• University of Exeter Business School
• Module

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.

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. identify and apply appropriate analytics methods and tools to a range of business situations;
• 2. demonstrate knowledge and understanding of fundamental, and domain-specific, analytics methods and tools;
• 3. 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...

• 4. critically analyse the use of data within a business context, identifying strengths and limitations.

ILO: Personal and key skills

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

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

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

Details of learning activities and teaching methods

Formative assessment

Summative assessment (% of credit)

Details of summative assessment

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

Re-assessment notes

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

Indicative learning resources - Basic reading

The following resources may be useful throughout the course:

• Winston (2004). Operations research: Applications and algorithms. Belmont, CA: Thomson/Brooks/Cole.
• Bertsimas, D., Allison, K. O. & Pulleyblank, W. R. (2016). The analytics edge. 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