Education

We offer tailored educational methodologies designed to meet learners at every stage of the digital transformation journey, from early-stage professionals seeking foundational knowledge to leaders guiding mature organizations. We combine flexible, online-driven learning with on-campus engagement. 

Keynotes

Our keynotes are high-impact presentations to engage the audience and share our latest research, experiences, and challenges from the research and insight delivered by leading faculty and researchers from the Lab. These sessions offer strategic insights on the latest digital supply chain transformation trends, AI adoption frameworks, and advanced analytical methods. We share our research findings on how organizations must reimagine decision-making and establish new supply chain partnerships to achieve greater agility and future-readiness.

Maria Saenz presenting to a crowd at DPW

Executive Education

Supply Chain Management: Leading with AI and Digital Transformation

This 6-week online executive program, offered with MITx Pro and Emeritus, provides a holistic view of digital transformation in the supply chain. The curriculum focuses on the strategic perspective and the necessary digital supply chain visions and capabilities. We examine real case studies and essential topics for discussions, including:

Digital Supply Chain Transformation Roadmaps  
End-to-End Visibility 
Human-AI Collective Intelligence
Artificial Intelligence 
New Technological Trends in Supply Chain Management

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On Campus Master Courses

The Digital Supply Chain Transformation Lab offers specialized courses exclusively for MIT Graduate Students. These in-depth courses are designed to equip the next generation of supply chain leaders with cutting-edge expertise in the field. These offerings provide the rigorous academic foundation needed to transform supply chains and digital adoption, ensuring students are prepared to navigate the complex and conflicting realities of AI-driven supply chains.

SCM 261: Supply Chain Transformation: Case Studies

A combination of case studies and industry speakers covering the strategic and operating issues in supply chain transformation. Focuses on the pragmatic creation of supply chain capabilities, including resilience, omnichannel, E2E visibility, entrepreneurship, servitization, E2E automation, and AI.

SCM 294: Digital Supply Chain Transformation

This course equips MIT graduate students with the strategic mastery to lead and execute digital transformation across complex value chains. It’s a hands-on environment focusing on AI, end-to-end visibility, and advanced analytics to build a unified, future-ready supply chain strategy.

Key learning outcomes:

Strategic Mandate: Lead and execute digital transformation, moving beyond fragmented projects to craft a unified supply chain strategy.

Applied Experimentation: Hands-on work with key capabilities like AI integration, advanced analytics, and end-to-end visibility.

Immediate Impact: Translate theory into action, graduating ready to immediately implement and drive the next generation of supply chain performance.

SCM 254: Analytical Methods for Supply Chain Management II

This course introduces the advanced statistical tools and causal inference methodologies required by modern supply chain managers.

Key analytical expertise:

Focus: Applied techniques to solve critical supply chain and logistics problems.

Topics: Includes principal component analysis, clustering, advance regression and prediction, experimental design and causal inference.

Tools: Instruction is provided in Python programming to immediately apply data analysis techniques to real-world challenges.

SCM C51: Advanced Machine Learning Applications for Supply Chain Management

This advanced course is designed for practitioners looking to leverage Machine Learning (ML) for enhanced efficiency, accuracy, and scalability in supply chain management. It moves beyond foundational concepts to apply cutting-edge ML models and algorithms specifically to complex, real-world supply chain challenges.

Key focus areas:

Deep Application: Master a blend of theoretical knowledge and practical insights into selected ML models tailored for supply chain needs.

Model to Market: Focus on practical application and building data-driven solutions for key business problems.

Real-World Implementation: Intensive discussion on implementation challenges, large-scale productionalization, and monitoring of ML models in practice.

On-site customized workshops

We enhance our digital learning approach with experiential on-site workshops held at MIT for the particular needs of companies. These in-person customized sessions facilitate joint discussions among diverse teams and partners to collectively analyze digital implications, strategic integration for implementing new digital capabilities and visualize outcomes across complex supply chain scenarios.