Course Outline

Module 1: Introduction to Data-Driven Decision Making

• Overview of data-driven decision-making principles.
• The role of data in supply chain management.
• Key concepts and tools for data analysis.
• Case Study/Practical: Analyzing supply chain data to identify trends.

Module 2: Data Collection and Management

• Techniques for collecting and managing supply chain data.
• Tools and technologies for data management.
• Best practices for ensuring data quality and accuracy.
• Case Study/Practical: Developing a data collection plan for a supply chain.

Module 3: Data Analysis Techniques

• Techniques for analyzing supply chain data (e.g., statistical analysis, predictive modeling).
• Tools and software for data analysis.
• Case studies of data analysis in supply chain management.
• Case Study/Practical: Conducting a data analysis for a supply chain scenario.

Module 4: Applying Data-Driven Insights

• Techniques for applying data insights to supply chain decision-making.
• Strategies for using data to optimize supply chain processes.
• Case studies of successful data-driven decision-making.
• Case Study/Practical: Developing an optimization plan based on data insights.

Module 5: Implementing Data Analytics Tools

• Overview of data analytics tools and technologies.
• Techniques for implementing and using data analytics tools.
• Integrating data analytics into supply chain operations.
• Case Study/Practical: Implementing a data analytics tool in a supply chain environment.

Module 6: Data-Driven Forecasting and Planning

• Techniques for data-driven forecasting and demand planning.
• Using data to improve forecasting accuracy and planning processes.
• Case studies of data-driven forecasting in supply chains.
• Case Study/Practical: Developing a forecasting model based on data analysis.

Module 7: Performance Measurement and Metrics

• Key performance indicators (KPIs) for data-driven supply chain management.
• Techniques for measuring and evaluating supply chain performance.
• Case studies of performance measurement using data.
• Case Study/Practical: Creating a performance measurement system based on data.

Module 8: Data Visualization and Communication

• Techniques for visualizing and communicating data insights.
• Tools and methods for effective data visualization.
• Case studies of data visualization in supply chain decision-making.
• Case Study/Practical: Developing a data visualization for a supply chain scenario.

Module 9: Managing Data Privacy and Security

• Understanding data privacy and security considerations.
• Techniques for ensuring data security in supply chain management.
• Case studies of data privacy and security best practices.
• Case Study/Practical: Developing a data security plan for supply chain data.

Module 10: Future Trends in Data-Driven Supply Chain Management

• Emerging trends and technologies in data analytics for supply chains.
• Preparing for future developments in data-driven decision-making.
• Developing a strategy for leveraging future data trends.
• Case Study/Practical: Analyzing future trends and their impact on supply chain data.