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Providing you with in-demand skills for solving challenging business problems.
This programme is ideal for students wishing to work in business analytics, decision support, industrial engineering, operational research and management science. It will equip you with in-demand analytics skills and prepares you to solve challenging business problems. You will gain hands-on experience in applying theory to practice guided by world-leading academics and management scientists with expertise in areas including Forecasting, Optimization, Simulation and Operational Research.
The aim of the MSc Business Analytics programme is to provide a solid basis in a variety of techniques including Forecasting, Optimization, Simulation and Operational Research which help in intelligent data-driven decision making when faced with complex business problems. This is achieved with a fine balance between theory and application of these techniques. The programme comes with great flexibility where you can choose from a range of modules to align with your own interests along with compulsory core modules. The structure of the programme is designed with special emphasis on the growing need for analytical skills required to deal with business problems in the big-data age.
We help you to improve your professional skills as well as your analytical abilities. In a significant real-life project, you will have the opportunity to develop professional skills by working for 16 weeks as a consultant to one of our client companies. The employment record of the programme is excellent, with our graduates in demand from business and the public sector for their analytical skills.
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.
Ranked 4th in the UK by the QS Business School Rankings 2018.
Average class size
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 four core modules:
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.
The main concern of this module is the process of conducting analytical studies for clients. It runs alongside the technical and applications courses of your MSc and should be regarded as the core 'professional' element. There are lectures, case exercises and team work, and we particularly stress the need to develop sensible approaches to problem structuring and model formulation. Students will develop an understanding of the ways in which modern management science methods can be effective in supporting decision making and analysis in contemporary organisations. In addition, you will gain an appreciation of theories of decision making and choice and some understanding of the ways in which data produced by accounting systems can be used in analytical consultancy practice.
Students will be introduced to the latest version of Microsoft spreadsheet: Excel 2016.
The module will cover the basics of ‘dynamic’ model building, including skills such as data visualization, handling, filtering and analysis, using a variety of key functions and charting tools. In addition there are advanced techniques such as optimisation, simulation, and the use of Visual Basic for Applications (VBA) to automate models and construct decision support models. The course will also introduce the basics of simulation programming, using VBA. The course will make extensive use of case-studies and workshop-orientated learning tasks.
At the heart of many management problems lies data that need to be described, analysed and interpreted. An operational researcher/management scientist needs to be able to do this soundly and efficiently. The overall objective of this module is to develop the ability to describe, analyse and interpret data soundly, making effective use of computer software. This module assumes some prior knowledge of statistics (although we know that some of you have plenty!) and some familiarity with simple algebra and calculus is assumed. This module emphasises the practical application of statistical methods, and makes extensive use of SPSS.
The second part of the course runs from January to May, and includes a further six modules. You will need to choose at least three modules from the first four listed below, as well as up to two modules from the optional choices listed on the next tab.
This module will develop an understanding of the strategic role that sourcing decisions can play in supply chain management in order to gain sustainable competitive advantage in a global environment. It will look at alternative ways in which the upstream supply chain can be successfully configured and coordinated in different contexts, including the strategic role of IT in supporting this.
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.
This module will consider a number of Operational Research (OR) techniques which have in the main been devised to tackle problems in which it is important to model the effects of stochastic influences.
The aim will be to provide sufficient information about the techniques to give an understanding of their potential and limitations, and of the steps likely to be involved in using them. The techniques will be selected from: Markov processes; stochastic simulation; queuing models; risk analysis and replacement, inspection and maintenance models. The first two techniques are generally applicable in many problem areas, whereas the latter three refer to models specifically developed for particular sorts of problems.
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.
You will also choose two optional modules from those listed below.
Python is a simple, yet very powerful, high level computer programming language that becomes immensely popular in our days. It is widely used in many scientific areas for data exploration and at the same time it is the preferred programming language among a wide range of modern organisations.
This course is an introduction to computer programming using Python for students without any prior programming experience. It introduces the basic principles of computer programming but is doing it with an emphasis on examples from the areas of business analytics and finance.
Every managerial decision concerned with future actions is based upon a prediction of some aspects of the future. Therefore Forecasting plays an important role in enhancing managerial decision making.
After introducing the topic of forecasting in organisations, time series patterns and simple forecasting methods (naïve and moving averages) are explored. Then, the extrapolative forecasting methods of exponential smoothing and ARIMA models are considered. A detailed treatment of causal modelling follows, with a full evaluation of the estimated models. Forecasting applications in operations and marketing are then discussed. The module ends with an examination of judgmental forecasting and how forecasting can best be improved in an organisational context. Assessment is through a report aimed at extending and evaluating student learning in causal modelling and time series analysis.
This module develops modelling skills on synthetic and empirical data by showing simple statistical methods and introducing novel methods from artificial intelligence and machine learning.
The module will cover a wide range of data mining methods, including simple algorithms such as decision trees all the way to state of the art algorithms of artificial neural networks, support vector regression, k-nearest neighbour methods etc. We will consider both Data Mining methods for descriptive modelling, exploration & data reduction that aim to simplify and add insights to large, complex data sets, and Data Mining methods for predictive modelling that aim to classify and cluster individuals into distinct, disjoint segments with different patterns of behaviour.
The module will also include a series of workshops in which you will learn how to use the SAS Enterprise Miner software for data mining (a software skill much sought after in the job market) and how to use it on real datasets in a real world scenario.
SAS is one of the leading providers of business intelligence and predictive analytics software.
There is increasing demand in the graduate labour market for analysts with SAS programming skills.
This module is primarily a 'support' course on the various postgraduate programmes and courses. This module will provide an introduction to SAS programming whilst giving the participants experience of using an advanced data base and a versatile statistical programming language. SAS, through our relationship with them, are supporting this course.
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.
Marketing research enables an organisation to better understand the market environment.
The main objective of conducting marketing research is to enable decision makers to make better decisions than if the latter were based only on intuition and guesses. At the heart of marketing research is information which facilitates the decision making process.
In this module we focus on the collection and use of information in marketing research but pay particular attention to the context of the problem. You will also have the opportunity to learn some transferable skills that relate to gathering and using information for business intelligence and decision making.
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 examines supply networks as extended operations that deliver products and services, and draws on concepts from operations management and from other disciplines. The emphasis is very much upon inter-organisational networks, rather than those between organisations and consumers.The central theme of the module is that e-business practices and technologies and supply network concepts and practices are inextricably linked: each facilitates the other.The module develops your ability to understand and critically evaluate the key principles of supply chain management, and helps you to appreciate and assess the important interrelationship between ICT and supply chain management practices and strategies. You will also develop skills in identifying and proposing solutions to specific network problems.
This module builds on the concepts learnt in this first term and covers topics such as visualising and understanding multidimensional problems; markets and competitors, market share modelling, marketing forecasting, retailing, promotional modelling and game theory for marketing.
This module will help students to apply the concepts of marketing modelling in its application to complex consumer and business markets. Students will also appreciate how such type of modelling work can help managers make better technical marketing-related decisions such as store location or the amount and type of promotional activity to promote brands.
This module enables you to develop an appreciation of the dynamics of the international marketplace and the complex and challenging forces shaping this environment. It uses the principles and frameworks underpinning international marketing to assess how key marketing and consumer behaviour theories, models and concepts apply in an increasingly globalised and internationally competitive marketplace.
From May to September you will work on a 60-credit project, usually based in an organisation, on which you write a report for the client and an academic dissertation. You will submit it at the start of September, at the end of your Masters programme.
At the end of the taught modules on all three Masters programmes in Management Science you will complete a three-four month project, which will be organisation-based (with organisations from both public and private sectors), organisation-driven or research-based. Eligibility for organisation-based projects will be competitive and based on merit and marks achieved.
These projects are an essential part of the learning on each of the MSc programmes and give you a chance to use the analytical methods and professional skills developed on the taught modules. Completion of a project will be an asset on your CV and some students go on to work for the organisation that sponsors their project. Recent examples of projects include simulation, product launch, optimisation and risk analysis at Jaguar Land Rover, Lego and Barclaycard.
Our programme-specific scholarship for 2018 entry include the Academic Excellence, UK-EU and International scholarships 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 other scholarships - visit our Apply for Masters page to find out more.
The Robinson Scholarship is an award of £5,000 available only to applicants for the MSc Business Analytics. The award is for an outstanding applicant from a developing country, to contribute toward the cost of tuition fees. Applicants need to have an offer for the programme in order to be eligible to apply. Those wishing to apply need to complete the application form by 1st May 2018 and return it to the Programme Director, Dr Trivikram Dokka .
The Department of Management Science provides an extensive careers service and postgraduate students may expect to be eagerly sought after by employers. More than 40 major employers normally 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. 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.
Organisations in which students have been offered jobs in the last three years or so include:
Accenture, Calanais Energy, Cap Gemini, Hartley McMaster, KMPG, Indicia, OEE Consulting Ltd, PA Consulting, QinetiQ.
Santander, Barclaycard, Halifax plc, HSBC, Lloyds TSB, NatWest Consultancy, PricewaterhouseCoopers, Royal Bank of Scotland, Woolwich.
AEA Technology - Rail, British Airways, BT, Digital, London Underground, National Air Traffic Services, T-Mobile, Royal Mail, Post Office Consulting.
Allied Domecq plc, Great Universal Stores, Littlewoods, J Sainsbury, Tesco, Unipart.
Corus, Coats Viyella, GlaxoSmithKline, Nestle, Procter & Gamble, Scottish Courage.
CIS Consultancy - Metropolitan Police, Ministry of Defence - DSTL, Home Office, North Essex Health Consortium, Oxfam.
MSc Operational Research and Management Science (Business Analytics), 2017
MSc Operational Research and Management Science (Business Analytics), 2013
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