MG107: Management Analytics in the Age of Big Data

Big Data and the rise of AI technology have the potential to transform firms, markets and even entire societies. This poses significant questions: What will the managerial landscape look like as data-intensive technologies proliferate? How should managers approach data and statistical analysis in this age?

This course offers students an overview of the economic potential of Big Data and AI. It begins by describing the rise of Big Data and the burgeoning field of AI, and proceeds to consider the implications of these new technologies for managers and for society as a whole.

With this foundation, students will examine managerial decision-making using data analytics. Big Data does not solve all of managers’ problems; even with increasing amounts of data and better AI, managers still need to make decisions under incomplete information (solve statistical inference problems) and to distinguish between correlation and causation (solve causal inference problems). Finally, students will learn how to apply their new understanding of statistical and causal inference to the construction of regression models.

The course is designed to provide students with an understanding of the foundational elements of data analysis and the use of statistical thinking in the context of managerial decision-making in today’s age of big data.

It is important to note that the course is primarily conceptual and analytical, rather than technical, and does not cover programming techniques. The tools developed in the course are the interpretation and evaluation of data analytics, and managerial decision-making based on such analytics.

Prerequisites: There are no prerequisites for this course 

Level: 100 level. Read more information on levels in our FAQs

Fees: Please see Fees and payments

Lectures: 36 hours

Classes: 18 hours

Assessment: One written examination and one project on strategy identification

Typical credit: 3-4 credits (US) 7.5 ECTS points (EU)

Please note: Assessment is optional but may be required for credit by your home institution. Your home institution will be able to advise how you can meet their credit requirements. For more information on exams and credit, read Teaching and assessment

The course is designed to provide students with an understanding of the foundational elements of data analysis and the use of statistical thinking in the context of managerial decision-making in today’s age of big data.

It will therefore be well-suited to anyone looking to embark upon a career or further studies in Business Management, Business Analytics or Consulting.

• Critically evaluate the development of big data and AI technology.

• Develop a framework for managerial decision-making under uncertainty.

• Evaluate causal arguments and design experiments to identify causal relationships.

• Construct and interpret multivariate regression models.

The design of this course is guided by LSE faculty, as well as industry experts, who will share their experience and in-depth knowledge with you throughout the course.