25841 Decision Making Tools

Subject level: Postgraduate

Handbook description

This subject strengthens students' ability to approach business-related problems by integrating methods and applications. Emphasis is placed on realistic business examples and the processes managers use to analyse business problems. The aim is to provide students with the skills to analyse business problems with tools they have access to and will use in their careers.

Subject objectives/outcomes

On successful completion of this subject students should be able to:

1. attain a general understanding of the management science approach to decision making
2. realise that quantitative applications begin with a problem situation
3. understand that managerial problem situations have both quantitative and qualitative considerations that are important in the decision-making process
4. learn about models in terms of what they are and why they are useful (the emphasis is on mathematical models)
5. identify the step-by-step procedure that is used in most quantitative approaches to decision making
6. obtain an introduction to the use of computer software packages such as Microsoft Excel for applying quantitative methods to decision making.

Contribution to graduate profile

The subject provides a unified approach to solving business-related problems by integrating methods and applications. Emphasis will be placed on realistic business examples and the processes managers use to analyse business problems. The aim is to develop skills to analyse business problems by employing the easily accessible tools managers will use in their careers.

Teaching and learning strategies

The subject uses lectures, workshop discussion, exercises and case studies to allow participants to build their understanding of the economics of the firm and their analytical capabilities in modelling managerial decisions. These methods will be supplemented with both printed and electronic learning materials and resources. The UTS web-based communication tool (UTSOnline) will be used to share information and encourage interaction between staff and students.

Content

• Introduction to modelling and spreadsheet modelling
• Introduction to spreadsheet optimisation, one of the most powerful and flexible methods of quantitative analysis. The specific type of optimisation discussed is linear programming, which is used in all types of businesses to solve a wide variety of problems from labour scheduling, inventory management and bond trading to hospital staffing
• Spreadsheets that focus on the applications of linear programming techniques and models
• Many important optimisation models, such as scheduling a fleet of aeroplanes, have a natural graphical network representation that is intuitive to users. Graphical representations aid spreadsheet model formulation and specialised solution techniques
• In many complex optimisation problems, the objective is a nonlinear function of the decision variables. Nonlinear programming examples include a variety of interesting applications on matters ranging from product pricing to portfolio optimisation to rating sports teams
• A formal framework for analysing decision problems that involve uncertainty is developed using a flexible graphical tool – the decision tree. Many examples of decision making under uncertainty exist in the business world, including closed tendering, introduction of new products and decisions with significant environmental consequences
• Simulation models will be used to generate a distribution of possible outcomes. Simulation allows the exploration of many possible scenarios and is helpful in understanding how sensitive a system is to changes in operating conditions
• Many decision-making applications depend on a forecast of some quantity. Of the many forecasting methods available the main quantitative tools are regression models and extrapolation methods. Forecasting methods are applied to realistic business scenarios

Assessment

Assessment item 1: Mid-semester Exam (Individual)

Assessment item 2: Case Study (Individual)

Assessment item 3: Final Examination (Individual)

Indicative references

Dowling, E.T., Mathematical Methods for Business and Economics, Shaums Ouline Series, McGraw-Hill, 1993.

Levine D.M., D.F. Stephan, T.C. Krehbiel, M.L. Berenson, Statistics for Managers Using Microsoft Excel, 5th Ed., Pearson Education 2008.

Albright, D.M., W.L. Winston W.L., C.J. Zappe, Data Analysis and Decision Making with Microsoft Excel, 3rd Ed., Thompson South-Western 2006.

Winston W.L., Microsoft Excel 2007 Data Analysis and Decision Making, Microsoft Press 2007.

Lecture overheads

These are available at UTSOnline. All lecture material, including data sets, will be posted to the subject website.

Other references

Faculty of Business (2006) Guide to Writing Assignments (available through UTSOnline or at www.business.uts.edu.au/resources/guide.html)