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DRPS : Course Catalogue : Business School : Common Courses (Management School)

Postgraduate Course: Performance Analytics with DEA: Basic Concepts and Methods (CMSE11424)

Course Outline
SchoolBusiness School CollegeCollege of Arts, Humanities and Social Sciences
Credit level (Normal year taken)SCQF Level 11 (Postgraduate) AvailabilityNot available to visiting students
SCQF Credits10 ECTS Credits5
SummaryThis course provide students with fundamental theory of Data Envelopment Analysis (DEA).
Course description Academic Description
Data Envelopment Analysis (DEA) is a performance evaluation and bench-marking methodology. DEA is a non-parametric and frontier-based methodology that benchmarks against the best or the worst practice frontier. Nowadays, DEA is commonly used for the relative performance evaluation and risk assessment of entities such as banks, bank branches, firms listed on stock markets, investment vehicles including projects, production technologies, suppliers, etc. This course aims at training students in the field of performance evaluation and management using DEA as the main methodology. The course shall cover the key concepts in performance management along with a general classification of performance evaluation methodologies; DEA concepts and generic methodology; static black-box DEA models and their use in business applications; and practical issues in DEA and how to address them.

Outline Content
1. Key concepts in performance management along with a general classification of performance evaluation methodologies
2. DEA concepts and generic methodology
3. Static DEA models and their use in business applications
4. Practical issues in DEA and how to address them

Student Learning Experience
Weekly lectures and hands-on programming exercises in Matlab and DEA solvers which enables students to implement the methodologies covered in class.

Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Other requirements For MSc Business Analytics students, or by permission of course organiser. Please contact the course secretary.
Course Delivery Information
Academic year 2020/21, Not available to visiting students (SS1) Quota:  None
Course Start Block 3 (Sem 2)
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 100 ( Lecture Hours 10, Seminar/Tutorial Hours 10, Programme Level Learning and Teaching Hours 2, Directed Learning and Independent Learning Hours 78 )
Assessment (Further Info) Written Exam 0 %, Coursework 100 %, Practical Exam 0 %
Additional Information (Assessment) Individual Report (100% weighting)
Assesses Learning Outcomes 1 to 5.

Course Assessment:
Students will have to undertake a performance evaluation and/or risk assessment exercise including problem statement, model building, solution design, report on findings, formulation of recommendations and managerial guidelines. The report should demonstrate effective communication of performance problems and viable solutions to demonstrate students' ability to address real world performance problems and to convince their line managers or sponsors to implement the proposed solution.

Feedback Feedback on formative assessed work will be provided in line the Taught Assessment Regulation turnaround period, or in time to be of use in subsequent assessments within the course, whichever is sooner. Summative marks will be returned on a published timetable, which will be communicated to students during semester. All assessments will be marked according to the University Common Marking Scheme.
No Exam Information
Learning Outcomes
On completion of this course, the student will be able to:
  1. Discuss the concept and methods of performance measurement, evaluation, and management using the proper terminology
  2. Identify and properly state performance problems in different business settings
  3. Address performance problems within a static DEA framework and choose the right basic DEA models to devise solutions
  4. Formulate managerial guidelines in the area of performance management and make recommendations based on basic DEA analyses
  5. Communicate performance problems and basic solutions effectively and efficiently to a critical audience
Reading List
Cooper WW, Seiford LM and Tone K. (2007) Data Envelopment Analysis: A Comprehensive Text with Models, Applications, References and DEA-Solver Software. Second Edition. Springer
Additional Information
Graduate Attributes and Skills Numeracy and Big data
Knowledge integration and application
Analytical thinking
Written communication
KeywordsNot entered
Course organiserProf Jamal Ouenniche
Tel: (0131 6)50 3792
Course secretaryMs Emily Davis
Tel: (0131 6)51 7112
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