IS01 - Quantitative Management Techniques

Stirling Management School

Business & Organisation Division

ISMP01/91 - Quantitative Management Techniques

department > postgraduate > ism
department > postgraduate > mba
department > postgraduate > ib

Module Co-ordinator: Ms Gill Mould

Module Aims

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.

This module combines two linked themes: 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.

Modelling for management entails building a representation of reality and experimenting, usually based on a computer package. Some of the most useful models are very simple, but others may be more detailed and sophisticated. A simple financial model might reflect the effect of exchange rate fluctuations on the profitability of a proposed venture. But a more complex simulation model of a factory production line might be needed to experiment with different options, identifying the best approach to eliminating bottlenecks and increasing capacity. 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: statistical analyses, financial modelling and forecasting.

In summary, the objectives of this module are to:

· introduce the basic quantitative techniques much used in business analysis and decision taking;

· 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 you to formulate a suitable quantitative problem, obtain a solution and interpret the solution.

Teaching Format

Each week you will normally attend two one-hour lectures and a two-hour workshop session. Exercises will be issued prior to the workshops and you are expected to prepare answers in advance of the workshops: the workshop sessions will be used to discuss any problems that have arisen and to explore further exercises designed to develop your skills. The workshops begin with an Excel exercise which is designed to ensure that you are familiar with Excel and demonstrate its potential in statistics and business modelling

Assessment

An assignment worth 25% and open book 3-hour exam worth 75%

Module Outline