Data-Driven Decision Making and Supply Chain Management - Strategic Analytics for Executives

Target group

Junior and senior managers in organizations who:

• Work with supply chain operations
• Need to understand digitalization and automation technologies
• Make strategic decisions about data collection and management
• Want to leverage data analytics and draft organizational policies for gaining competitive advantages without being technical specialist.

Managers working as import and export managers and handling production flows are highly recommended to join the course.

Content

The course is divided into four interconnected modules.

1. The first module begins with an exploration of Supply Chain Management (SCM) and emphasizes digitization and automation techniques that improve the efficiency and resilience of supply chains. Students will learn what digitization and automation mean in manufacturing and how they have evolved over time. They will also gain knowledge of tools for assessing technology portfolios. In addition, students will gain more knowledge of how to analyze supply chains, identify critical suppliers, and use tools to visualize key performance indicators (KPIs) to mitigate risk.
2. The second module explores basic data concepts and shows how different types of data – from IoT sensor outputs to production logs – can provide a competitive advantage in industries such as manufacturing. This will be discussed using real-world case studies.
3. The third module focuses on data collection and data quality, where strategies for selecting reliable data sources, ensuring data quality in industrial datasets, and applying frameworks to solve quality challenges are discussed, complemented by insights from leading executives in the field.
4. Finally, the course concludes with a case study to text analytics, where students learn to extract actionable insights from unstructured text documents, such as maintenance reports or supplier communications. This approach is validated through real-world datasets, demonstrating its effectiveness in optimizing performance using maintenance-related text data.

The goal of the course is for you to be able to:

• Define Supply Chain Management (SCM).
• Explain the concepts of automation, digitalization, and blockchain.
• Know how technology portfolio assessments could be used for technological transitions.
• Use best practices to create efficient, digitized, and automated supply chains.
• Explain basic data concepts, including data types, big data, and the strategic value of data.
• Develop strategies to identify, acquire, and manage organizational data resources.
• Understand and define data quality, including methods for measuring and improving it.
• Evaluate data quality issues and implement improvement frameworks.
• Think long-term and find unique ways to make data valuable to your organization.
• Learn how to process text data and create insights that can be used for strategic planning processes. For example, how can product performance be optimized using text error data?

This course is developed within the project Smart Industry phase 2 and funded by the Swedish Knowledge Foundation (KK-stiftelsen).

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