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Course Overview

In today’s complex and competitive business environment, data-driven decision-making is essential for achieving supply chain excellence. This course equips participants with the analytical skills and tools necessary to optimize supply chain operations, improve efficiency, and drive strategic outcomes. Through a blend of theoretical concepts, practical case studies, and hands-on exercises, participants will explore various analytics techniques and their applications across key supply chain functions. From demand forecasting and inventory optimization to network design and risk management, participants will learn how to leverage analytics to enhance performance, mitigate risks, and create value across the supply chain.

Target Audience

This course will be particularly beneficial for:

  • Mid-career professionals in operations-management
  • Analysts
  • Senior leaders or heads of operations
  • Supply chain consultants

Learning Outcomes

By the end of the course, participants should be able to:

  1. Understand the role and importance of analytics in supply chain management.
  2. Learn key analytical techniques and tools used in supply chain analysis.
  3. Develop the ability to collect, process, and analyze supply chain data.
  4. Apply analytics to solve common supply chain challenges and improve performance.
  5. Explore best practices and case studies of successful analytics-driven supply chain initiatives.
  6. Gain practical experience with data visualization and reporting tools.
  7. Develop skills to communicate analytical insights effectively to stakeholders.

Course Duration

  •  Two (2) days online

Course Outline

Module 1: Introduction to Supply Chain Analytics

  • Overview of supply chain management and analytics
  • The role of data and analytics in supply chain decision-making
  • Key concepts and terminology in supply chain analytics

Module 2: Data Collection and Management

  • Data sources in supply chain management
  • Data collection methods and best practices
  • Data cleaning, processing, and management

Module 3: Descriptive Analytics

  • Basics of descriptive analytics
  • Techniques for summarizing and visualizing supply chain data
  • Tools for descriptive analytics: Excel, Tableau, and Power BI

Module 4: Predictive Analytics

  • Introduction to predictive analytics and forecasting techniques
  • Time series analysis and demand forecasting
  • Applications of predictive analytics in inventory management and demand planning

Module 5: Prescriptive Analytics

  • Overview of prescriptive analytics and optimization techniques
  • Linear programming and optimization models for supply chain planning
  • Scenario analysis and decision support systems

Module 6: Supply Chain Performance Metrics

  • Key performance indicators (KPIs) for supply chain management
  • Measuring and analyzing supply chain performance
  • Benchmarking and continuous improvement strategies

Module 7: Advanced Analytics and Emerging Technologies

  • Introduction to machine learning and artificial intelligence in supply chain analytics
  • Big data analytics and IoT applications in supply chain management
  • Blockchain and its impact on supply chain transparency and security

Module 8: Case Studies and Best Practices

  • Analysis of successful analytics-driven supply chain initiatives
  • Lessons learned from leading organizations
  • Guest lectures and insights from industry experts
  • Group projects and presentations on applying analytics to solve supply chain challenges

Training methodology

The training delivery model will be virtually over two (2) days. The training will include hands-on and practice utilizing tools such as Tableau, Power BI, R, Python, etc.

Course Costing


Course Dates

20-21 February 2024

03-04 October 2024

04-05 December 2024

Course Registration

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Established in 2019, the African Institute for Supply Chain Research (AISCR) provides supply chain research, education, outreach, and networking solutions for a better Africa.





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