LOYOLA MARYMOUNT UNIVERSITY
SPRING 2007
MBAA 607: Operations Analysis & Decision Support Systems
Instructor: / Linda Leon, Hilton #209, 338-7634,Time: / Tuesday 4:25 – 7:05 pm
Office Hours: / Monday 11:00 – 1:00 pm
Tuesday 8:45 - 9:15 am, 2:45 – 4:15 pm
Thursday 8:00 - 9:15 am, 1:30 - 2:15 pm
Text: / Ragsdale, Spreadsheet Modeling and Decision Analysis, 5th edition, South-Western College Publishing, 2007.
Other Materials: / Blackboard account, flashdrive
Finals Week: / Tuesday, May 1st, 4:25 pm
Prerequisites: / MBAA603, sound knowledge of algebra, basic spreadsheet proficiency
Course Objectives
Upon completion of the course, the student should:
1. Understand how to model operations management and decision-making problems using quantitative management science techniques.
2. Understand various operations management and decision-making problems encountered in today's business world, including resource allocation, demand forecasting, inventory management, project management and queueing system analysis.
3. Have developed analytical and computer modeling skills necessary to implement and analyze decision problems.
4. Be able to integrate the information provided by the use of quantitative techniques and computer models into the decision-making process and be aware of the limitations of the quantitative technique used.
Course Description
This course is intended to help the potential manager discern the value of information provided by quantitative models in an organization. The emphasis will be on model formulation, the interpretation and modification of solutions, and the understanding of the mathematical versus verbal explanation of a situation. Some solution techniques will be introduced and the computer will be used in depth to solve and analyze problems. Cases and computer exercises will be assigned to complement the lecture material. Class time will be utilized to structure, analyze and discuss these exercises. Students are expected to attend class, read the assigned case materials beforehand, attempt the in-class computer exercises and homework, and participate in the class discussions.
Course Requirements
Three case projects will be assigned and graded. These projects will require each student to develop his/her own spreadsheet model. Students will submit a typed 1 to 2 page executive summary and supporting computer printouts or files. At least two weeks will be allowed for completion of the projects. Late projects and projects not meeting the required format will not be accepted.
Problems from the book and short computer exercises will also be assigned as homework for each course topic in order to reinforce the concepts, methods and techniques studied. These problems and exercises will not be graded and solutions will be provided on the course website the next lecture. Cases will be used as a basis for several small group class discussions and exercises throughout the semester. Most of these cases are identified on the syllabus course outline. Students are expected to prepare the cases before the class lecture period so that they can participate meaningfully in the discussions. The preparation work required for the BriLux case will be collected and graded to reflect your effort.
Flash snippits will also be posted as course documents in Blackboard. These optional snippits will provide support for many of the intermediate Excel concepts required in this class. The course outline identifies the topics where the different snippits will be relevant to the material being presented in class. If you miss class or if you are struggling with Excel, you should make sure that you review these snippits as they are assigned. Some of the snippits will be interactive, which can provide you with additional practice and support.
There will be two noncumulative exams (including the final) that will be based on the recommended homework problems, projects and class lectures and discussions. All exams are closed book, closed notes and will require use of the laptop to complete. The final course grade will be distributed as follows:
ASSIGNMENT / WEIGHTProject 1: Linear Programming / 12%
Midterm / 30%
BriLux Case Preparation / 4%
Project 2: Waiting Line Simulation / 12%
Project 3: Forecasting / 12%
Final / 30%
TOTAL / 100%
All assignments will be graded on the scale 0-100. The point scores will then be combined according to the above weights at the end of the course and a letter grade will be assigned on the final total score according to the following guidelines:
FINAL TOTAL POINTS / GRADE90 - 100 / A
80 - 89 / B
70 - 79 / C
60 - 69 / D
Below 60 / F
NOTES:
1. Pluses and minuses for the letter grade are given based on the class curve for the final total points.
2. Files containing class handouts and spreadsheet examples will be distributed to the class through the web page http://myweb.lmu.edu//lleon/mbaa607/. Students will also be required to use Blackboard at http://lmu.edu/bb7 to submit files for their project assignments, access snippits for Excel support, and view grades.
3. No make-up examinations will be offered. If you are excused from an exam due to a documented medical situation or a pre-scheduled business trip, the weights used to determine the final grade will be adjusted. Otherwise, the exam will have a score of 0.
4. Additional readings besides those listed in the course outline will be assigned as necessary. The scheduled course outline may also be adjusted as necessary.
5. In accordance with the University’s academic honesty and integrity regulations, no cheating of any kind will be tolerated with regard to any work in the course. Cheating on any part of the coursework will result in a score of 0 for the corresponding work.
COURSE OUTLINE
Text and Excel support
1 / 1/9 / Introduction to CourseOverview of Operations Analysis & Management Science; Optimization of a Spreadsheet Model Using Solver; Resource Allocation LP Models / Chpt. 1, 3.0-3.8
Excel functions and Solver snippits
2 / 1/16 / Linear Programming
Formulation & Graphical Solutions of LP;
Spreadsheet-based LP Models: Transportation and Scheduling Applications / Chpt. 2, 3.10
Solver snippits
3 / 1/23 / Case 3.1 Discussion
Multi-period LP Model Applications;
Sensitivity Analysis of LP Solutions
Discussion of Project 1 (LP) / Chpt.3.12, 4
Solver Sensitivity Analysis snippits
4 / 1/30 / Forecasting
Time Series Analysis & Decomposition,
Stationary Models, Seasonal Indices, Crystal Ball Predictor / Chpt. 11.0-11.9, 11.21
Graphing snippits
5 / 2/6 / Regression Models;
Time Series with Trend Components; Case 11.2 and 11.3 Discussion
* PROJECT 1 DUE * / Chpt. 9.0-9.9, 9.11-9.14, 11.15-11.17
Regression snippits
6 / 2/13 / Discussion of Project 2 (Forecasting)
Decision Theory
Decision-making under risk / Chpt.15.0-15.9
7 / 2/20 / Decision Trees with Treeplan;
Freemark Winery Case Discussion;
Data Tables / Chpt.15.10-15.12
Treeplan and Data Table snippits
8 / 2/27 / * MIDTERM EXAMINATION *
3/6 / * Spring Break *
Week / Date / Topic /
Text & Excel Support
9 / 3/13 / Case Analysis: BriLux and The Fot-320 decision* PROJECT 2 DUE *
F / 3/16 / ** LAST DAY TO WITHDRAW **
10 / 3/20 / Simulation
Monte Carlo Simulation, Random Number Generators (RNGs);
Yield Management Application / Chpt. 12.0-12.3
Vlookup & simulation snippits
11 / 3/27 / Computer Simulation with Crystal Ball;
Case 12.4 Discussion; / Chpt. 12.5-12.10, 12.14
Crystal Ball snippits
12 / 4/3 / Inventory Management Models;
Greaves Brewery Case Discussion / Chpt. 8.4, 12.15
13 / 4/10 / Waiting Line Models
Discussion of Project 3 (Simulation) / Chpt. 13.0-13.5, 13.11
14 / 4/17 / Project Management
Network Construction, Critical Path Analysis;
Case 14.2 and 14.3 Discussion / Chpt. 14.0-14.8
15 / 4/24 / Case 14.1 Discussion
Uncertain Activity Times: PERT, Simulation Models
Microsoft Project
* PROJECT 3 DUE *
Summary of Course / Chpt. 14.9-14. 13