This module focuses on analytics from an operations management perspective. Operations Management covers the design, optimisation and management of products, processes, services and supply chains. It uses analytics to make decisions regarding product and service quality and cost, and as well as decisions regarding acquisition, development, and utilization of resources. You will learn about the value of analytics when applied to different types of data such as: machine data, sensor data, and other forms of data generated by operational systems.
Full module specification
|Module title:||Operations Analytics|
This module is closed to MSc Business Analytics only
|Duration of module:||
Duration (weeks) - term 3: |
The module aims to impart knowledge and skills in optimisation and decision-making algorithms where students can apply to a variety of fields, including business, education, and research. Graduates of this module would be equipped to frame and analyse decisions through an optimisation framework, leading to employment as technical staff members in business or industry, government planners, and private consultants.
ILO: Module-specific skills
- 1. P2: Demonstrate knowledge and understanding of key business processes and structures, and the role of business analytics in decision support.
- 2. P3: Critically analyse and discuss current issues and influences relevant to the ongoing development of business analytics, and its application.
- 3. P4: Draw on knowledge of current research and practice to identify and apply appropriate analytics methods and tools to a range of business situations.
- 4. P5: Create, manage, interrogate, interpret and visualise data from a wide range of different sources, types and including structured and unstructured forms.
ILO: Discipline-specific skills
- 5. P6: Critically analyse the use of data within a business context, identifying strengths and limitations.
- 6. P10: Contribute effectively to managerial decision processes within a business context.
Learning activities and teaching methods (given in hours of study time)
|Scheduled Learning and Teaching Activities||Guided independent study||Placement / study abroad|
Details of learning activities and teaching methods
|Category||Hours of study time||Description|
|Scheduled Learning and Teaching Activities||30||Lectures, workshops and labs (6 x 5 hours)|
|Guided Independent Study||50||Preparatory reading prior to workshops and lectures|
|Guided Independent Study||70||Practice use of software and concepts from additional exercises and examples|
|Form of assessment||Size of the assessment (eg length / duration)||ILOs assessed||Feedback method|
|Review of individual performance on group exercises||During workshops / tutorials||n/a||Verbal|
|Outline plan for assessed report||One page||n/a||Written/Verbal|
Summative assessment (% of credit)
|Coursework||Written exams||Practical exams|
Details of summative assessment
|Form of assessment||% of credit||Size of the assessment (eg length / duration)||ILOs assessed||Feedback method|
|Group assessment (groups of 3 to 4 students)||30||1,000 words||1-7||Electronic, written comments|
|Individual report||70||2,000 words||1-7||Electronic, written comments|
Details of re-assessment (where required by referral or deferral)
|Original form of assessment||Form of re-assessment||ILOs re-assessed||Timescale for re-assessment|
|Group assessment (30%)||Individual Report (30%)||1-7||August/September Reassessment Period|
|Individual report (70%)||Individual report (2,000 words, 70%)||1-7||August/September Reassessment Period|
The module showcases analytical techniques and tools to problems involving the operations of a system, which includes:
- Formulating operational and business problems as linear programs
- Apply solution methods of linear optimisation in operational problems
- Solving supply and demand issues through the assignment problem
- Apply network algorithms to solve a broad variety of operational problem
- Apply multi-objective optimization methods
Indicative learning resources - Basic reading
The following resources may be useful throughout the course:
- Winston, W. L., & Albright, S. C. (2019). Practical management science. Cengage. 6th Edition.
- Bertsimas, D., O’Hair, A., & Pulleyblank, W. R. (2016). The analytics edge. Belmont, MA: Dynamic Ideas LLC.
Official page for R: http://www.r-project.org
- Download page: http://www.cran.r-project.org
Module has an active ELE page?
Indicative learning resources - Web based and electronic resources
Some helpful websites:
Last revision date