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Operations Analytics

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.

Full module specification

Module title:Operations Analytics
Module code:BEMM462
Module level:M
Academic year:2023/4
Module lecturers:
  • Dr Han Lin - Lecturer
Module credit:15
ECTS value:



This module is only available for MSc Business Analytics and MSc Global Operations Management students. 

For students on the MSc Business Analytics there are no pre-requisitesFor students on the MSc Global Operations Management, this module can only be taken if BEMM460 Statistics and Mathematics for Business Analytics has been completed.



Duration of module: Duration (weeks) - term 2:


Module aims

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 ActivitiesGuided independent studyPlacement / study abroad

Details of learning activities and teaching methods

CategoryHours of study timeDescription
Scheduled Learning and Teaching Activities 30Lectures, workshops and labs (6 x 5 hours)
Guided Independent Study50Preparatory reading prior to workshops and lectures
Guided Independent Study70Practice use of software and concepts from additional exercises and examples

Formative assessment

Form of assessmentSize of the assessment (eg length / duration)ILOs assessedFeedback method
Review of individual performance on group exercisesDuring workshops / tutorialsn/aVerbal
Outline plan for assessed reportOne pagen/aWritten/Verbal

Summative assessment (% of credit)

CourseworkWritten examsPractical exams

Details of summative assessment

Form of assessment% of creditSize of the assessment (eg length / duration)ILOs assessedFeedback method
Group assessment (groups of 3 to 4 students)301,000 words1-7Electronic, written comments
Individual report702,000 words1-7Electronic, written comments

Details of re-assessment (where required by referral or deferral)

Original form of assessmentForm of re-assessmentILOs re-assessedTimescale for re-assessment
Group assessment (30%)Individual Report (30%)1-7August/September Reassessment Period
Individual report (70%)Individual report (2,000 words, 70%)1-7August/September Reassessment Period

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

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:

  • Download page:


Module has an active ELE page?


Indicative learning resources - Web based and electronic resources

Some helpful websites:

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