Modules

Core Module Information
Module title: Prescriptive Analytics
SCQF level: 11:
SCQF credit value: 20.00
ECTS credit value: 10
Module code: SOE11449
Module leader: Max Chipulu
School The Business School
Subject area group: Management
Prerequisites

There are no pre-requisites for this module to be added
Description of module content:

Organisations face countless complex decisions daily. To operate efficiently and plan effectively, finding the best solutions is critical. Prescriptive Analytics are modelling techniques and software tools that help organisations determine the best course of action. This module equips you with powerful prescriptive analytics techniques to optimise decision-making in your organisation. You will learn how to appraise optimisation problems, evaluate and apply appropriate techniques, and communicate your findings effectively to non-technical stakeholders.
Learning Outcomes for module:

Upon completion of this module you will be able to

LO1: Appraise and formulate an optimisation problem.

LO2: Critically evaluate the appropriateness of optimisation techniques and software to model and solve diverse business problems.

LO3: Demonstrate a critical understanding of the different types of simulation techniques and have insight into the domains in which we can usefully apply each.

LO4: Model business decision problems using the appropriate simulation techniques.

LO5: Explain the results of your prescriptive model to non-technical business users in a way that is easy to understand.
Full Details of Teaching and Assessment
2025/6, Trimester 1, ONLINE,
VIEW FULL DETAILS
Occurrence: 001
Primary mode of delivery: ONLINE
Location of delivery: ONLINE
Partner:
Member of staff responsible for delivering module: Max Chipulu
Module Organiser:


Student Activity (Notional Equivalent Study Hours (NESH))
Mode of activityLearning & Teaching ActivityNESH (Study Hours)NESH Description
Independent Learning Practical classes and workshops 12 In weekly online live academic sessions, you will gain hands-on experience with relevant software tools. Interactive case studies, based on real organisations and datasets where possible, will help you apply what you've learned to real-world situations.
Online Guided independent study 188 Independent reading: You will engage with materials on specific topics at your own pace. A variety of online resources (e.g., code samples, articles, textbooks, videos, etc.) will be provided to help you develop a deep understanding of the module content.
Total Study Hours200
Expected Total Study Hours for Module200


Assessment
Type of Assessment Weighting % LOs covered Week due Length in Hours/Words Description
Project - Practical 100 1~2~3~4~5 Week 13 HOURS= 3500 words You will:1. Model and solve a problem using the appropriate optimisation techniques.2. Interpret the results of your analysis and write a report of your findings in non-technical language that any layperson in business can understand (3500 words).3. You will submit through Moodle:a) A digital file containing your computer model in the appropriate software format so that the model can be run and tested.b) A Word or PDF document containing your report.
Component 1 subtotal: 100
Component 2 subtotal: 0
Module subtotal: 100

Indicative References and Reading List - URL:
Contact your module leader
 

Related information