Business Analytics (Study Abroad) BSc Hons - 2022 Entry

Course Structure

Lancaster University offers a range of programmes, some of which follow a structured study programme, and others which offer the chance for you to devise a more flexible programme to complement your main specialism. We divide academic study into two sections - Part 1 (Year 1) and Part 2 (Year 2, 3 and sometimes 4). For most programmes Part 1 requires you to study 120 credits spread over at least three modules which, depending upon your programme, will be drawn from one, two or three different academic subjects. A higher degree of specialisation then develops in subsequent years. For more information about our teaching methods at Lancaster please visit our Teaching and Learning section.

The following courses do not offer modules outside of the subject area due to the structured nature of the programmes: Architecture, Law, Physics, Engineering, Medicine, Sports and Exercise Science, Biochemistry, Biology, Biomedicine and Biomedical Science.

Information contained on the website with respect to modules is correct at the time of publication, and the University will make every reasonable effort to offer modules as advertised. In some cases changes may be necessary and may result in some combinations being unavailable, for example as a result of student feedback, timetabling, Professional Statutory and Regulatory Bodies' (PSRB) requirements, staff changes and new research.

Year  1

Core

• Introduction to Business Intelligence and Analytics

  The module will cover the introductory topics of business intelligence, business analytics and business data science. You will learn basic analytics concepts, principles and techniques and will see how the data collection, description, visualisation and analysis can help businesses, governments and other organisations make more informed decisions.

  The module will also cover topics on discovering, measuring and visualising relationships in data, and basics of forecasting and data mining. Examples of real cases studies will illustrate the practical potential, and special emphasis will be given on discussing what the main pitfalls in using different analytical techniques are, such as “lying with descriptive statistics”, misleading visualisation, data overfitting, or why “forecasts are always wrong”. The module will rely on spreadsheet software to support the computing and visualisation side and will teach you useful approaches that will prove in valuable for your future studies and employment.

  Finally, you will learn how to write reports for the management based on the produced results. It is important to understand basics of analytics even if you do not intend to get an analytics job, because it is critical to business strategy, and so there is a great professional advantage in being able to interact competently with analytics teams. This module aims to refute the belief that organisations and individuals may be able to successfully live without the use of data and analytics.

• Introduction to Operations Management

  Operations management is a core discipline for all kinds of organisation, from private-sector manufacturers through to public-sector service providers. This module introduces the core topics of operations management, including operations design, capacity management, supply chain management, inventory analysis, demand forecasting, quality management and risk analysis. Most of these topics have both qualitative and quantitative elements that need to be understood and practised in combination.

• Tools and Techniques for Business Analytics

  The techniques of Management Science, based on mathematics, statistics, analytics and computing, can be extremely powerful in helping to solve organisational problems and are widely used in practice. This module explains the business situations in which such techniques apply and shows how to use the techniques and interpret the results to make better business decisions. Techniques are introduced through a mix of lectures, computer workshops and tutorials at which tutors can give extra help. The techniques introduced include decision analysis, simulation, queueing analysis, computer algorithms and linear programming. To support development, students are introduced to probability and probability distributions and gain familiarity with useful computer tools such as Excel and Python programming.

  In this module, students work on challenging case studies based on real problems. These provide the opportunity to apply the concepts and techniques of problem solving, making recommendations and reporting results. There is a stress on practical examples of using the techniques. The module lays a foundation for learning more advanced techniques later in the degree, and emphasises not only how to apply techniques, but also when (and when not) to apply them.

Year  2

Core

• Optimisation

  This module describes a variety of optimisation algorithms and how business problems can be modelled using these techniques.

  Optimisation is one of the primary techniques associated with management science/operational research. Sometimes called Mathematical Programming, optimisation is concerned with finding the ‘best’ solution to a problem that has a large number of possible solutions. It has a huge array of applications in many fields, and optimisation models are now used routinely in industry (especially in manufacturing, energy production and transport), in the public sector (especially defence and healthcare) and in the services (especially finance). Therefore, skills in formulating and solving optimisation problems are valuable for a variety of careers. The course is designed to enable students to apply optimisation techniques to business problems. Students should take it if they are interested in modelling real situations via mathematics. However, the goal is not mathematics for its own sake. We also want the students to have an understanding of the types of situations in which the various techniques can (or cannot) be applied.

  Four main topics are covered:

  • Linear programming

  • Specially-structured linear programs

  • Integer and mixed-integer programming

  • Heuristics for large-scale problems

• Professional Skills

  The overall objective of the Consultancy Skills module is to introduce and practise in a progressive and reflective way some of the key consultancy skills required when working for a client, using a consultancy competencies framework. These skills include teamwork, coping with clients in project situations and the use of oral and written communication skills to help persuade management to accept your findings.

  Via a group simulated consultancy study, it covers some of the key communication and technical skills needed in project work, such as teamwork, interviewing for information, oral presentations and writing a management report. Students are encouraged to reflect upon their own strengths and weaknesses, and those of their team, by means of a reflective log, updated as the module progresses.

• Project Management Tools & Techniques

  Designed as an introduction to the theory and practice of managing business projects, this module introduces project management methods in a way which links to the life cycle of a typical project – from the early project identification and definition stages, through project execution and control, to issues of implementation and change. The coverage of the early stages of the project cycle uses methods emerging from the systems movement and stresses the strategic relevance of project management. The management of the project is covered by introducing techniques for planning, scheduling and controlling projects. Attention is also given to the people management aspects of this process, including leadership, team-working and motivation.

• Spreadsheet Modelling for Management

  Many organisational recruiters have identified a number of skills and knowledge they want to see from a prospective employee. Top in the priorities are spreadsheet modelling, problem structuring, statistics, and project management.

  Students will be introduced to Microsoft Excel 2019 and the basics of dynamic model building, including skills such as data handling, filtering and analysis, using functions, charting, plus 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 make extensive use of case-studies and workshop-orientated learning tasks.

Optional

• Business Modelling and Simulation

  This module covers the skills needed to improve business process by modelling and simulation.

  Computer simulation methods are among the most commonly used approaches within operational research and management science. This module teaches you the skills required to apply simulation successfully to help improve the running of a business, and it shows how companies can find good solutions by predicting the effects of changes before implementing them.

  Modern simulation packages are a valuable aid in building a simulation model, and this module uses the Witness simulation package, which is widely used commercially. However, without the proper approach, the results of a simulation project can be incorrect or misleading. This module looks at each task 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.

• IT in Organisations: Introduction to ERPs

  Enterprise resource planning systems (ERPs) and integration solutions are essential to every modern enterprise, and this module gives you hands-on experience of SAP, a widely used enterprise technology. The module develops your understanding of how information technologies can help companies to achieve their strategic objectives, and introduces you to techniques and tools that can be used to evaluate the performance of business processes, diagnosing where problems lie and how processes can be improved.

  After introductory sessions which look at the pervasive use of IT by business and at quantitative and qualitative business process analysis, you then work in small teams to compete in running a virtual dairy company, using SAP GUI as your ERP technology.

• Managing Business Information Systems

  This module provides an introduction to the use and impact of information, communication and integrated technology systems on business and organisations. It focusses not on technical specifications, but rather on managerial and business implications of using these systems.

  The following issues will be addressed:

  • Data, Information and Decision-making
  • Business Uses and Benefits of IS
  • IT Selection
  • Obtaining Information Systems
  • Strategy and Information Systems

  The course provides the business foundation for other more specialised or technical topics in Information Systems.

• Supply Chain Management

  This module examines the principles and practices of supply chain management, building on operations management concepts. It examines supply chain and logistics management applications in various sectors, such as retailing, pharmaceuticals, information technology, and even higher education.

  Most of the time will be spent considering inter-organisational relationships from various perspectives, but it will also be necessary to understand how they relate to matters within the organisation, including functional areas such as logistics and procurement. As well as covering core principles and practices, the module also considers emerging supply chain themes such as service supply chains and sustainability.

Year  3

Core

• Management School UG Study Abroad Year

  This year of your degree will be spent studying abroad at one of our partner universities. We have exchange agreements with prestigious universities all over the world and many of our undergraduate degree programmes include a year spent studying at a top international university. Progression to the study abroad year will be dependent upon performance in the first year of the degree programme. Some students may also have to complete a Study Abroad Maths examination. You can find out more about our study abroad programmes on our LUMS Study Abroad web pages.

Year  4

Core

• Business Analytics Project

  This module is the final year capstone of the Business Analytics degree scheme, and aims to integrate the core principles and techniques in an integrative manner and in a realistic context, that have been taught during the previous years.

  Students will learn to apply the project lifecycle framework, the associated consulting and business analytics tools and techniques, along with people and presentation skils, to define and manage a real-world project, being responsible for developing a comprehensive project management plan, to justify and document all decisions related to its development and implementation, to deliver the anlaytical aspects of the project, to discuss lessons learned, and to present the outcome of their work to a professional audience.

  The module aims to ensure that students graduating from the BA degree are able to use integrative, innovative and analytical approaches to solve real-world consulting probems.

• Project Management: Negotiation and Decision Support

  Central to this module is the Crossbay Contracting Game, a management game designed by the module convenor and his colleagues at HCS Ltd.

  Three (health service) organisations are involved in a contract negotiation, and you will be part of the management team of one of these organisations. The contract concerns funding requirements for core activities over the coming financial year.

  The main aim is to reach an agreement that is satisfactory to all three parties – but you must of course ensure that your own organisation is likely to come out of it well. Much of your time will be spent analysing the emerging situation and negotiating with the other parties.

  Alongside this 'management' task there is also a modelling task. Teams are provided with a decision support system they can use to analyse the emerging situation and help them decide which strategies are cost-effective for their organisation.

Optional

• Advanced Spreadsheet Modelling

  Many organisational recruiters have identified particular skills and knowledge they want to see from a prospective employee. Top in the priorities are spreadsheet modelling, problem structuring, statistics, and project management. This highly practical module equips you with an advanced set of spreadsheet modelling skills, including advanced functions and programming using Visual Basic for Applications (VBA) that can be used to produce a wide range of effective decision-support models.

  You will learn general concepts about spreadsheet modelling using VBA and a wide range of modelling skills which are highly relevant to management. These include structured programming, program documentation, program verification, user interface design, and general investigative modelling – including applications involving optimisation, forecasting and simulation.

• Business Forecasting

  This module introduces you to various current techniques for forecasting future customer demand, including a range of predictive models that develop your knowledge of the best ways of forecasting in problem situations.

  The aim is to ensure that you have the skills needed to develop a validated quantitative set of forecasts using both extrapolative and causal forecasting methods, and that you can apply a simple forecasting method to support demand and revenue management.

  You will also learn to identify and exploit opportunities for revenue optimisation in different business contexts. You review the main methodologies used in each of these areas, discuss legal issues associated with different pricing strategies, and survey current practices in different industries. Most of the topics covered are either directly or indirectly related to pricing issues faced by firms operating in environments where they enjoy some degree of market power.

• Data Mining for Direct Marketing and Finance

  At the heart of many real-world industrial and scientific problems are increasingly large data sets that need to be analysed efficiently in order to gain novel and useful insights. The field of as data mining (also known as intelligent data analysis) brings together real large-scale datasets and algorithms from statistics, machine learning and computational intelligence that can work efficiently with real-world datasets.

  he 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. The course content covers:

  -Exploratory data analysis including visualisation and simple feature selection methods

  -Classification methods like: Logistic Regression, Decision trees (Random forests), k-Nearest Neighbours, and Naive Bayes

  -Performance assessment and model selection

  The course uses the R programming language and more specifically the RStudio integrated programming environment.

• Developing Business Information Systems

  In this module we look at how to study business operations, analyse the situation and develop appropriate information systems designs. The same techniques can be of value whether you develop them further and become an information systems professional or use them in general management or consultancy. There is an emphasis on practical application and extensive use of class exercises.

  The techniques taught in this module are widely employed by analysts in the fields of information systems and general business consultancy, and the ability to analyse information requirements and design efficient and effective information systems to meet those requirements is increasingly recognised and valued by employers as an important management skill.