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:	2020/1
Module lecturers:	Professor Joshua Ignatius - Convenor
Module credit:	15
ECTS value:	15
Pre-requisites:	This module is closed to MSc Business Analytics only
Co-requisites:	N/A
Duration of module:	Duration (weeks) - term 2: 12

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. P8: Work with stakeholders from a range of backgrounds to identify the need for, design, develop, and deploy, analytics solutions within a business environment
7. 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
30	120	0

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

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
Practical (take-home) coursework exercise	30	2 hours duration	1-5	Written
Individual report	70	3000 words	1-7	Written
	0

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
Practical (take-home) coursework exercise	Practical (take-home) coursework exercise (30%)	1-5	Summer reassessment period
Individual report	Individual report (70%)	1-7	Summer reassessment period

Re-assessment notes

Re-assessment will be in nature to the original assessment, but the topic, data, and materials must be new.

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 reassessment 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 re-take some or all parts of the assessment, as decided by the Module Convenor. The final mark given for a module where re-assessment was taken as a result of referral will be capped at 50%.

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 decision making algorithms under uncertainty

Indicative learning resources - Basic reading

The following resources may be useful throughout the course:

Winston, W. L. (2004). Operations research: Applications and algorithms (4^th ed.). Belmont, CA: Thomson/Brooks/Cole.
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?

Yes

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

Origin date

09/01/2020

Last revision date

01/09/2020