INTRODUCTION TO MODELING
Modeling Approach to Decision Making:
Involves spreadsheet based
management models
Uses spreadsheet software such as Excel®
This approach is easy for managers to use,
Results in better management decisions,
Provides important insights into problem.
THE MODELING PROCESS
Managerial Approach to Decision Making
Manager analyzes
situation (alternatives)
Makes decision to
resolve conflict
Decisions are
implemented
Consequences
of decision
These steps
Use
Spreadsheet
Modeling
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Operations Research / Management Science
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Origin: Military services early in World War 2.
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Urgent need to allocate scarce resources to the various military operations and to the activities within
war operation in an effective manner
Research teams called upon to apply a scientific approach to this and other strategic and tactical
problems
This scientific approach is transferred and, and is used extensively in the industrial part of business,
as well as in a lot of other areas such as government, engineering, economics, natural and social
sciences
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Definition.
The use of modern science, with a special weight on numerical techniques, on complex problems
concerning management of people, machines, raw materials and money, in business, industry, the
public sector and military services. The goal of OR is to help the management to make strategical and
tactical decisions on a more scientific basis.

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Mathematical programming

Roughly speaking, the part of OR that focuses primarily on deterministic problems where probability
theory is not needed
Approach: to construct a mathematical model to represent the problem of interest, identifying
decisions to be made and constraints on the decisions. An algorithm is then used to solve for an
optimal solution
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Why learn Management Science?
•
You will learn different techniques that may give public
organizations and private firms and farms a more solid foundation
for decision-making

You will develop your modeling skills in general --> developing
your abilities for logical thinking

You will sharpen your quantitative skills
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You will develop your intuition by studying many different types of
models
THE MODELING PROCESS
as applied to the first two stages of decision making.
Real
World
Management
Situation
Results
Interpretation
Symbolic
World
Abstraction
Model
Analysis
Intuition
Decisions
THE MODELING PROCESS
The Role of Managerial Judgment in the Modeling Process:
Analysis
Real
World
Management
Situation
Results
Managerial
Judgment
Interpretation
Symbolic
World
Abstraction
Model
Decisions
Intuition
THE MODELING PROCESS
Decision Support Models force you to
1. be explicit about your objectives.
2. identify and record the types of decisions that influence
3.
4.
5.
6.
7.
those objectives.
identify and record interactions and trade-offs among
those decisions.
think carefully about which variables to include.
consider what data are pertinent and their interactions.
recognize constraints or limitations on the values.
Models allow communication of your ideas and
understanding to facilitate teamwork.
Models allow us to use the analytical power of spreadsheets hand in
hand with the data storage and computational speed of computers.
MORE ON MODELS
A model is a carefully selected abstraction of reality.
Symbolic models
1. always simplify reality.
2. incorporate enough detail so that
• the result meets your needs,
• it is consistent with the data you have available,
• it can be quickly analyzed.
Decision models are symbolic models in which some of the
variables represent decisions that must or could be made.
Decision variables are variables whose values you can
control, change or set.
MORE ON DECISION MODELS
Decision models typically include an explicit performance
measure that gauges the attainment of that objective.
For example, the objective may be to maximize profit
or minimize cost in relation to a performance measure
(such as sales revenue, interest income, etc).
In summary, decision models
1. selectively describe the managerial situation.
2. designate decision variables.
3. designate performance measure(s) that reflect
objective(s).
BUILDING MODELS
To model a situation, you first have to frame it (i.e.,
develop an organized way of thinking about the situation).
A problem statement involves possible decisions and a
method for measuring their effectiveness.
Steps in modeling:
1. Study the Environment to Frame the Managerial Situation
2. Formulate a selective representation
3. Construct a symbolic (quantitative) model
BUILDING MODELS
1. Studying the Environment
Select those aspects of reality relevant to the situation
at hand.
2. Formulation
Specific assumptions and simplifications are made.
Decisions and objectives must be explicitly identified and
defined.
Identify the model’s major conceptual ingredients using
“Black Box” approach.
BUILDING MODELS
The “Black Box” View of a Model
Decisions
(Controllable)
Parameters
(Uncontrollable)
Model
Performance
Measure(s)
Consequence
Variables
BUILDING MODELS
3. Model Construction
The next step is to construct a symbolic model.
Var. Y
Mathematical relationships are developed. Graphing the
variables may help define the relationship.
Var. X
To do this, use “Modeling with Data” technique.
MODELING WITH DATA
Consider the following data.
Graphs are created to view any relationship(s) between the variables.
This is the first step in formulating the equations in the model.
DETERMINISTIC AND
PROBABILISTIC MODELS
Deterministic Models
are models in which all relevant data are assumed to be known
with certainty.
can handle complex situations with many decisions and constraints.
are very useful when there are few uncontrolled model inputs
that are uncertain.
are useful for a variety of management problems.
are easy to incorporate constraints on variables.
software is available to optimize constrained models.
allows for managerial interpretation of results.
constrained optimization provides useful way to frame situations.
will help develop your ability to formulate models in general.
MODELING AND REAL
WORLD DECISION MAKING
Four Stages of applying modeling to real world
decision making:
Stage 1: Study the environment, formulate the model
and construct the model.
Stage 2: Analyze the model to generate results.
Stage 3: Interpret and validate model results.
Stage 4: Implement validated knowledge.
MODELING AND REAL
WORLD DECISION MAKING
Management
Modeling Term
Lingo
Formal Definition
Example
Decision Variable
Lever
Controllable Exogenous
Input Quantity
Parameter
Gauge
Uncontrollable Exogenous Interest Rate
Input Quantity
Consequence
Variable
Outcome
Performance
Measure
Yardstick
Endogenous Output
Variable
Endogenous Variable
Used for Evaluation
(Objective Function Value)
Investment
Amount
Commissions
Paid
Return on
Investment