The document discusses decision making and decision support systems. It covers 4 phases of the decision making process: intelligence/information gathering, design, choice, and implementation. In the intelligence phase, problems are identified and classified. The design phase involves developing models of possible solutions. The choice phase selects the best solution according to principles of choice like optimization. The last phase is implementation of the chosen solution.

1. IS - 332
DECISION SUPPORT SYSTEMS
Lecture 03
Dr. Abdul Rauf Baig
Second Semester 2010-2011 1

2. Topic 02: Decision Making
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3. DECISION MAKING
Summary of previous lectures:
1. From databases to DSS
2. Computerized support for decision making: its benefits
3. Framework for computerized decision support
4. Framework for business intelligence
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4. DECISION MAKING
Decision Making: Introduction
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5. DECISION MAKING
What is decision making?
Decision making is a process of choosing among two or more
alternate courses of action for the purpose of attaining a goal
(or goals)
Managerial decision making is a complex task in today’s
business environment.
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6. DECISION MAKING
Phases of Decision Making Process
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7. DECISION MAKING: Four Phases
Decision Making Phases
Systematic decision making involves three major phases
followed by the implementation phase:
• Intelligence or Information gathering,
• Design,
• Choice,
• Implementation
Decision making process starts with the intelligence or
information gathering phase, where reality is examined and
the problem is identified.
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8. DECISION MAKING: Four Phases
Decision Making Phases
In the design phase, a model that represents the system is
constructed.
The choice phase includes selection of a proposed solution to
the model.
Once the proposed solution seems to be reasonable, we are
ready for the last phase: implementation.
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9. DECISION MAKING: Intelligence Phase
Decision Making Phases:
Intelligence & Information Gathering
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10. DECISION MAKING: Intelligence Phase
Decision Making: Intelligence Phase
Intelligence or information gathering includes several
activities aimed at identifying problem situations or
opportunities.
1. Problem or opportunity identification
2. Problem classification
3. Programmed versus non-programmed problems
4. Problem decomposition
5. Problem ownership
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11. DECISION MAKING: Intelligence Phase
Decision Making: Intelligence Phase
Problem or Opportunity Identification:
The intelligence or information gathering phase begins with
the identification of organizational goals and objectives
related to an issue of concern (e.g. inventory management,
job selection).
Problems occur because of dissatisfaction with the status
quo. Dissatisfaction is the result of a difference between what
we desire (or expect) and what is occurring.
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12. DECISION MAKING: Intelligence Phase
Decision Making: Intelligence Phase
Problem or Opportunity Identification:
In the first phase, one attempts to determine whether a
problem exists, identify its symptoms, determine its
magnitude, and explicitly define it.
The existence of a problem can be determined by monitoring
and analyzing the organization’s productivity level. This is
based on real data.
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13. DECISION MAKING: Intelligence Phase
Decision Making: Intelligence Phase
Problem or Opportunity Identification:
Some issues that may arise during data collection and
estimation are:
- Data may not be available - Outcomes or results may occur
- Obtaining data may be expensive over an extended period of time. As
- Data may not be accurate or precise a result, revenues, expenses, and
- Data estimation is often subjective profits will be recorded at different
- Important data that influence the points in time.
results may be qualitative - It is assumed that future data will
- There may be too much data be similar to historic data.
(information overload)
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14. DECISION MAKING: Intelligence Phase
Decision Making: Intelligence Phase
Problem Classification:
Problem classification is the placement of a problem in a
definable category.
This leads to a standard solution approach.
An important classification is according to the degree of
structuredness evident in the problem. This ranges from
totally structured to totally unstructured
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15. DECISION MAKING: Intelligence Phase
Decision Making: Intelligence Phase
Problem Decomposition:
Many complex problems can be divided into sub-problems.
Solving the simpler sub-problems may help in solving the
complex problem.
Some unstructured problems may have some highly
structure sub-problems
Decomposition also facilitates communication among
decision makers
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16. DECISION MAKING: Intelligence Phase
Decision Making: Intelligence Phase
Problem Ownership:
A problem exists in an organization only if someone or some
groups takes on the responsibility of attacking it and if the
organization has the ability to solve it.
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17. DECISION MAKING: Design Phase
Decision Making:
Design Phase
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18. DECISION MAKING: Design Phase
Decision Making: Design Phase
The design phase involves finding (or developing) and
analyzing possible courses of action.
These include understanding the problem and testing
solutions for feasibility.
A model of the decision making problem is constructed,
tested, and validated
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19. DECISION MAKING: Design Phase
Decision Making: Design Phase
Modelling involves abstracting the problem to quantitative
and/or qualitative forms.
For a mathematical model, the variables are identified and
the relationships among them are established.
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20. DECISION MAKING: Design Phase
Decision Making: Design Phase
Components of Quantitative Models:
All models are made up of three basic components: decision
variables, uncontrollable variables, and result (outcome)
variables
Mathematical relationships link these components together
In a non-quantitative model, the relationships are symbolic
or qualitative.
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21. DECISION MAKING: Design Phase
Decision Making: Design Phase
Components of Quantitative Models: Result Variables
Result variables are outputs.
They reflect the level of effectiveness of the system.
These are dependent variables.
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22. DECISION MAKING: Design Phase
Decision Making: Design Phase
Components of Quantitative Models: Decision Variables
Decision variables describe alternative courses of action.
Example: For an investment problem, the amount to invest
in bonds is a decision variable.
In a scheduling problem, the decision variables are people,
times, and schedules.
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23. DECISION MAKING: Design Phase
Decision Making: Design Phase
Components of Quantitative Models: Uncontrollable Variables
In any decision making situation, there are factors that affect
the result variables but are not under the control of the
decision maker.
Either these factors are fixed (called parameters) or they can
vary.
Examples: Prime interest rate, a city’s building code, tax
regulations
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24. DECISION MAKING: Design Phase
Decision Making: Design Phase
Components of Quantitative Models: Intermediate Results
Variables
Intermediate result variables reflect intermediate outcomes.
Example: Employee’s salaries is a decision variable,
It determines employee’s satisfaction
(intermediate variable),
which determines productivity level (final
outcome)
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25. DECISION MAKING: Design Phase
Decision Making: Design Phase
Structure of Quantitative Models:
The components (i.e. decision variables, result variables, etc.)
of a quantitative model are linked together by mathematical
expressions.
Example: Profit = Revenue - Cost
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26. DECISION MAKING: Design Phase
Decision Making: Design Phase
Selection of a Principle of Choice:
A principle of choice is a criterion that describes the
acceptability of a solution approach.
Two types: normative and descriptive
Normative models: Normative implies that the chosen
alternative is demonstrably the best of all possible
alternatives. To find it, one should examine al alternatives
and prove that the one selected is indeed the best. The
process is basically optimization
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27. DECISION MAKING: Design Phase
Decision Making: Design Phase
Selection of a Principle of Choice:
Descriptive models: They investigate alternate courses of
action under different configurations of inputs and processes.
Al the alternatives are not checked, only a given set of
alternatives are checked.
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28. DECISION MAKING: Choice Phase
Decision Making:
Choice Phase
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29. DECISION MAKING: Choice Phase
Decision Making: Choice Phase
Choice is the critical act of decision making.
The choice phase is the one in which the actual decision is
made and where the commitment to follow a certain course
of action is made.
The choice phase includes search for, evaluation of, and
recommendation of an appropriate solution to the model
(problem).
The boundary between the design and choice phases is often
unclear
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30. DECISION MAKING: Implementation Phase
Decision Making:
Implementation Phase
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31. DECISION MAKING: Implementation Phase
Decision Making: Implementation Phase
Implementation means putting a recommended solution to
work.
It does not stop at implementing a computer system. There
are many issues involved, such as user expectations,
resistance to change, and user training
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32. DECISION MAKING
Decision Making: How decisions are supported
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33. DECISION MAKING: How decisions are supported
Support for Intelligence Phase
The primary requirement of decision support for the
intelligence phase is the ability to scan external and internal
information sources for opportunities and problems and to
interpret what the scanning discovers
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34. DECISION MAKING: How decisions are supported
Support for Design Phase
The design phase involves generating alternate courses of
actions, discussing the criteria for choices and their relative
importance, and forecasting the future consequences of using
various alternatives
Several of these activities can use standard models provided
by a DSS (e.g. financial and forecasting models)
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35. DECISION MAKING: How decisions are supported
Support for Choice Phase
In addition to providing models that rapidly identify a best
or good-enough alternative, a DSS can support the choice
phase through what-if and goal seeking analyses
Different scenarios can be tested for the selected option to
reinforce the final decision
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36. DECISION MAKING: How decisions are supported
Support for Implementation Phase
The DSS benefits implementation phase through the
vividness and detail of analyses and reports
This improves the communication, explanation, and
justification of decisions
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37. DECISION MAKING
Reference
Chapter 2:
Sections 2.1 to 2.9 (except 2.3)
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