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MRes Management Science

This twelve-month programme provides an opportunity for those with some familiarity with the theory and techniques of Management Science to extend their knowledge of methodology and applications and carry out an extended piece of desk research.

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About The Course

Businesses, organisations and governments are now turning to quantitative and qualitative analytics to solve complex problems. Research is being used to inform or justify action like never before. This programme is designed for those with some familiarity with management science theory and techniques. It’s ideal for those wishing to pursue a PhD or a specialist career in government, industry or consulting.

Our department has a broad spectrum of interests with staff incorporating insights from cutting-edge projects into their teaching. We take the lead in the Centre for Marketing Analytics and Forecasting, the Centre for Productivity and Efficiency and the Centre for Transport and Logistics. This means you can benefit from these three research centres’ extensive and diverse research experience.

You will join a group of high-potential scholars from across the world. Together you will learn how to use advanced technical skills to solve real problems and find new ways to move forward. We combine taught and research elements to develop a focused approach to research. You will study research methodologies, techniques and design approaches in organisational settings.

Key Facts

12-month course, starts in October

Designed for graduates looking to pursue a PhD or a specialist career in government, industry or consulting.

Course Content

The MRes programme entails taking the core modules listed on the next tab, as well as appropriate lectures and assessments drawn from the taught postgraduate programmes in the Department of Management Science or the wider School.

If you are intending to specialise in Operational Research, the modules will be drawn from those offered in the Department's postgraduate programmes. If you are considering Operations Management, Systems and Information Management, the MRes will include appropriate modules from other programmes within the Management School. These will be chosen by agreement between you and the programme director, based upon your intended field of research and gaps in your current knowledge.

Coursework takes up to 40% of the programme. The remainder of the year is spent undertaking a literature review and a supervised research project and dissertation.

The Core modules are listed below.

  • Statistics and Descriptive Analytics

    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.

  • 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.

  • 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.

  • 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.

  • 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.

The Core modules are listed below.

  • 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.

  • 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.

  • 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.

  • Marketing Analytics

    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.

  • Marketing Research Methods

    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.

  • 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.

  • 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.

  • Dissertation (Industry)

    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

  • Dissertation (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.

Assessment Methods

The assessment procedures for the taught components are the same as for the taught MSc programmes. A dissertation must be submitted by mid-September.

Scholarships

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.

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Careers

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.