1. Introduction to Modeling
MGS Business Analysis
Chapter 1
Introduction to Modeling
Copyright 2001
Prentice Hall

2. Model Definition

3. CLASSIFICATIONS OF MODELS
Decision making models are classified by the business function
they address or by the discipline or industry involved.
Classification
Examples
Business Function Finance, Marketing, Cost Accounting, Operations
Discipline Science, Engineering, Economics
Industry Military, Transportation, Telecommunications, Non-Profit
Time Frame One Time Period, Multiple Time Periods
Organizational Level Strategic, Tactical, Operational
Mathematics Linear Equations, Non-Linear Equations
Representation Spreadsheet, Custom Software, Paper and Pencil
Uncertainty Deterministic, Probabilistic

4. TYPES OF MODELS Type Physical Analog Symbolic The model is
What is being modeled
Examples
Physical
Tangible
Model airplane, building, etc.
Analog
Abstract
Speedometer
Thermometer
Painting
Symbolic
Either tangible or Abstract
Language
Mathematics

5. Models in Decision Making
Results
Analysis
Symbolic
World
Abstraction
Interpretation
Real
World
Management
Situation
Decisions
Intuition

6. The Modeling Process Objective Hierarchies Variables and Attributes
Describe Problem / opportunity
Identify Overall Objective
Organize Sub-Objectives into a hierarchy
Objective
Hierarchies
Variables
and Attributes
Identify Model’s Objective
Determine all variables and their attributes
Decide on Measurement / Data Collection
Influence
Diagrams
Graphically depict relationships among variables
Distinguish between Decision and outcome variables
Mathematical
Representation
Determine mathematical relationships among variables
Develop mathematical model(s)
Testing and
Validation
Evaluate reliability and validity
Understand limitations
Implement models in DSSs
Clarify assumptions, inputs, and outputs
Implementation
and use

7. Decision Making Simon’s Model of Decision Making Intelligence Design
Choice

8. Course Outline Introduction to Decision Support Models Forecasting
Basic Profit models, Simulation
Forecasting
Estimation of values that go into the profit models
Decision Analysis, Process Control
Choosing the right alternative after modeling
Monitoring a process after implementing decision