MSc Business Analytics
Providing you with in-demand skills for solving challenging business problems.
About The Course
We live in a world where analytical decision-making happens every second. Data is collected about everything in order to construct, operate and maintain systems. If you want a career in decision support, operational research, industrial engineering or management science, this is the ideal programme for you.
This course will train you in analytical decision-making. Not only do you learn the theory of business analytics but also how to apply it in practice. This involves generating relevant business insights using data-driven methodologies and tools. Our programme is one of the few to teach the entire Business Analytics life cycle, covering Descriptive, Predictive and Prescriptive analytics.
We have excellent partnerships with industry business analytics practitioners. We constantly update this programme to reflect the dynamically changing landscape of business analytics. We place a very high emphasis on creating graduates with skills that are valuable in the job market. For example, you will experience a real-life analytics project as part of your course.
12-month course, starts in October.
Designed for students interested in careers in operations research, business analysis, problem solving, data mining, strategic planning and supply chain management.
The MSc in Business Analytics consists of compulsory and optional modules, plus a project. The compulsory modules ensure that you have a firm grounding in important subjects. The wide range of optional modules allows you to specialise in subjects that particularly interest you.
During your first term from October to December, you will study the following core modules:
Operational Research and Prescriptive Analytics
This module provides an introduction to Business Analytics and Operational Research. It begins with a description of the origins of the subjects, an overview of their subsequent development, and a discussion on how to model real-life problems adequately. The remainder of the course gives an overview of some of the most widely used models and solution methods, including decision analysis, linear programming, inventory control, simulation and Markov chains.
Statistics and Descriptive Analytics
At the heart of many management problems lies data that need to be described, analysed and interpreted. The overall objective of this module is to develop the students’ abilities to describe, analyse and interpretdata soundly, making effective use of computer software. The skills learned on this course underpin manyof the other modules on the Management Science Department programmes. Although the moduleassumes little prior knowledge of statistics, those with prior knowledge should not expect to find it easy.
Data Sourcing, Handling and Programming
The overall objective of the module is to provide students with an introduction to core principles and techniques around data and processes within organizations, along with an introduction to the basic principles of programming with data, through the use of Python. The initial emphasis is on developing basic programming skills in Python, such as: Data Types; IF Statements, and FOR and WHILE Loop; Objects; Operators; Functions; Read from and Write to Files. Emphasis will then move to developing an understanding of Data within organizations, with a focus on: Data Types; Data Sources; Storage of Data (e.g. files, database, data warehouse); Enterprise Resource Planning (ERP) and Enterprise Systems; Business Processes; Relationships of Data to Business Processes; Data Flow Diagramming; Decision Tables.
Forecasting and Predictive Analytics
After introducing the topic of forecasting in business organisations, issues concerned with forecasting model building in regression and its extensions are presented, building on material covered earlier in the course(s). Extrapolative forecasting methods, in particular Exponential Smoothing are then considered, as well as Machine Learning / Artificial Intelligence methods, in particular Neural Networks. All methods are embedded in a case study in forecasting in organisations.
The second part of the course runs from January to May, and includes the moduile below plus three from the optional modules on the next tab.
Analytics in Practice
In this era of unprecedented data and computational power, analytics is proving to be the cornerstone of ever-growing areas of organisational decision making, be it for example for businesses to compete or for public sector organisations to innovate. There are several aspects in applying analytics to real business and decision-making scenarios and problems. These not only include computational and algorithmic methodologies, which encompass three main strands of analytics (descriptive, predictive and prescriptive) but also problem structuring methodologies like SSM. A key ability expected of an analyst or analytics practitioner is to have a good idea and understanding of how these aspects of analytic decision-making play together in any given context. Hence, the aim of this module is to enable students to develop analytic thinking at a holistic level to make informed choices when using or recommending analytics in a real-world context.
You will also choose three optional modules from those listed below.
Simulation and Stochastic Modelling
The aim of this module is to teach the skills required to apply simulation successfully to help improve the running of an organisation, whether in the public or private sectors, manufacturing or services.
Modern simulation packages are a valuable aid in building a simulation model and this module will employ a widely used and up-to-date discrete event simulation package. However, without the proper approach, the results of a simulation project can be incorrect or misleading. This module looks at each of the tasks required in a simulation project. It emphasises the practical application of simulation, with a good understanding of how a simulation model works being an essential part of this.
Optimisation and Heuristics
Optimisation, sometimes called mathematical programming, has applications in many fields, including operational research, computer science, statistics, finance, engineering and the physical sciences. Commercial optimisation software is now capable of solving many industrial-scale problems to proven optimality.
The module is designed to enable students to apply optimisation techniques to business problems. Building on the introduction to optimisation in the first term, students will be introduced to different problem formulations and algorithmic methods to guide decision making in business and other organisations.
Transportation and Logistics Analytics
The purpose of this module is to understand and use in somewhat simple contexts, some of the basic models from logistics.
Algebraic formulations will be used as vehicle for describing models and discussing their relationships. There will be a focus on modelling, the use of professional software, and the understanding of results. For problems where exact solutions are hard to achieve even for simple instances of the problem, heuristics will be discussed. The main topics which are covered are: facility location, network design, warehousing and inventory control, vehicle routing and scheduling, and environmental considerations in transportation and distribution operations.
Intelligent Data Analysis and Visualisation
The course provides an introduction to the fundamental methods and approaches from the interrelated areas of data mining, statistical/ machine learning, and intelligent data analysis. The course covers the entire data analysis process, starting from the formulation of a project objective, developing an understanding of the available data and other resources, up to the point of statistical modelling and performance assessment. The focus of the course is classification.
Operations and Supply Chain Excellence
Successfully managing its operations and its supply chain activities is central to any organisation’s ability to compete for revenues and resources.
The aim of this module is to introduce a series of innovations and capabilities in operations and supply chain management that have been associated with excellence and outstanding performance.
These include strategic procurement management, lean production principles, supply chain contract design and negotiation, supply chain financing and risk management, and managing business process flows.
The module will look at these subjects in both manufacturing and service contexts.
This module introduces you to the basic principles of marketing and places particular emphasis on the role of analytical modelling in supporting marketing decisions in organisations.
It is hoped that you will be in a position at the end of this course to fully appreciate how analytical models enable managers to make better marketing decisions instead of relying on their intuition or gut feel. We also provide a brief overview of some of the key topics on other modules that you will cover in more detail in the second term.
From May to September you will choose one of the modules below.
The aim of this module is to provide students' a valuable opportunity to research a real business problem for an organisation, delivering a viable and well documented solution to the client. For a successful project, students' will employ their knowledge of methods (qualitative/quantitative), problem scoping and the research literature to identify and implement a solution approach to the business problem. Throughout the project student will develop their knowledge and understanding of professional engagement both in their interactions with the client and in the reporting of their outputs and discourse on their research
The aim of this module is to provide students' a valuable opportunity to research an area of Business Analytics in-depth, linking this to business problems that arise in the real world. For a successful project, students' will employ their knowledge of analytical methods, problem scoping, modelling and the research literature to identify and implement a solution approach to the business problem or expand on their knowledge of the state of the are in the area researched. Throughout the project student will develop their knowledge and understanding of professional academic engagement both in their interactions with the supervisor and in the reporting of their outputs and discourse on their research.
Our programme-specific scholarships for 2020 entry are aimed at high-achieving students with a strong academic or personal profile. We'll automatically consider you for these scholarships when you apply and if you are shortlisted we'll be in touch with the next steps, so it's best to apply as soon as possible.
We also offer LUMS Alumni scholarships - visit our Apply For Masters page to find out more.
The Department of Management Science provides an extensive careers service and postgraduate students may expect to be eagerly sought after by employers. Major employers contact the Department each year to recruit. Many former students now hold senior positions in their organisation – as management scientists or as managers.
The Department has strong links with companies and organisations, many of which employ our alumni. Companies visit the department to make presentations and interview students as part of their selection process. In other instances, opportunities are advertised via the noticeboards and electronically on the student VLE. You are also asked to contact company recruitment offices directly.
Management Science, Operational Research, Logistics, Supply Chain and Market Analysis are seen by leading companies as the start of a fast track to promotion for high flyers with a numerate or scientific background. Project Management skills are also highly sought after by companies due to a need for improved project success rates and more global and complex project organisations. There is a continually growing market for the project profession which covers many roles from support to strategic leadership. Experience has shown that if you have a postgraduate qualification, you will not only obtain a better starting job but will also receive more rapid promotion.