Operations Analytics

Module title	Operations Analytics
Module code	BEMM462
Academic year	2025/6
Credits	15
Module staff	Dr Han Lin (Convenor)

Duration: Term	1	2	3
Duration: Weeks			10

Number students taking module (anticipated)	60

Module description

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.

Module aims - intentions of the module

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.

Intended Learning Outcomes (ILOs)

ILO: Module-specific skills

On successfully completing the module you will be able to...

1. P1: Demonstrate knowledge and understanding of key business processes and structures, and the role of business analytics in decision support.
2. P2: Critically analyse and discuss current issues and influences relevant to the ongoing development of business analytics, and its application.
3. P3: Draw on knowledge of current research and practice to identify and apply appropriate analytics methods and tools to a range of business situations.
4. P4: 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

On successfully completing the module you will be able to...

5. P5: Critically analyse the use of data within a business context, identifying strengths and limitations.
6. P6: Contribute effectively to managerial decision processes within a business context.

ILO: Personal and key skills

On successfully completing the module you will be able to...

7. P7: Demonstrate the ability to work collaboratively in teams to solve complex operational problems and communicate solutions effectively.
8. P8: Apply critical thinking and analytical reasoning to evaluate alternative strategies and make sound decisions under uncertainty.
9. P9: Develop independent learning skills, including time management and reflective practice, to enhance personal effectiveness in professional settings.
10. P10: Communicate technical and non-technical information clearly and effectively to a variety of audiences, using appropriate media and formats.

Syllabus plan

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

Learning activities and teaching methods (given in hours of study time)

Scheduled Learning and Teaching Activities	Guided independent study	Placement / study abroad
20	130	0

Details of learning activities and teaching methods

Category	Hours of study time	Description
Scheduled learning and teaching activities	20	Lectures, workshops and labs (6 x 5 hours per week in Term 3)
Guided Independent Study	60	Preparatory reading prior to workshops and lectures
Guided Independent Study	70	Practice use of software and concepts from additional exercises and examples

Formative assessment

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
100	0	0

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 (1,000 words, 30%)	1-7	Referral/deferral period
Individual report (70%)	Individual report (2,000 words, 70%)	1-7	Referral/deferral period

Re-assessment notes

Deferral – if you miss an assessment for certificated reasons judged acceptable by the Mitigation Committee, you will normally be either deferred in the assessment or an extension may be granted. The mark given for a re-assessment taken as a result of deferral will not be capped and will be treated as it would be if it were your first attempt at the assessment.

Referral – if you have failed the module overall (i.e. a final overall module mark of less than 50%) you will be required to submit a further assessment as necessary. If you are successful on referral, your overall module mark will be capped at 50%.

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. 6^th 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

Indicative learning resources - Web based and electronic resources

Some helpful websites:

http://www.statmethods.net
www.rseek.org
http://www.ats.ucla.edu/stat/r/
http://finzi.psych.upenn.edu/search.html

Key words search

Operations Research, R, Optimization, Analytics, Decision Making

Credit value	15
Module ECTS	7.5
Module pre-requisites	Prior evidence of achievement in Statistics and Mathematics is required.
Module co-requisites	None
NQF level (module)	7
Available as distance learning?	No
Origin date	09/01/2020
Last revision date	29/05/2025