This Specialization integrates supply chain management with data analytics and AI-augmented decision-making. Through six courses spanning the source, make, move, and sell functions, you will learn to frame and solve problems, apply data analytics skills (visual storytelling and statistical analysis in Excel and Google Sheets), and critically interpret results to make sound business decisions. You will also develop the critical thinking and human judgment needed to validate AI-generated outputs, and to know when to trust — or question — AI-assisted analysis, so you can frame, solve and decide like a business-savvy, AI-ready supply chain analyst.
Supply Chain Analytics Essentials: The financial impact of supply chains (the butterfly effect), supply chain pain points and how analytics may relieve them, job market trends and requirements.
Business intelligence and Competitive Analysis: Problem framing and prioritization, how to isolate the operational issues with the greatest financial stakes?
Demand Analytics: Data analytics, visualization and interpretation for demand forecasting and planning.
Inventory Analytics: Discover and solve inventory problems - an essential part of Sales & Operations Planning.
Sourcing Analytics: Supplier intelligence, bargaining power analysis, and supplier benchmarking to identify the right suppliers globally.
Supply Chain Analytics: Data analytics and interpretation to design and evaluate logistics and distribution strategies.
Applied Learning Project
Each course provides on an authentic, data-driven project that lets learners apply what they've learned to a real business problem. Learners will diagnose supply chain potential and risk in financial terms, identify and prioritize problems for a company of their choosing, build and validate forecasting models using real-world data, design and evaluate logistics strategies for a large-scale distribution network, uncover and validate inventory-related problems, and evaluate and select global suppliers for a company of their choosing — applying diagnostic, predictive, and prescriptive analytics tools throughout.
