Prescriptive Analytics module (BU52711)

Prescriptive analytics focuses on recommending actions to reach desired outcomes. It goes beyond descriptive analytics (what happened) and predictive analytics (what might happen) by turning data insights into clear next steps you can take.

Prescriptive analytics relies on techniques like optimisation and decision theory. This helps you evaluate various scenarios to determine the best course of action under given constraints. 

It is widely used in industries such as logistics, finance, healthcare, and marketing. It can improve decision-making, efficiency, and performance.

Some examples of where it might be used are:

• Retail: optimise inventory levels and allocate the promotions budget
• Healthcare: schedule surgeries and coordinate operating-theatre resources
• Delivery and logistics: design delivery plans and routes to minimise transport costs

By combining real-time data with predictive models, prescriptive analytics helps organisations anticipate likely events and choose actions that influence the outcome. It supports clear, evidence-based decisions that are practical and aligned with organisational strategy

What you will learn 

In this module you will: 

• learn to formulate complex real-world problems in mathematical form
• discover decision making techniques and solution methods
• practice solving such problems using industry standard software and tools

By the end of this module you will be able to : 

• gain proficiency in using industry-standard software to conduct analyses
• evaluate and select most appropriate techniques to address specific business problems
• communicate analytical insights to both technical and non-technical audiences

Assignments / assessment

• Coursework, 2,500-word report (50%)
• Written exam, 2 hours (50%)

Teaching methods / timetable

You will learn through weekly interactive lectures and lab sessions that provide hands-on experience with specialised, industry-standard software, supported by videos, lecture slides, books, tutorial questions, and other library resources.