08/2024 Proceedings

Bender, Benedict | Bretschneider, Sina | Fattah-Weil, Jasmin

Advances in Demand Forecasting: A Systematic Review of Methods, The Role of AI, and Data Strategies in Manufacturing


This systematic literature review highlights the gap in demand forecasting in the manufacturing sector, which is challenged by complex supply chains and rapid market change. Traditional methods fall short in this dynamic environment, highlighting the need for an approach that combines advanced forecasting techniques, high-quality data, and industry-specific insights. Our research contributes by evaluating advanced forecasting methods, the effectiveness of AI and data strategies to improve accuracy. Our analysis reveals a shift towards machine learning and deep learning to improve accuracy and highlights the untapped potential of external data sources. Key findings provide both researchers and practitioners with guidance on effective forecasting strategies and key data types and offer an integrated framework for improving forecasting accuracy and strategic decision-making in manufacturing. This work fills a critical research gap and provides stakeholders with actionable insights to manage the complexity of modern manufacturing, representing a significant advance in forecasting practice.

Category Proceedings
Authors Bender, Benedict; Bretschneider, Sina; Fattah-Weil, Jasmin
Place of publication Salt Lake City
Book title Proceedings of the thirtieth Americas Conference on Information Systems, Salt Lake City, 2024
Date 08/2024
Conference Title Demand Forecasting, Sales Forecasting, Forecasting Methods, Manufacturing Industry, Forecasting Data, Systematic Literature Review
Publisher Association of Information Systems