1. Chapter 8 Models and Decision Support
Decision Support System:
DSS is an interactive IT system that creates new information on demand to help you make nonstructural decisions.

2. Components of Decision Support System (p.295)
Model Base
User
User Interface
Question
Answer
Choice of Models
Results
Database
Information

3. Why do we use models? (p.290)
Understand process
Optimization
Prediction
Simulation
Problems when using models
Complexity of model
Cost of model
Error of model

4. Popular Decision Support Models:
Prediction: regression model, other statistical model.
What-If analysis: simulation
Optimization models: Optimization models seek the best solution where decision need to be made in a constrained or limited resource environment. An optimization model has its objective function, decision variables and constraints.
Heuristic methods: A heuristic* is a practical and quick method based on intuitive and plausible arguments that likely to (but not guaranteed to) lead to a solution that is approximately optimal or near optimal.
* K. G. Murty, 1995, “Operations Research”.

5. Why many managers still seem to prefer heuristic method?
There are no optimization algorithms to find the optimum solutions to many large scale problems in real business world within acceptable computer time.
Because of errors in the data, an optimal solution can only be a good solution for the real problem and serves the same purpose as a good but simple heuristic.

6. Optimum solution: projects 2, 5, and 7. Profit = 351.
Example: Optimum solution and a good solution by heuristic. Capacity is 35 hours.
Optimum solution: projects 2, 5, and 7. Profit = 351.
Greedy heuristic: projects 7, 5, and 1. Profit = 348.
Project
Hours
Profit
Profit/Hour 1 3 21 7 2 4 24 6 12
168 8 5 15
135 9 13 26 16
192 20
200 10 40
800
Eliminate

7. Data Mining
A collection of data analysis techniques for extremely large dataset.
Properly applied, data mining can reveal hidden relationships and information buried within the data warehouse..
* G. M. Marakas, 2003, “Modern Data Warehousing, Mining, and Visualization”.

8. The purpose to use EIS Advantages of EIS
Display transaction data in a form of overall picture.
Provide easy access to corporate data for executives.
Advantages of EIS
Top executive can retrieve data without waiting for report.
Data of all functional areas are retrieved from the same system – a better big picture.
Drill down to get more detailed data.
Comparison of time series and cross-sectional data.
The data is nonintrusive (a copy of the transaction data).