OPM 506: Data and Decision Management in Supply Chains

Contents
This module provides a practice-oriented introduction to data and decision management in supply chains, drawing on the experience of two senior supply chain experts. It focuses on how data is structured, managed, and leveraged to support decision-making and execution in modern supply chain organizations.
The course begins with an introduction to the role of data and decision management in supply chains and establishes the foundations of data modelling. It then explores how IT systems enable decision-making processes, with particular emphasis on enterprise systems and the distinction between master and trans­actional data.
Building on this foundation, the module examines data structures and models used in supply chain planning, highlighting how data supports key processes such as forecasting, inventory planning, and network decisions. Students are introduced to supply chain analytics, including key performance indicators (KPIs) and end-to-end data analysis approaches used in practice.
The course further addresses how data-driven decisions are trans­lated into operational execution, emphasizing the integration between planning and execution systems. Advanced topics include the role of artificial intelligence, world models, and machine learning-based forecasting in improving decision quality and automation.
In addition, the module covers data management processes, governance structures, and organizational aspects required to ensure data quality and consistency. It also discusses how companies derive business value from data and how data capabilities contribute to competitive advantage.
The course concludes with a discussion of data management and an outlook on future developments in data and decision management, including emerging technologies and evolving roles in supply chain organizations. Throughout the module, real-world examples, project experiences, and practical frameworks from consulting practice are used to illustrate concepts and challenges.

Learning outcomes
Upon successful completion of this module, students will:

• understand the fundamentals of data modelling and decision-making,
• understand how IT systems support decision-making in supply chains,
• be familiar with supply chain data models, including ERP and planning data structures,
• understand the role of analytics in supply chain decision-making and execution,
• gain an introduction to AI, world models, and machine learning applications in supply chains,
• understand key data management processes, the business value of data, and future developments in data and decision management.

Necessary prerequisites
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Recommended prerequisites
Basic knowledge in supply chain management