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FIT2017 Computer models for business decision making - Semester 1, 2015

The objective of this unit is to introduce students to the quantitative modelling techniques commonly used by executives in decision making and the application of IT tools to real-world decision making situations. Techniques covered typically include decision making under uncertainty, linear and nonlinear programming, sequential decision making, forecasting, and simulation. Upon the completion of this unit, the students are expected to recognise a complex decision making situation and to build a corresponding quantitative model. They are also expected to solve the model by applying techniques covered in this unit, to interpret results and finally, to provide analyst-type recommendations. The unit includes extensive use of advanced modelling tools available in Microsoft Excel as well as some VBA programming.

Mode of Delivery

Clayton (Day)

Workload Requirements

Minimum total expected workload equals 12 hours per week comprising:

(a.) Contact hours for on-campus students:

  • One 2-hour lecture
  • One 2-hour laboratory

(b.) Additional requirements (all students):

  • A minimum of 8 hours of independent study per week in order to satisfy the reading and assignment expectations.

See also Unit timetable information

Unit Relationships

Prohibitions

ETC2480, ETC3480, ETC4348, ETF2480, ETF9480, GCO2802, MAT1097, BUS1110

Prerequisites

FIT1006 or BUS1100 or ETC1000 or STA1010
Basic knowledge of MS Excel is assumed.

Chief Examiner

Campus Lecturer

Clayton

Mark Carman

Your feedback to Us

Monash is committed to excellence in education and regularly seeks feedback from students, employers and staff. One of the key formal ways students have to provide feedback is through the Student Evaluation of Teaching and Units (SETU) survey. The University’s student evaluation policy requires that every unit is evaluated each year. Students are strongly encouraged to complete the surveys. The feedback is anonymous and provides the Faculty with evidence of aspects that students are satisfied and areas for improvement.

For more information on Monash’s educational strategy, see:

www.monash.edu.au/about/monash-directions/ and on student evaluations, see: www.policy.monash.edu/policy-bank/academic/education/quality/student-evaluation-policy.html

Previous Student Evaluations of this Unit

Last year we trialled short, 15 minute, tests on a single topic during lectures. Students preferred this to a single, one hour test. We will retain the short tests this year. Students last year also indicated that they enjoyed more case-oriented problems. More of these will be incorporated into the course this year. We will also continue to develop the process of modelling as a pursuit in its own right.

If you wish to view how previous students rated this unit, please go to
https://emuapps.monash.edu.au/unitevaluations/index.jsp

Academic Overview

Learning Outcomes

On successful completion of this unit, students should be able to:
  • develop interactive decision models, using a variety of techniques;
  • interpret the results of mathematical decision models and conduct sensitivity analyses;
  • apply appropriate decision modelling techniques to real world problems;
  • critically assess the accuracy and applicability of modelling techniques;
  • communicate the results of model-based decision analysis;
  • design and implement spreadsheet-based mathematical programming techniques for optimisation;
  • design, construct and analyse simulation based models.

Unit Schedule

Week Activities Assessment
0   No formal assessment or activities are undertaken in week 0
1 Introduction to the course, The role of Management Science in business decision making, Introduction to modelling. Tutorial Participation assessed Weekly
2 Linear Programming - Modelling and solving problems by hand.  
3 Linear Programming - Solving problems using Excel.  
4 Linear programming - Sensitivity analysis and the interpretation of solutions. Test during lecture 1
5 Integer Linear Programming.  
6 Inventory Modelling.  
7 Decision making under uncertainty. Assignment 1 due 24 April 2015
8 Decision Trees. Decision making using sample information. Test during lecture 2
9 Queuing Theory.  
10 Simulation. Assignment 2 due 15 May 2015
11 Time Series Analysis and Forecasting. Test during lecture 3
12 Review and revision. Test during lecture 4
  SWOT VAC No formal assessment is undertaken in SWOT VAC
  Examination period LINK to Assessment Policy: http://policy.monash.edu.au/policy-bank/
academic/education/assessment/
assessment-in-coursework-policy.html

*Unit Schedule details will be maintained and communicated to you via your learning system.

Teaching Approach

Lecture and tutorials or problem classes
This teaching and learning approach provides facilitated learning, practical exploration and peer learning.

Assessment Summary

Examination (2 hours): 60%; In-semester assessment: 40%

Assessment Task Value Due Date
Assignment 1 15% 24 April 2015
Assignment 2 5% 15 May 2015
Tests during class 10% in total Weeks 4, 8, 11 and 12 during lecture
Tutorial Participation 10% Weekly (all tutorials)
Examination 1 60% To be advised

Assessment Requirements

Assessment Policy

Assessment Tasks

Participation

  • Assessment task 1
    Title:
    Assignment 1
    Description:
    Spreadsheet modelling using linear programming and integer linear programming.
    Weighting:
    15%
    Criteria for assessment:

    Criteria include:

    • Modelling and formulation
    • Interpretation
    • Presentation
    Due date:
    24 April 2015
  • Assessment task 2
    Title:
    Assignment 2
    Description:
    Decision Tree analysis using Excel and TreePlan
    Weighting:
    5%
    Criteria for assessment:

    Criteria include:

    • Modelling and formulation
    • Interpretation
    • Presentation
    Due date:
    15 May 2015
  • Assessment task 3
    Title:
    Tests during class
    Description:
    4 short tests will cover the material taught in weeks 1 - 12. These will be conducted during lectures 4, 8, 11 and 12, and will each be of approx 20 minutes duration.
    Weighting:
    10% in total
    Criteria for assessment:
    • Interpretation of question
    • Formulation of solution
    • Correctness of answer
    Due date:
    Weeks 4, 8, 11 and 12 during lecture
  • Assessment task 4
    Title:
    Tutorial Participation
    Description:
    Students are assessed on their participation in tutorials.
    Weighting:
    10%
    Criteria for assessment:
    • Participation in tutorials
    • Completion of class exercises
    • Contribution to class discussions
    Due date:
    Weekly (all tutorials)

Examinations

  • Examination 1
    Weighting:
    60%
    Length:
    2 hours
    Type (open/closed book):
    Closed book
    Electronic devices allowed in the exam:
    Calculators (including graphics calculators) may be used in tests and in the exam.

Learning resources

Reading list

Ragsdale C.T. Spreadsheet Modeling & Decision Analysis, 6th Edition, Thomson 2011, (Prescribed Textbook).

Anderson, D., Sweeney, D., Williams, T. Quantitative Methods for Business, 8th Edition (or latest edition), 2001, Thomson Learning. 

Lapin LL and Whisler WD, "Quantitative Decision Making with Spreadsheet Applications", 7th Edition, Duxbury Press, 2002

Winston WL, "Operations Research: Applications & Algorithms", 3rd Edition, Duxbury Press, 2004

Winston WL and Albright SC, "Practical Management Science: Spreadsheet Modelling and Applications" 3rd Edition, Duxbury Press, 1997

Monash Library Unit Reading List (if applicable to the unit)
http://readinglists.lib.monash.edu/index.html

Feedback to you

Types of feedback you can expect to receive in this unit are:

  • Informal feedback on progress in labs/tutes
  • Graded assignments without comments
  • Test results and feedback
  • Solutions to tutes, labs and assignments

Extensions and penalties

Returning assignments

Assignment submission

It is a University requirement (http://www.policy.monash.edu/policy-bank/academic/education/conduct/student-academic-integrity-managing-plagiarism-collusion-procedures.html) for students to submit an assignment coversheet for each assessment item. Faculty Assignment coversheets can be found at http://www.infotech.monash.edu.au/resources/student/forms/. Please check with your Lecturer on the submission method for your assignment coversheet (e.g. attach a file to the online assignment submission, hand-in a hard copy, or use an electronic submission). Please note that it is your responsibility to retain copies of your assessments.

Online submission

If Electronic Submission has been approved for your unit, please submit your work via the learning system for this unit, which you can access via links in the my.monash portal.

Required Resources

Please check with your lecturer before purchasing any Required Resources. Limited copies of prescribed texts are available for you to borrow in the library, and prescribed software is available in student labs.

Microsoft Office 2007.

Prescribed text(s)

Limited copies of prescribed texts are available for you to borrow in the library.

Ragsdale. (2011). Spreadsheet Modeling and Decision Analysis. (6th Edition) Thomson Learning.

Examination material or equipment

Calculators (including graphics calculators) may be used in tests and in the exam.

Other Information

Policies

Monash has educational policies, procedures and guidelines, which are designed to ensure that staff and students are aware of the University’s academic standards, and to provide advice on how they might uphold them. You can find Monash’s Education Policies at: www.policy.monash.edu.au/policy-bank/academic/education/index.html

Faculty resources and policies

Important student resources including Faculty policies are located at http://intranet.monash.edu.au/infotech/resources/students/

Graduate Attributes Policy

Student Charter

Student services

Monash University Library

Disability Liaison Unit

Students who have a disability or medical condition are welcome to contact the Disability Liaison Unit to discuss academic support services. Disability Liaison Officers (DLOs) visit all Victorian campuses on a regular basis.