MANU9BA: Business Analytics

Semester:  Autumn

Level:  10

Credit Value:  20

Module Coordinator:  Dr Gerry Edgar, Management, Work & Organisation Division

Contact Hours:  30 hours

Assessment:  100% assignment based on an analysis of 3 case studies using the methods and computer based tools taught in the module


Modern businesses have vast amounts of data. Often data are overwhelming and add to the confusion of managers striving to control their organisation. But a knowledge of a few basic techniques can help you use the data to gain insights into problems and explore possible solutions. The module develops a capability in the techniques which are central to much quantitative analysis in management.  In addition to developing your technical capability, the module encourages creativity in analysis, often the greatest challenge is in selecting the most appropriate technique and deploying it in a meaningful way. The objective is to turn data into valuable information, enabling managers to make better decisions. Business Analysis will be put into practice via the development of a range of consultancy skills.

Aim:

This Business Analysis combines: statistics and modelling.  Statistics seeks to clarify and summarise numerical data and then make deductions from those data.  A command of a few statistical techniques provides great power to managers, enabling them to combine judgement with quantitative evidence to inform decisions.  For example, following an expensive marketing campaign, this year’s sales have increased but is this just due to chance or a result of the campaign?  Statistics provides a language for examining uncertainty and distinguishing acceptable business risks from foolhardy gambles.

This module will develop vital basic modelling skills, and provide you with the opportunity to explore other more sophisticated techniques.

Both statistics and modelling extensively employ computers to remove the routine number crunching.  This module employs Excel in a range of applications in statistical analyses and forecasting. 

In addition consultancy skills are essential to putting the Business Analysis into practice. The analyst must carefully define the problem with the client. Effective presentation and report writing skills are essential both for initially tendering for a project and presenting findings.

A student completing this module will have developed a range of skills for problem definition and solution and also skills to help sell the results to clients.

Objectives:

This Business Analysis combines: statistics and modelling.  Statistics seeks to clarify and summarise numerical data and then make deductions from those data.  A command of a few statistical techniques provides great power to managers, enabling them to combine judgement with quantitative evidence to inform decisions.  For example, following an expensive marketing campaign, this year’s sales have increased but is this just due to chance or a result of the campaign?  Statistics provides a language for examining uncertainty and distinguishing acceptable business risks from foolhardy gambles.

This module will develop vital basic modelling skills, and provide you with the opportunity to explore other more sophisticated techniques.

Both statistics and modelling extensively employ computers to remove the routine number crunching.  This module employs Excel in a range of applications in statistical analyses and forecasting. 

In addition consultancy skills are essential to putting the Business Analysis into practice. The analyst must carefully define the problem with the client. Effective presentation and report writing skills are essential both for initially tendering for a project and presenting findings.

A student completing this module will have developed a range of skills for problem definition and solution and also skills to help sell the results to clients.

Learning Outcomes:

  • Knowledge of problem definition techniques.
  • Appreciate and perform basic quantitative techniques much used in business analysis and decision making.
  • Appreciate the role of modelling in business analysis.
  • Develop an awareness of the uncertainties in data and the methods of coping with these uncertainties.
  • Enable formulation of suitable quantitative problems, obtain a solution and interpret the solution. 

 

This module information is representative of what is included in the module in a given year. Details of actual reading, lectures and coursework may vary year to year and will be available at the beginning of the semester.

 

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