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Research Paper | Computer Science & Engineering | India | Volume 10 Issue 7, July 2021 | Popularity: 5.8 / 10
Artificial Intelligence - Enabled Demand and Supply Planning: Revolutionizing Forecasting and Optimization in Supply Chains
Harish Narne
Abstract: Demand and supply planning are pivotal to supply chain management, ensuring businesses maintain a balance between meeting customer needs and optimizing operational costs. Traditional approaches to planning, reliant on historical data and statistical methods, often fall short in managing the complexity and unpredictability of modern global markets. The rise of Artificial Intelligence (AI) has introduced transformative solutions that enhance the accuracy, agility, and efficiency of demand and supply planning processes. AI technologies, such as machine learning (ML), natural language processing (NLP), and reinforcement learning, provide advanced capabilities for predictive analytics, real - time decision - making, and optimization. By leveraging diverse data sources, including historical sales, social media trends, and market reports, AI can uncover hidden patterns, anticipate demand fluctuations, and recommend optimal supply chain strategies. This paper explores the application of AI in demand and supply planning, highlighting its potential to reduce forecasting errors by up to 25%, improve inventory management efficiency by 20%, and minimize operational costs by 15%. It further discusses the integration of AI with existing systems, its role in enhancing supply chain resilience, and the challenges associated with data complexity, scalability, and interpretability. Through case studies and experimental analysis, this research underscores the transformative impact of AI, providing actionable insights for businesses seeking to build adaptive and efficient supply chains. Finally, the paper outlines future directions, emphasizing the development of explainable AI models, decentralized learning frameworks, and sustainable supply chain practices to address evolving market demands and global challenges.
Keywords: Artificial Intelligence, Demand Planning, Supply Planning, Predictive Analytics, Machine Learning, Inventory Optimization, Supply Chain Management, Natural Language Processing, Data Integration, Reinforcement Learning, Data - Driven Decision - Making
Edition: Volume 10 Issue 7, July 2021
Pages: 1556 - 1560
DOI: https://www.doi.org/10.21275/SR21078105302
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