Senior Exe / AM Data Analytics Supply chain

The Senior Executive / Assistant Manager of Data Analytics in the Supply Chain will play a key role in providing strategic insights through the analysis of supply chain data. This position is responsible for leveraging data analytics to optimize the supply chain, improve decision-making, forecast demand, manage inventory levels, and reduce costs. The ideal candidate will have strong experience in both supply chain processes and data analytics, with a focus on improving operational efficiency and driving performance.

Key Responsibilities:

Data Analysis & Reporting:

• Collect, analyze, and interpret large datasets related to supply chain activities (e.g., procurement, logistics, inventory, and demand).
• Develop and maintain reports and dashboards to track key performance indicators (KPIs) such as delivery performance, inventory turnover, and cost efficiency.
• Provide actionable insights to improve supply chain operations, focusing on cost optimization and process improvement.

Demand Forecasting & Inventory Management:

• Utilize historical data, predictive analytics, and statistical modeling techniques to forecast demand and inventory needs.
• Support inventory optimization by analyzing trends and identifying opportunities for cost savings and improved stock levels.

Process Improvement:

• Collaborate with cross-functional teams (e.g., logistics, operations, procurement) to identify and address inefficiencies in the supply chain.
• Recommend data-driven solutions to improve supply chain operations, reduce lead times, enhance supplier performance, and minimize operational costs.

Supply Chain Optimization:

• Leverage data analytics to optimize the flow of goods from suppliers to customers, ensuring on-time delivery and inventory availability.
• Use data to support strategic decisions related to sourcing, logistics, and supply chain network design.

Stakeholder Communication & Reporting:

• Prepare and present data-driven insights and recommendations to senior management, including supply chain performance metrics and potential improvements.
• Collaborate with stakeholders across various departments to ensure alignment on supply chain initiatives and data-driven goals.

Project Management:

• Lead or participate in data-driven supply chain projects aimed at improving efficiency, cost savings, and overall performance.
• Monitor and track progress, ensuring project milestones are met on time and within budget.

Continuous Improvement:

• Stay up-to-date with the latest trends and best practices in supply chain analytics, implementing new methodologies and tools to enhance data analysis and reporting.
• Continuously improve data collection processes, tools, and methodologies to ensure accuracy and efficiency.