Transcript Chapter 1: Introduction to Managerial Decision Modeling

Chapter 1:
Introduction to Managerial
Decision Modeling
© 2007 Pearson Education
What is Decision Modeling?
A scientific approach to managerial
decision making
• The development of a (mathematical) model
of a real-world scenario
• The model provides insight into the solution of
the managerial problem
Types of Decision Models
• Deterministic Models
Where all the input data value are known with
complete certainty
• Probabilistic Models
Where some input data values are uncertain
Quantitative vs. Qualitative Data
The modeling process begins with data
• Quantitative Data
Numerical factors such as costs and revenues
• Qualitative Data
Factors that effect the environment which are
difficult to quantify
Spreadsheets in Decision Making
• Computers are used to create and solve
models
• Spreadsheets are a convenient alternative
to specialized software
• Microsoft Excel has extensive modeling
capability via the use “add-ins”
Steps in Decision Modeling
1. Formulation
Translating a problem scenario from
words to a mathematical model
2. Solution
Solving the model to obtain the optimal
solution
3. Interpretation and Sensitivity Analysis
Analyzing results and implementing a
solution
Steps in
Modeling
Example Model: Tax Computation
Self employed couple must estimate and
pay quarterly income tax (joint return)
• Income amount is uncertain
• 5% of income to retirement account, up to
$4000 max
• Personal exemption = 2 x $3200 = $6400
• Standard deduction = $10,000
• No other deductions
Tax Brackets
Taxable Income
up to $14,600
$14,601 to $59,400
$59,401 to $119,950
Percent of
Taxable Income
10%
15%
25%
Example Model: Break-Even Analysis
Profit = Revenue – Costs
Revenue = (Selling price) x (Num. units)
Costs = (Fixed cost) +
(Cost per unit) x (Num. units)
The Break Even Point (BEP) is the
number of units where;
Profit = 0, so
Revenue = Costs
BEP
=
Fixed cost
(Selling price) – (Cost per unit)
Possible Problems in
Developing Decision Models
Defining the Problem
• Conflicting viewpoints
• Impact on other departments
• Beginning assumptions
• Solution outdated
Possible Problems in
Developing Decision Models
Developing a Model
• Fitting the textbook models
• Understanding the model
Acquiring Input Data
• Using accounting data
• Validity of data
Possible Problems in
Developing Decision Models
Developing a Solution
• Hard to understand mathematics
• Limitations of only one answer
Testing the Solution
Analyzing the Results
Implementation