs to organize and leverage data-driven analytics & tools. Complexity Reduction & Process Improvement: Identify opportunities to streamline and optimize supply chain processes through data analysis, leveraging automation, process mining techniques, and other innovative solutions to drive efficiency and reduce costs. Collaborate closely with cross-functional stakeholders in the Supply Chain field to implement data-driven improvements that enhance agility and responsiveness. Performance Measurement & Reporting: Transform complex data into compelling visualizations, dashboards and reports that effectively communicate supply chain performance, identify key trends, and drive informed decision-making at all levels of the organization. Manage and ensure that the monthly and weekly reporting activities are properly executed. Make use of data automation when adequate. Champion a data-driven culture by communicating insights and recommendations in a clear, concise, and persuasive manner to both technical and non-technical audiences. Foster a culture of continuous improvement by identifying opportunities to leverage data and technology to optimize supply chain processes and drive efficiencies. Team Management: Lead, mentor, and inspire data analysts and scientists, fostering a culture of collaboration, innovation, and excellence. Contribute to the broader LDB Supply Chain scope of team management (monthly team meetings, goals setting, trainings, etc).