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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 lessCovid, Brexit, financial crises, cyber-attacks, labour strikes, key employees turnover… businesses are now confronted to a vast range of possible disruptions often threatening not just their profits but also their survival. This course offers in-depth exposure to the latest knowledge, tools and frameworks relevant to business resilience, that is the capability of a business to survive and minimise costs incurred when facing disruptions. Its structure reflects the three different levels driving business resilience, namely: Strategic resilience: capability of designing or changing the business model (products offered, markets targeted) in response to actual or possible disruptions (instructor Julian Birkinshaw); Operational resilience: capability of maintaining existing core business activities when facing disruptions (Jérémie Gallien and Alex Yang); Personal resilience: capability of coping with stress-provoking events while reducing adverse experience and stress symptoms (Dan Cable).
Data science enables the extraction of useful knowledge and business value from complex data collections. This will be a coding-focused course in R, with equivalent code in Python. The main goal is not to teach the technical aspects of algorithms but to focus on the application of useful tools and the issues that arise using real-world examples. These tools should be useful for students who want to build careers in data-intensive industries. On completing the elective, participants will master data manipulation and visualization and explore a spectrum of machine learning methodologies. In addition, we will learn how to scrape the web to harvest data, how to connect to and work with databases (SQL, Apache Arrow) with massive (1.7 billion rows) data sets, and how to work with geospatial data to create maps and perform GIS operations.
The business world is burgeoning with novel digital technologies, from Artificial Intelligence to Blockchain and Web 3. It is imperative for business leaders to keep pace with this constantly evolving digital technologies landscape, though the task is undeniably formidable. With a combination of lectures, case discussions, workshops, and guest speeches, this course aims to provide you a deep dive into the digital space. Upon completing this course, it will help you answer the following questions. How do these most discussed digital technologies work? What are the basic elements and value-generating mechanisms of these technologies? How can these technologies help to streamline my business processes and transform my value chains? How could I adopt and manage a technology for my organization and industry to harness its full potential?
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 analytics to make financial decisions that have a profound impact on the performance of their organizations. Often business analysts produce the analytics that top management use to support their decision making, but top management must also understand the strengths and weaknesses of analytics 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 analytics 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 analytic 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.
In this course students delve deep into the world of data analytics without writing a single line of code. Through compelling case studies and real-world datasets, participants will master advanced visualization techniques and explore a spectrum of machine learning methodologies, from supervised and unsupervised learning to text classification and predictive analytics. With hands-on sessions using powerful tools like Tableau and Alteryx, students will emerge with a robust analytical toolkit, ready to tackle large datasets with confidence.
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 characterised 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: Present the best practices and most relevant theory for designing and managing supply chains; Provide a laboratory that is as realistic as possible for students to practice managing supply-chains and obtain insightful feedback on their decisions. Using a combination of case studies, simulations, practitioner guest lectures and readings, the specific topics covered include: physical infrastructure (logistics and warehousing); product flows (forecasting and planning); supply chain design (strategic sourcing and contracting); supply chain risks (resilience to disruptions) and sustainability.
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 II
MSO Seminar 1 / Queuing Theory
MSO PhD seminar / Revenue Management
MSO seminar / Modeling and Analysis
Statistical Research Methods I
Statistical Research Methods II
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
Nicos Savva’s work aims to root out some of hospitals’ harmful profit incentives
By Cintra Scott
Think at London Business School
George Chen explains how a new procurement model has the potential to generate significant cost savings for both buyer and supplier
By Mel Bradman
Think at London Business School
How Jean Pauphilet and Kamalini Ramdas used probability theory to develop a method that could slash the cost of testing
By Nick Mickshik
Want to know more about MSO at London Business School? We’d love to hear from you.
Zainab Mehr
MSO Subject Area Manager