Supply Chain Analytics Training Course

The Supply Chain Analytics Training Course equips supply chain, procurement, logistics, and planning professionals with the analytical methods, tools, and data skills needed to turn supply chain data into insights and better decisions across the end-to-end supply chain. In government entities, ministries, healthcare systems, banks, energy and utility companies, manufacturing, retail, and distribution organizations, and large corporations, supply chains generate large volumes of data from ERP, procurement, warehouse, transport, and supplier systems. Organizations that use this data effectively can reduce costs, improve service levels, manage risk, and respond faster to change. Despite having data, many organizations struggle to use it. Data may be spread across disconnected systems, inconsistent, or incomplete, reports may describe what happened without explaining why, and decisions may still rely mainly on experience and intuition. Analysis may be limited to basic spreadsheets, dashboards may display too many numbers without clear insights, and teams may lack confidence in statistical and optimization techniques. As a result, opportunities to reduce spend, optimize inventory, improve transport efficiency, and anticipate supplier and supply risks are often missed. This course provides a practical, applied introduction to supply chain analytics without requiring an advanced mathematical background. Participants learn the four levels of analytics, descriptive, diagnostic, predictive, and prescriptive, and how they support different supply chain decisions. The program covers building strong data foundations, including data sources, data quality, cleansing, integration, and governance, and applying core analytical techniques such as descriptive statistics, variability analysis, correlation, regression, segmentation, and root cause analysis. Participants then apply analytics across key supply chain areas, including spend and supplier analytics, demand and inventory analytics, warehouse and transport analytics, cost-to-serve analysis, and supply risk analytics. The course also introduces scenario and what-if analysis, simulation, and optimization using practical tools such as spreadsheet solvers, as well as an overview of machine learning applications. Participants learn data visualization and dashboard design, storytelling with data, and how to build analytics capability and a data-driven culture in their supply chain teams. The course is delivered through an interactive, hands-on approach using spreadsheet and business intelligence tools with realistic supply chain datasets. Participants leave with a supply chain data readiness assessment, a set of analytical templates, a spend and supplier analysis, an inventory and logistics analysis, a scenario and optimization model, a supply chain analytics dashboard design, and a supply chain analytics roadmap for their organization.