Market basket analysis for Supply Chain Management (Pilot)

Type of course:

Digital learning, Lesson

Language:

Duration:

10 minutes

Proficiency:

Intermediate

Target:

Manager, Professionals, Workers

SUMMARY

Are you curious about how data-driven techniques can transform supply chain operations? This lesson offers an overview into Market Basket Analysis (MBA), an essential tool for discovering relationships between items frequently purchased together.

Whether you’re optimizing inventory for a niche manufacturer or planning targeted marketing campaigns, this lesson equips you with the knowledge and skills to leverage MBA for actionable insights.

Through practical examples and real-world applications, you’ll learn to interpret key metrics, select appropriate algorithms, and implement strategies tailored to unique business needs. By the end of the lesson, you’ll have the tools to make data-driven decisions that enhance supply chain efficiency and customer satisfaction.

About The Author

Dilek Dustegor is a Professor of Computing Science at the University of Groningen in the Netherlands. She is interested in bridging the gaps between research, development and implementation using AI and automation. She is pursuing research about modeling, design and analysis of large scale / networked systems using IoT and ML techniques, with a special interest in smart city applications. She is a seasoned educator, and loves using the newest educational technologies for an enhanced learning experience.

Learning outcomes

By the end of this lesson, learners will be able to define Market Basket Analysis (MBA) and, its relevance in supply chain management.
By the end of this lesson, learners will be able to interpret and utilize key MBA metrics, such as support, confidence, and lift, to make data-driven decisions for inventory optimization, warehouse management, and demand forecasting.
By the end of this lesson, learners will be able to select the most appropriate MBA algorithm (Apriori or FP-Growth) based on the complexity and size of the data, ensuring the most effective analysis for different supply chain scenarios, from inventory control to targeted marketing strategies.