Forecasting Principles for Industrial Engineering and Operations

Accurate forecasting is the backbone of efficient industrial operations, supply chain management, and resource allocation. Without reliable predictions, businesses face costly inventory shortages, overproduction, and operational bottlenecks. This text-based course guides you through the fundamental principles of forecasting within industrial engineering. You will transition from understanding core statistical concepts to selecting and applying the right qualitative and quantitative models for real-world operational challenges. What you will learn: Understand the critical role of forecasting in operations planning, inventory control, and capacity management. Apply qualitative forecasting methods, including consensus and market feedback, to long-term strategic planning. Calculate quantitative forecasts using time-series models, moving averages, and exponential smoothing techniques. Evaluate forecast accuracy using standard error metrics to continuously improve model performance. Explore modern data-driven forecasting trends, including predictive analytics concepts in supply chain planning. Analyze the advantages and limitations of different forecasting models to select the optimal approach for your operational needs. The course starts with foundational definitions and key terminology in industrial forecasting before walking you through step-by-step mathematical models and practical scenarios. You will practice interpreting data trends and refining forecast models through structured written exercises. Designed for aspiring industrial engineers, operations managers, and business analysts, this course requires no prior forecasting experience. Start reading today to master the forecasting techniques that drive modern industrial efficiency.