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The University of Southampton

MANG6346 Business Analytics and Risk

Module Overview

In today's era of "big data", business analytics has become a key part of management decision making. Modern managers must now routinely understand the use and value of both qualitative and quantitative data in order to manage risk more effectively. This module provides an overview of the key analytical tools and techniques to improve decision-making in an uncertain business environment.

Aims and Objectives

Learning Outcomes

Knowledge and Understanding

Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:

  • The impact of risk and uncertainty in a range of business scenarios;
  • The different uses of data analytics to inform business decisions.
  • A range of analytical modelling approaches to support business decisions.
Subject Specific Intellectual and Research Skills

Having successfully completed this module you will be able to:

  • Analyse and evaluate business risk scenarios, based on relevant data and statistical techniques;
  • Apply a range of business analytics to support business decisions.
  • Critically evaluate the appropriate application of different analytical approaches;
Transferable and Generic Skills

Having successfully completed this module you will be able to:

  • Thinking critically and arguing effectively;
  • Interpreting and analysing quantitative data related to business issues, using appropriate financial and/or statistical skills and models to solve problems;
  • Information technology and computing using commercial software;
  • Use problem structuring methods to analyse complex problems.


Basic principles underpinning descriptive, predictive and prescriptive analytics such as, but not limited to: - Statistics analysis - Visual analytics - Decision making under uncertainty - Forecasting and classification - Simulation Applications of descriptive analytics tools Applications of predictive analytics tools Applications of prescriptive analytics tools

Learning and Teaching

Teaching and learning methods

- Lectures - Problem solving sessions - Case studies

Independent Study70
Total study time100

Resources & Reading list

Robinson, S. (2004). Simulation: The Practice of Model Development and Use. 

Kunc, M. (2018). Strategic Analytics: Integrating Management Science and Strategy. 

Morris, C. (2003). Quantitative Approaches in Business Studies. 

Evans, J.R. (2014). Business Analytics: Methods, Models, and Decisions. 

Curwin, J. and Slater, R (2004). Quantitative Methods: A short course. 

Wisniewski, M. (2010). Quantitative Methods for Decision Makers. 

Render, B., Stair, R.M. and Hanna M.E. (2009). Quantitative Analysis for Management. 

Kunc, M., and O'Brien, F.A. (2018). The role of business analytics in supporting strategy processes: Opportunities and limitations. Journal of the Operational Research Society. ,1-12 .



In-class formative opportunities


MethodPercentage contribution
Examination  (2 hours) 50%
Report  (2000 words) 50%


MethodPercentage contribution
Examination  (2 hours) 50%
Report  ( words) 50%


MethodPercentage contribution
Report  (2000 words) 100%

Repeat Information

Repeat type: Internal & External


Costs associated with this module

Students are responsible for meeting the cost of essential textbooks, and of producing such essays, assignments, laboratory reports and dissertations as are required to fulfil the academic requirements for each programme of study.

In addition to this, students registered for this module typically also have to pay for:


Recommended texts for this module may be available in limited supply in the University Library and students may wish to purchase the mandatory/additional reading text as appropriate.

Please also ensure you read the section on additional costs in the University’s Fees, Charges and Expenses Regulations in the University Calendar available at

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