Demand Planning and Forecasting: Technical Foundations for Supply Chain Excellence

Abstract

Demand planning and forecasting represent critical capabilities in modern supply chain management, enabling organizations to anticipate customer needs while optimizing inventory investments and operational resources. This article explores the technical foundations of effective demand planning, including statistical frameworks, computational requirements, and advanced methodologies. Starting with baseline forecasting approaches, the discussion progresses through consensus planning architectures, hierarchical aggregation systems, and cross-functional integration mechanisms. The article then examines quantitative forecasting techniques like machine learning models and causal modeling alongside qualitative forecast integration mechanisms. Technical infrastructure requirements spanning data integration, computational environments, visualization tools, and system scalability considerations are detailed. Performance evaluation metrics and emerging technical trends complete the overview, providing a comprehensive framework for developing sophisticated demand planning capabilities that balance statistical rigor with practical business application.