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DECISION SUPPORT SYSTEMS



        Lecture 03


    Dr. Abdul Rauf Baig


                          Second Semester 2010-2011   1
Topic 02: Decision Making




                       Second Semester 2010-2011   2
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




                                            Second Semester 2010-2011   3
DECISION MAKING




Decision Making: Introduction




                         Second Semester 2010-2011   4
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.




                                          Second Semester 2010-2011   5
DECISION MAKING




Phases of Decision Making Process




                           Second Semester 2010-2011   6
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.

                                         Second Semester 2010-2011   7
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.




                                         Second Semester 2010-2011   8
DECISION MAKING: Intelligence Phase




        Decision Making Phases:
 Intelligence & Information Gathering




                             Second Semester 2010-2011   9
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



                                      Second Semester 2010-2011   10
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.


                                          Second Semester 2010-2011   11
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.



                                         Second Semester 2010-2011   12
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)

                                                    Second Semester 2010-2011     13
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


                                         Second Semester 2010-2011   14
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

                                           Second Semester 2010-2011   15
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.




                                         Second Semester 2010-2011   16
DECISION MAKING: Design Phase




       Decision Making:
        Design Phase




                          Second Semester 2010-2011   17
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




                                    Second Semester 2010-2011   18
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.




                                       Second Semester 2010-2011   19
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.


                                        Second Semester 2010-2011   20
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.




                                            Second Semester 2010-2011   21
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.




                                           Second Semester 2010-2011   22
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

                                          Second Semester 2010-2011   23
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)


                                         Second Semester 2010-2011   24
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




                                           Second Semester 2010-2011   25
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
                                        Second Semester 2010-2011   26
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.




                                          Second Semester 2010-2011   27
DECISION MAKING: Choice Phase




       Decision Making:
        Choice Phase




                          Second Semester 2010-2011   28
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
                                            Second Semester 2010-2011   29
DECISION MAKING: Implementation Phase




           Decision Making:
         Implementation Phase




                                Second Semester 2010-2011   30
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




                                        Second Semester 2010-2011   31
DECISION MAKING




Decision Making: How decisions are supported




                                Second Semester 2010-2011   32
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




                                          Second Semester 2010-2011   33
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)




                                          Second Semester 2010-2011   34
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




                                        Second Semester 2010-2011   35
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




                                   Second Semester 2010-2011   36
DECISION MAKING


Reference

Chapter 2:
      Sections 2.1 to 2.9 (except 2.3)




                                         Second Semester 2010-2011   37

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Lecture 03 decision making

  • 1. IS - 332 DECISION SUPPORT SYSTEMS Lecture 03 Dr. Abdul Rauf Baig Second Semester 2010-2011 1
  • 2. Topic 02: Decision Making Second Semester 2010-2011 2
  • 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 Second Semester 2010-2011 3
  • 4. DECISION MAKING Decision Making: Introduction Second Semester 2010-2011 4
  • 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. Second Semester 2010-2011 5
  • 6. DECISION MAKING Phases of Decision Making Process Second Semester 2010-2011 6
  • 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. Second Semester 2010-2011 7
  • 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. Second Semester 2010-2011 8
  • 9. DECISION MAKING: Intelligence Phase Decision Making Phases: Intelligence & Information Gathering Second Semester 2010-2011 9
  • 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 Second Semester 2010-2011 10
  • 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. Second Semester 2010-2011 11
  • 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. Second Semester 2010-2011 12
  • 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) Second Semester 2010-2011 13
  • 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 Second Semester 2010-2011 14
  • 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 Second Semester 2010-2011 15
  • 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. Second Semester 2010-2011 16
  • 17. DECISION MAKING: Design Phase Decision Making: Design Phase Second Semester 2010-2011 17
  • 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 Second Semester 2010-2011 18
  • 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. Second Semester 2010-2011 19
  • 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. Second Semester 2010-2011 20
  • 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. Second Semester 2010-2011 21
  • 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. Second Semester 2010-2011 22
  • 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 Second Semester 2010-2011 23
  • 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) Second Semester 2010-2011 24
  • 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 Second Semester 2010-2011 25
  • 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 Second Semester 2010-2011 26
  • 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. Second Semester 2010-2011 27
  • 28. DECISION MAKING: Choice Phase Decision Making: Choice Phase Second Semester 2010-2011 28
  • 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 Second Semester 2010-2011 29
  • 30. DECISION MAKING: Implementation Phase Decision Making: Implementation Phase Second Semester 2010-2011 30
  • 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 Second Semester 2010-2011 31
  • 32. DECISION MAKING Decision Making: How decisions are supported Second Semester 2010-2011 32
  • 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 Second Semester 2010-2011 33
  • 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) Second Semester 2010-2011 34
  • 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 Second Semester 2010-2011 35
  • 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 Second Semester 2010-2011 36
  • 37. DECISION MAKING Reference Chapter 2: Sections 2.1 to 2.9 (except 2.3) Second Semester 2010-2011 37