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Outstanding faculty. Applied excellence. Our MSO teaching is supported by ground-breaking research.
data mining and analytics
machine learning
decision modelling and analysis optimisation and stochastic modelling
operations, logistics and supply chain management
simulation, risk analysis and forecasting
energy, health services and financial engineering.
Assistant Professor Management Science and Operations
Assistant Professor of Management Science and Operations
Professor of Decision Sciences, Management Science and Operations; Chief Examiner
Professor of Management Science and Operations
Professor of Management Science and Operations
Associate Professor of Management Science and Operations
Professor of Management Science and Operations; Deloitte Chair in Innovation and Entrepreneurship
Professor of Management Science and Operations; Chair, Management Science and Operations Faculty
Associate Professor of Management Science and Operations
Assistant Professor of Management Science and Operations
Discover the pioneering research that supports our teaching excellence.
Interested in joining our world-leading MSO faculty as a research leader and lecturer?
A key part of our Masters programmes curriculum.
View courses Show lessBusiness Analytics
Data and Time Series Analytics
Data Analytics for Management
Data Analytics for Managers
Data Management
Data Science for Business
Data Visualisation and Story Telling
Decision Analytics & Modelling
Decision Risk Analysis
Introduction to Python for Data Science
Machine Learning for Big Data
Managerial Statistics
Operations Management
Operations Management
Using Data-Science Responsibly
Value Chain Management
Optional courses providing a deep dive into specialist areas.
View electives Show lessBusiness Resilience
Data Science with R
Digital Deep Dive
This course provides an introduction to an industrial sector of worldwide importance, and one in which there are now many business challenges through market restructuring and the development of low carbon technologies.
In today's information age, managers increasingly rely on quantitative models to make financial decisions that have a profound impact on the performance of their organizations. Often business analysts produce the quantitative models that top management use to support their decision making, but top management must also understand the strengths and weaknesses of the models if they are to use them effectively to support their decisions. The objective of this course is to equip you with the frameworks, tools, and methodologies necessary to build and/or be an educated user of quantitative models for financial decision making. The course is suitable for students seeking a career in finance, but also for students with broader interests who wish to strengthen their general modelling skills, and it does not require any quantitative background other than what is covered in the MBA core courses.
With increased demand and pressure to reduce costs, healthcare delivery systems across the globe are under pressure to find ways to increase quality and widen access, while simultaneously reducing cost. The aim of the course is to explore the challenges these competing goals create and to throw light on how they can be best managed. In so doing the course seeks to identify opportunities in health care for managers, entrepreneurs and policy makers. This course draws substantially from the research and consulting expertise of the team of instructors teaching it.
This elective focusses on the business of sport and entertainment. The aim is to develop understanding and skills in the strategic, operational and marketing management of these two related and converging sectors. It is designed to foster strategic and operational thinking in a rapidly professionalizing area and one that is key to future economic growth.
This course covers the emerging field of business analytics (BA) or data mining and expands and develops the students' analytical tool kit in analyzing massive data sets. Using case studies and hands-on data sets, students will learn advanced data query techniques, data cleaning and organization, explore various machine learning techniques including supervised and unsupervised classification schemes, text classification, clustering techniques as well as predictive analytics. Students will gain hands-on experience with a variety of software tools, including Tableau and XLMiner.
To meet the challenges of the globalised and rapidly changing business environment, companies are increasingly adopting flat, flexible and matrix-oriented organisation structures in which work is structured around cross-functional business processes and projects. The success of such companies crucially depends on effective project management. The key dimensions of projects are people, time, costs, and resources. This course introduces methodologies and practical tools that facilitate and support the management of these dimensions, throughout the project design, planning and implementation phases.
The modern economy is characterized by reduced legal and technological obstacles to global trading. As a result, the success of modern enterprises is increasingly driven not only by their products, people and internal processes, but also by the performance of their supply chain as a whole. In this context, the goal of this course is twofold:
HKU Elective
Innovating Business Models, Products & Services is a fast-paced,hands-on, experiential and interdisciplinary class where students will identify and develop new business models, products and services, in a multi-tiered innovation tournament context.
This is a practical course developed to extend statistical capabilities and critical understanding in the analysis of time series data. The main emphasis will be upon analysing financial and commodity data, mostly high frequency. Although various advanced regression-based methods are reviewed, the course will not be mathematically demanding and students who were comfortable with the pre-programme, or first term, statistics course will be able to move on to this material without difficulty. Students should, however, have an interest in model-based analysis. The course material will be developed intuitively, rather than theoretically, through the exploration of many examples and practical workshops. The course will start with the fundamental basics of time series analysis and lead to a look at recent techniques for algorithmic forecasting and value-at-risk. Two of the later sessions will be led by Dr Peter Bolland, who was formerly head of electronic market making at Morgan Stanley.
The primary objective of this course is to enhance the participants’ ability to use analytics to develop insights in a wide range of business situations. We will work on five in-depth real-world case studies developed by the instructor. For each case, we will start with breaking down what seems to be a complex and ill-structured problem to simpler subproblems that are amenable to analysis. Through a mixture of lectures and workshops, we will use data analysis (visualization, regression) and modelling techniques (Monte-Carlo simulation, decision-tree analysis, optimization) to build progressively more sophisticated models that allow us to evaluate possible alternatives, make sensible recommendations, and serve as the basis for communicating findings and influencing decisions. After each session, participants will have the opportunity to further refine the models developed in class and prepare a presentation for the management of the company featured in the case study.
Emerging Topics in MSO I
Advanced Optimisation
MSO Seminar / Dynamic Programming
Statistical Research Methods I
Statistical Research Methods II
Supply and Inventory Management
Short programmes offering academic excellence, global focus and exceptional diversity of perspective.
View programmes Show less"Attending the Accelerated Development Programme is a unique opportunity for participants to learn not only from our world-class faculty but from their fellow participants. Consequently, the way the programme is designed encourages you to get to know as many people as possible and to form a life-long network of culturally diverse peers".
Become an intellectual leader with our PhD programme
Think at London Business School
Leaders are responsible for creating an environment people can succeed in.
By Randall S Peterson
Think at London Business School
Lynda Gratton examines technology’s impact on the traditional managerial role
By Lynda Gratton
Think at London Business School
The reasoning behind performance-based pay is to encourage executives to go above and beyond.
By Alex Edmans
Want to know more about MSO at London Business School? We’d love to hear from you.
Teodora Moneva
MSO Subject Area Manager