Postgraduate Course: Methods and Tools for Business Analytics (CMSE11337)
Course Outline
| School | Business School |
College | College of Humanities and Social Science |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Availability | Available to all students |
| SCQF Credits | 15 |
ECTS Credits | 7.5 |
| Summary | This course aims to equip students with tools and frameworks to tackle common decision problems in business and marketing management. The course develops skills in understanding, framing and structuring a managerial problem, as well as building, verifying, validating and using decision support models to inform better and effective decision making. In terms of the specific modelling and analysis techniques studied in this course, the focus is intentionally put on; discrete event simulation, linear and integer programming. Spreadsheet modelling using Microsoft Excel will also be covered, to ensure all students possess the skillset required in quantitative modelling of business decisions through the use of electronic spreadsheets. Using an extensive case study and realistic examples, students will learn how to model and analyse decision problems with commercial software for discrete event simulation (Arena), spreadsheet modelling tools (Excel) and statistical analysis (Minitab), thus complementing learning experiences of other software packages on the programme (e.g. SPSS, SPSS Modeller, etc.). |
| Course description |
Aims, Nature, Context
This course builds on knowledge gained in the core courses of the MSc Marketing and Business Analysis programme, particularly: Marketing Decision Analysis, Business Statistics and the quantitative component of Marketing Research. Methods and Tools for Business Analytics (MTBA) complements these other courses and minimises overlap of materials.
Teaching will involve a combination of lectures, tutorials and independent study. The key issues and techniques will be presented in lectures. Tutorial examples will re-enforce learning through practical experience as well as offering the opportunity to obtain immediate feedback from the lecturer should any problems arise. Furthermore, tutorials will also offer the opportunity to develop technical modelling skills. Students will also be expected to engage in self-study, both to consolidate the learning of core work and to familiarise themselves with the broader literature. A key component of the learning experience is represented by the coursework, where students will apply one of the techniques studied in the course, discrete event simulation, to a realistic case study, thereby simulating a realistic case of management consulting project where simulation is employed.
Syllabus
A detailed lecture outline is available as a separate document on the course Learn page.
Student Learning Experience
Students will:
* participate in lectures, held in a computer lab setting, where they will be introduced to the principles and techniques involved in structuring and solving of business problems, through: spreadsheet modelling and analysis; discrete event simulation modelling and analysis; and mathematical programming (linear and integer programming).
* complete tutorial exercises, also in a computer lab setting, which will reinforce the ideas discussed in lectures;
* actively engage in discussions both inside and outside of the classroom;
* construct a discrete event simulation model of a business problem, analyse the model and produce an executive report;
* perform independent reading and research:
* critically reflect on their own learning experiences.
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
Students MUST have passed:
Marketing Decision Analysis (CMSE11120)
|
Co-requisites | |
| Prohibited Combinations | |
Other requirements | For Business School PG students only, or by special permission of the School. Please contact the course secretary. |
Information for Visiting Students
| Pre-requisites | None |
| High Demand Course? |
Yes |
Course Delivery Information
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| Academic year 2017/18, Available to all students (SV1)
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Quota: None |
| Course Start |
Semester 2 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
150
(
Lecture Hours 24,
Seminar/Tutorial Hours 13,
Summative Assessment Hours 2,
Programme Level Learning and Teaching Hours 3,
Directed Learning and Independent Learning Hours
108 )
|
| Assessment (Further Info) |
Written Exam
50 %,
Coursework
50 %,
Practical Exam
0 %
|
| Additional Information (Assessment) |
Coursework 50%
Exam 50% |
| Feedback |
The feedback consists of: continuous (formative) feedback on practical work; (summative and formative) feedback in the individual coursework; and (summative) feedback in the written exam.
Feedback on the individual coursework will be provided within 15 working days of submission, or in time to be of use in subsequent assessments within the course, that is the final written examination, whichever is sooner. Summative exam marks will be returned on a published timetable, which has been made clear to students at the start of the academic year.
Students will gain in-process formative feedback on their understanding of the material when they discuss their answers to the tutorial questions posed during the computer labs. Students are also strongly encouraged to ask questions in lectures to assess their knowledge and understanding of the subject as the course progresses. Finally, the lecturer will be available to provide one-on-one formative feedback to individual students who wish to meet during his office hours, in which case a time slot must be booked via email by contacting the lecturer directly. |
| Exam Information |
| Exam Diet |
Paper Name |
Hours & Minutes |
|
| Main Exam Diet S2 (April/May) | | 2:00 | |
Learning Outcomes
On completion of this course, the student will be able to:
- Understand and critically discuss the nature of problem solving and decision making (and its support through quantitative techniques) in business and marketing management
- Understand and critically assess various methods for structuring management decision problems
- Understand and apply the techniques of discrete event simulation, linear programming, and integer programming for modelling decision problems
- Understand and critically assess the relative merits of discrete event simulation, linear programming, and integer programming
|
Reading List
The official course material is released in the form of slide sets (Powerpoint format). These will be made available after each session, as the course progresses. This official material, especially if integrated by good quality own notes by the student, should be enough both to prepare for the exam and to carry out a successful coursework, provided the student also engages, at the same time, with the practical aspect of the course in the computer lab.
The following textbooks provide useful references for different parts of the course. Specific references to these sources are given in the official course slides whenever a piece of theory or a particular example or tutorial is taken or developed from these sources. These textbooks are available in The Hub for consultation and integration with all other course material.
* Albright, S.C. and Winston, W.L. (2011) Management Science Modeling (4th edition), South-Western Cengage (International Edition)
* Ragsdale, C.T. (2011) Managerial Decision Modeling (6th edition), South-Western Cengage Learning (International Edition)
* Law, A.M. (2014) Simulation Modeling and Analysis (5th edition), McGraw-Hill
* Kelton, W.D., Sadowski, R.P. and Zupick, N.B. (2014) Simulation with Arena (6th edition) McGraw-Hill
* Albright, S.C and Winston, W.L. (2004), Spreadsheet Modeling and Applications - Essentials of Practical Management Science, South-Western Cengage Learning
* Walkenbach, J. (2010) Microsoft® Excel® 2010 Bible, Wiley |
Additional Information
| Graduate Attributes and Skills |
Cognitive Skills
Students will develop skills such as:
* the ability to build models to support management decision making;
* the ability to critically validate models for management decision making;
* the ability to interpret results from decision-making models in light of possible courses of action for a given business/marketing problem or situation;
* the ability to understand methods of model solution.
Subject Specific Skills
Students will gain:
* an appreciation of methods involved in business decision modelling;
* experience in applying model building methods to realistic examples;
* experience in using commercial software to tackle management decision problems.
By the end of the course students will be expected to:
* be able to plan and carry out analyses based on construction and solution of appropriate models;
* be able to employ analytical and problem-solving skills;
* show that they can report results in a concise way;
* have enhanced their skills in using commercial software products. |
| Keywords | Not entered |
Contacts
| Course organiser | Dr Maurizio Tomasella
Tel:
Email: |
Course secretary | Miss Ashley Harper
Tel: (0131 6)51 5671
Email: |
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