Demand Forecasting Analytics

Course Overview

A practical, analytics‑driven course that teaches learners how to use historical data, statistical models, and machine‑learning techniques to predict future demand. The course covers time‑series forecasting, causal modelling, seasonality analysis, scenario planning, accuracy measurement, and data‑driven decision‑making across supply chain, operations, finance, and retail environments.

Target Audience

• Supply chain, logistics, and inventory planning teams

• Operations and production planners

• Business analysts and data analysts

• Retail, e‑commerce, and merchandising professionals

• Students or professionals entering forecasting or operations analytics

Course Outcomes

• Understand core forecasting concepts, models, and demand drivers

• Analyse historical data to identify trends, seasonality, and patterns

• Apply time‑series techniques such as moving averages, ARIMA, and exponential smoothing

• Use causal and regression models to incorporate external factors

• Evaluate forecast accuracy using MAPE, RMSE, and bias metrics

• Build forecasting dashboards to support planning and decision‑making

• Use forecasts to optimise inventory, production, staffing, and supply chain operations

• Communicate forecasting insights clearly to business and leadership teams