Programme Specification 2015/16 N/A

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1 Programme Specification 20/16 1. Awarding Body University of Surrey 2. Teaching Institution (if different) 3. Final Award MSc 4. Programme title/route/pathway Business Analytics 5. Subsidiary award(s) and title(s) PG Dip, PG Cert 6. FHEQ Level FHEQ Levels 6 & 7 7. Credits and ECTS credits 180 UK credits, 90 ECTS credits 8. Name of Professional, Statutory or Regulatory Body (PSRB) 9. Date of last accreditation (if applicable) 10. Mode of study Full-time 11. Language of study English 12. UCAS Code 13. QAA Subject Benchmark Statement (if applicable) 14. Other internal and / or external reference points. Faculty / Department Faculty of Arts and Social Sciences, Surrey Business School 16. Programme Director Dr Wolfgang Garn 17. Date of Production / Revision of the June 2014 specification 18. Educational aims of the Programme The programme s aim is to provide a high quality education that is both intellectually rigorous and at the forefront of management science research, relevant for problem solving and decision making by managers. It will respond to the emergent needs of corporations and academia for professionals who are able to work with analytical tools to generate value from available Information depots and take advantage of the vast amounts of data now provided by the modern ICT and ERP systems, which underlie the operations of modern corporations. The program will implant understanding of the theoretical base around knowledge management and knowledge work, practical skills and experience in using analytical software tools. It will allow future professional managers and consultants to cope with an increasingly complex and global operational environment of the modern corporation. Completion of the programme will provide a sound foundation for those considering continuing their academic development towards a PhD degree in the management disciplines. The programme is structured in a way that would provide students with a choice between a more quantitative intensive track of modules or a qualitative analytic (business development track) which would reflect students personal strengths and preferences and match future career aspirations. The compulsory modules provide a sound foundation which builds an analytical skillset using relevant statistical and management theories, and supports the development of practical hands-on experience applying the theoretical aspects using real-world data to address corporate challenges and find solutions to actual problems. The readings in the module will build a sound basis which would allow students to access and understand the academic literature and undertake empirical investigations in the areas of decision modelling and business development. 19. Programme learning outcomes the programme provides opportunities for students to develop and demonstrate knowledge and understanding, skills, qualities and other attributes in the following areas:

2 Knowledge and Understanding Teaching and learning strategies A systematic, in-depth understanding of the development; issues and influences relevant to discipline of Management Decision Making, Management Science, and Data Science. Deep and thorough understanding of quantitative analytical methodologies and handson experience with decision-making software and data management tools. Knowledge about issues, application and analysis of Big Data An understanding of the academic research process. Optional modules and Choices The module structure of the programme allows students to choose optional modules in the second semester. The two options available to students range between a more economical (econometrics and forecasting) oriented set of modules, or a focus on ICT driven analytics (Knowledge Analytics and Managing Decision Implementation). Teaching and learning strategies and methods The teaching and learning strategy aims in the most effective and efficient ways to provide a framework of knowledge within which students can take responsibility for their own learning, to introduce students to the contemporary issues, latest thinking and research, to provide opportunities for students to consider and evaluate the issues and to explore them further with their peers and teaching staff. To achieve these aims, the teaching and learning will include: Large group sessions that are designed to provide overall framework of the existing knowledge and sufficient information for students to follow up details independently; Large group sessions that will introduce students to new issues, controversial topics, recent research etc. Small group sessions that will provide opportunity for students to discuss and demonstrate their learning with their peers and lecturers in details Hands on work with the latest Analytics software (for Quantitative Analysis or Knowledge Management Practices) will provide the practical experience necessary to work in a Big Data environment

3 Individual supervision, particularly in the applied dissertation, in which students will be able to develop, discuss and refine business models and problem solutions to data intensive problems with the help of their supervisor. Assessment As a guide it is expected that each module will have a minimum of two different types of assessments, and wherever possible the demonstrated ability to use analytical tools will be assessed on par with demonstrated understanding of concepts and theories being taught by each module. The weighting between assessments is based on the intended learning outcomes and justified in the module description documents. The implication is that a sensible balance be achieved between theoretical understanding and the ability to apply the knowledge to real-world problems, across the modules in the programme. Examination (open or close book, short answer or multiple choices) and assignment (including essays, case studies, practical exercises, problem solving etc.) Formative and summative assignment (including tutorial discussion, practising past examination questions during the class and feeding back within their peers and lecturers, additional online discussion questions via SurreyLearn) Individual and group assessment Individually supervised dissertation. Skills and other attributes - Intellectual / cognitive skills Teaching and learning strategies Demonstrate deep learning, understanding of the material and ability to apply the knowledge and demonstrate skills in problem solving in the topic space of the modules studied Carry out assessments of data in a repository, select the appropriate analysis tools, design and execute an analytical methodology (not required for PG Certificate), apply adequate visualization methodologies to present the results and interpret the findings and finally to communicate the results effectively to a select audience The strategy for each individual module is designed to contain a mix of teaching and learning methods to provide a rich and varied learning environment. Sessions may take the form of traditional lectures, seminars, tutorials, workshops or they may be delivered through paper or electronic and online resource.

4 Assessment Skills and other attributes - Professional practical skills Teaching and learning strategies Demonstrate the ability to independently evaluate critical approaches and techniques relevant to Business Analytics; Know and apply a range of techniques and tools to analyse data related to business operations; Capability of selecting the right methodology and software to solve management and operational business issues; Relate existing knowledge structures and methodologies to analytical business challenges; Assessment Key / transferable skills An ability of demonstrating competence in a range of skills that are relevant to the needs of future professionals concerned with Business Analytics; critical thinking, analysis and synthesis (not required for PG Certificate); using computer software for extracting information out of structured, unstructured and big data; reasoning; problem solving; independent research; (not required for PG Certificate); presentation; report writing. Skills and other attributes - Key / transferable skills Teaching and Learning strategies & Assessment An ability to conduct research and produce a high quality dissertation- this includes the ability to critical literature review, to select, define and focus upon an issue at an appropriate level; to develop and apply relevant and sound methodology; to apply the methodology to analyse the issue; to develop logical conclusions and recommendations; to be aware of the limitations of the research An ability to identify modifications to existing knowledge structures and theoretical frameworks and therefore to prose new areas for investigation, new problems, new or alternative applications or methodological applications 20. Programme structure including the route / pathway / field requirements, levels modules, credits, awards and further information on the mode of study. All students are initially registered for MSc in Business Analytics

5 The (programme) is studied over one academic year and is fulltime. The Programme is divided into modules. All taught modules are worth credits, which is indicative of 0 hours of learning, comprised of student contact, private study and assessment. In order to achieve the (MSc) students must complete 180 credits. Data Analytics is the basis for Supply Chain Analytics, because it extracts essential information from the data for subsequent analytical analysis of supply chains. Preliminary Quantitative Methods is fundamental to Econometrics I and supports Data Analytics and Principles of Accounting. This module takes place in week one only. Data Analytics has strong synergies with Econometrics I due to related techniques. Supply Chain Analytics will fall back on some of the introduced quantitative methods and concepts from Econometrics I. The major difference between Supply Chain and Logistics Management and Supply Chain Analytics is that the former introduces and covers the general principles, as well as strategic approaches; whilst the later concentrates on a specific set of analytical methods. Due to the importance of finance to businesses the module Principles of Accounting links to these two modules naturally. In the second semester students are encouraged to pick one of the two option blocks, which are Management Decision Making and Analytical Economics. The modules in the Management Decision Making option investigate in depth decision concepts. These concepts were introduced in the Data Analytics and Supply Chain Analytics modules from different perspectives. Additionally this block of options gives special attention to the Big Data concepts. The Analytical Economics option deepens and supplements the Data Analytics and Supply Chain Analytics modules using a primarily economic view. Programme adjustments (if applicable) Programme pathways and variants The programme is offered in full-time mode and if demand in following years as part-time mode.. Credit Level 7 Potential Awards: Master of Science Postgraduate Diploma Postgraduate Certificate Award Requirements: Master of Science 120 Taught Credits + 60 credits from Dissertation Postgraduate Diploma 120 Taught Credits Postgraduate Certificate 60 Taught Credits In the case of joint honours (equally weighted subjects) or a major/minor combination programme, please provide a rationale for the particular subject combination and details on how the combination will operate. Who is the lead faculty, department or school? FHEQ Level 7: Potential awards MSc, PGDip, PGCert Module code Module title Core /compulsory /optional Credit volume Semester (1 / 2) Award requirements MANM301 MANM304 Data Analytics Supply Chain Analytics Compulsory Compulsory 1 2 On completion of this level students will have achieved 180 credits at FHEQ level 7 and will

6 ECOM042 MANM198 Econometrics I Principles of Accounting Compulsory Optional 1 1 be awarded an MSc (principal award) MANM097 Foundations of Finance: Optional 1 Subsidiary award MANM250 MANM302 Finance and Investments Supply Chain and Logistics Management Compulsory Optional 1 2 PG Cert 60 credits at FHEQ level 7must be achieved before a student may exit this programme with a PG Cert MANM303 MANM317 Information for Decision Making Managing Decisions Implementation Introduction to Marketing Analytics Optional 2 Optional 2 ECOM043 Econometrics II Optional 2 MANM101 Business Process Optional 2 Management MANM282 Investment Analysis Optional 2 MANM061 Dissertation Compulsory 60 2 How many optional modules must a student choose in order to achieve the necessary amount of credits to achieve this level? PG Dip 120 credits at FHEQ level 7 must be achieved before a student may exit this programme with a PG Dip The pass mark for all modules is 50% Choose 1 optional module from 2 in semester 1 Choose 3 optional modules from the 6 in semester Opportunities for placements / work-related learning / collaborative activity please indicate if any of the following apply to your programme Data supplied by an external source for student analysis which contributes to an assessment Guest / external / associate lecturer (please detail the extent of their contribution, i.e. do they mark?) Professional Training Year (PTY) Placement, study or work placement outside of the PTY(please indicate if this is one day, one month, six months, a year etc) Clinical Placements (that are not part of the PTY Scheme) ERASMUS Study (that is not taken during Level P) Study exchanges (that are not part of the ERASMUS Scheme) Dual Degree Joint Degree Further information 22. Criteria for admission Target groups The programme will target individuals who are interested in developing skills and knowledge that can exploit and develop information from large databases to deliver value and competitive advantage to employers and employees. Employers such as IBM and Microsoft have highlighted the shortages of qualified students.

7 Qualifications required for entry The entry requirement for applicants to the programme would be to hold a Bachelor s degree to at least UK Upper Second/ 2:1 or equivalent from a recognised British or Overseas University that have a significant exposure to mathematical subjects such as: economics, finance, mathematics, computer science or engineering subjects. For applicants whose first language or education is not in English, a minimum IELTS score of 6.5 (with not less than 6.0 in every element) or above (or equivalent e.g. TOEFL or Cambridge Advanced Certificate in English). Applicants may also be eligible to enrol on the University of Surrey English language programmes to facilitate English language development. 23. Assessment regulations Please click on the following link for the full assessment regulations All programmes within the University of Surrey adhere to the Assessment Regulations. All taught programmes also reference and follow the Code of practice for assessment and feedback. 24. Support for students and their learning The strategy aims in the most effective and efficient ways: To provide a framework of knowledge within which students can take responsibilities for their own learning; To introduce students to the latest thinking and research; To give opportunities for students to consider and evaluate the issues and to explore them further with their peers and lecturers. Overall Learning and Teaching Strategy The focus of teaching and learning strategies is on developing students as independent and reflective learners. This is encouraged from the point of Induction. Induction introduces students to the Faculty and University expectations of them, and also aims to set student expectations of us. In addition, it introduces students to SurreyLearn (see below), which is a major vehicle for teaching and learning in the Faculty. Induction also raises issues such as plagiarism, to alert students to University policy on this at an early stage. The need for hard work and commitment is stressed through induction sessions. Some modules cross programmes and as such are taught in large groups. In some cases these groups will be broken down into smaller tutorial groups for instance Supply Chain Analytics where practicing mathematical manipulations is an important part of learning. Despite this being labour intensive, previous results have evidenced the correlation between attendance of such sessions and success in the modules. Programme specific modules will involve smaller groups. Within the classroom, teaching and learning approaches can include didactic teaching, discussions, question and answer sessions, case studies, simulations, student-lead sessions and external lecturers. The latter are often invited to give an industry perspective on the topic. We encourage students to interact with the session, which can be a challenge in larger groups and with those from cultures with a tendency to avoid speaking out. To overcome this, a number of strategies may be employed, including the use of buzz groups where a small group discusses the issue and reports back on the group view. Another widely used approach within the Faculty is the Electronic Voting System (EVS). This is particularly

8 effective as a means of increasing engagement within large lecture groups where individuals are often reticent to speak out. It also allows students to test their knowledge, without exposing themselves. Used in this way the EVS is also a useful and effective means of providing formative feedback. Support in searching the literature is provided at module level, but also by the Faculty librarians. These run bespoke sessions by Programme, providing advice and guidance on the most appropriate databases and search strategies. These sessions are run early in the academic year, and then again closer to preparation of the Dissertation. SurreyLearn is used to a greater or lesser extent by all staff in the Faculty. All modules post Module handbooks, assessment briefs, reading lists and so on in their area. Powerpoint presentations are also, usually, posted prior to a lecture, allowing students to print these off prior to the session. This is particularly valuable for those with English as a second language, or with specific learning difficulties, as they are able to familiarise themselves with the material prior to a lecture. SurreyLearn also provides a useful discussion area where students can post questions about assignments, etc. Module leaders answer these, such that the entire cohort can benefit from the clarification. Support may also be offered between students. Some Module Leaders will also put useful materials, weblinks, podcasts, etc. into the Module area. Teaching and learning strategies also aim to develop generic skills, albeit that these are not all assessed in all modules. Across a programme we aim to cover those skills identified as important by industry. The primary focus of this programme is to provide the students with capability required to analyse data and to apply mathematical models. Furthermore, students will have to be able: to give oral presentations during their programmes, to write concise reports, to write assignments in an evaluative, critical, creative and innovative way, to search for and use the literature to inform arguments, to work co-operatively and independently and to develop research skills (largely through the Research Methods module and the dissertation, but also through other modules). IT skills are embedded in programmes through the need to employ a variety of programmes, including programming, spread-sheets, and data analysis programmes and databases, across modules and the dissertation. Some work is undertaken in groups (although the ultimate assessment attached to this may be written up individually). Within a business-related degree we believe that it is important for students to experience the challenges and rewards of working in teams. Given the nature of the cohort, this also exposes students to working with people from different cultures, which is important in an increasingly global business environment. Students work in different groups, some tutors assigning groups, some allowing self-selection, but usually requiring students to not work always with the same group (which might often mean working with those from their own cultural background). Those who enter the University with English as their second language, which in our case will mean the majority of students, undertake a diagnostic English test during Induction week. This is despite the students being required to achieve an IELTS of 6.5 (minimum of 6.0 in any component) or equivalent. Students who are identified as having weaknesses in some element of their English abilities (listening, reading, writing) are invited to attend appropriate remedial English sessions at no extra charge. These do not form an assessed part of the Masters programme. Students are encouraged to attend and the importance of the sessions stressed by the Director of Studies, Programme Leaders and Personal Tutors. The English language Institute does provide feedback on attendance and students found not to be attending are contacted by their Programme Leader. 25. Quality management indications of quality and the methods for evaluating and improving quality The quality management of this programme is monitored through: Periodic programme review

9 Annual Programme Review Reports Module Evaluation Questionnaires The igrad Survey Joint Staff Student Liaison Committees Personal Tutoring Board of Study meetings Board of Examiners 26. Further information Further information can be found on our webpages at and within the Programme Handbook, which is provided on entry to the Programme. The Regulations and Codes of Practice for taught programmes can be found at

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