1. DECISION MAKING, SYSTEMS, MODELING, AND SUPPORT
Chapter 2
DECISION MAKING, SYSTEMS, MODELING, AND SUPPORT
8th Edition
2nd semester 2010 Dr. Qusai Abuein

2. 2nd semester 2010 Dr. Qusai Abuein
Learning Objectives
Understand the conceptual foundations of decision making
Understand Simon’s four phases of decision making: intelligence, design, choice, and implementation
Recognize the concepts of rationality and bounded rationality, and how they relate to decision making
2nd semester 2010 Dr. Qusai Abuein

3. 2nd semester 2010 Dr. Qusai Abuein
Learning Objectives
Differentiate between the concepts of making a choice and establishing a principle of choice
Learn how DSS support for decision making can be provided in practice
Understand the systems approach
2nd semester 2010 Dr. Qusai Abuein

4. 2nd semester 2010 Dr. Qusai Abuein
(2.1) Opening Vignette
Illustrates how does Greenspan (the U.S federal Reserve chairman) decided to raise or lower interest rate.
He used statistical analysis to data collected from different systems, his 25 years experience, real-time information and knowledge systems.
2nd semester 2010 Dr. Qusai Abuein

5. (2.2) Decision Making: Introduction and Definitions
Knowing:
How decision making is practiced,
Theories and models of decision making,
Traits of decision makers
Help in understanding the types of decision support tools that managers can use to make more effective decisions.
2nd semester 2010 Dr. Qusai Abuein

6. (2.2) Decision Making: Introduction and Definitions
Characteristics of decision making
Groupthink
Decision makers are interested in evaluating what-if scenarios
Experimentation with the real system may result in failure
Experimentation with the real system is possible only for one set of conditions at a time and can be disastrous
Changes in the decision making environment may occur continuously, leading to invalidating assumptions about the situation
2nd semester 2010 Dr. Qusai Abuein

7. (2.2) Decision Making: Introduction and Definitions
To determine how real decision makers make decisions, we :
Must understand the process of decision making
Understand appropriate methodologies for assisting decision makers
Contributions IS can make
Only then can we develop DSS to help decision makers.
2nd semester 2010 Dr. Qusai Abuein

8. (2.2) Decision Making: Introduction and Definitions
A decision is selection the best alternative from two or more solutions. (as defined in ch1)
Decision making:
The action of selecting among alternatives
Planning involves a series of decisions: What should be done? When? Where? Why? How? By whom?
Managers set goals or plan
Planning implies decision making
2nd semester 2010 Dr. Qusai Abuein

9. (2.2) Decision Making: Introduction and Definitions
Decision making and problem solving
A problem occurs when:
A system does not meet its goals
Does not yield the predicted results, or
Does not work as planned
Problem solving may deal with identifying new opportunities.
Q) How to differentiate between problem solving and decision making?
By examining the phases of decision process.
2nd semester 2010 Dr. Qusai Abuein

10. (2.2) Decision Making: Introduction and Definitions
Phases of the decision process
Intelligence
Design
Choice
Problem solving
A process in which one starts from an initial state and proceeds to search through a problem space to identify a desired goal. It includes the 4th phase of the decision process
Implementation
Some consider the phases (1-4) as problem solving, with the choice phase as the real decision-making process.
Others, consider phases (1-3) as the formal decision-making, with the implementation phase as the problem solving
2nd semester 2010 Dr. Qusai Abuein

11. (2.2) Decision Making: Introduction and Definitions
In this book problem solving is used interchangeably with decision making.
2nd semester 2010 Dr. Qusai Abuein

12. (2.2) Decision Making: Introduction and Definitions
Decision making disciplines are:
Behavioral
Scientific
What constitutes a successful decision in practice?
Effectiveness
The degree of goal attainment. Doing the right things
Efficiency
The ratio of output to input. Appropriate use of resources. Doing the things right
Effectiveness is the concern of MSS (Management Support Sys.)
Efficiency is the concern of TPS (Transaction Support System)
2nd semester 2010 Dr. Qusai Abuein

13. (2.2) Decision Making: Introduction and Definitions
Decision style and decision makers
Decision style
The manner in which a decision maker thinks and reacts to problems. It includes perceptions, cognitive responses, values, and beliefs.
Decision styles are:
Autocratic
Democratic
Consultative
2nd semester 2010 Dr. Qusai Abuein

14. (2.2) Decision Making: Introduction and Definitions
Decision style and decision makers
Different decision styles require different types of support
Individual decision makers need access to data and to experts who can provide advice
Groups need collaboration tools
In small organizations, decisions are often made by individuals at lower managerial level.
In medium and large organizations, decisions are made by groups.
2nd semester 2010 Dr. Qusai Abuein

15. 2nd semester 2010 Dr. Qusai Abuein
(2.3) Models
The basic idea is to perform the DSS analysis on a model of reality rather than on real system.
A model is a simplified representation of reality.
Models are classified into:
Iconic model
A scaled physical replica, such as an airplane model (3D)
Analog model
An abstract, symbolic model of a system that behaves like the system but looks different, such as charts and figure represents water on mountains. (2D)
2nd semester 2010 Dr. Qusai Abuein

16. 2nd semester 2010 Dr. Qusai Abuein
(2.3) Models
Mental model
The mechanisms or images through which a human mind performs sense-making in decision making
Mathematical (quantitative) model
A system of symbols and expressions that represent a real situation
2nd semester 2010 Dr. Qusai Abuein

17. 2nd semester 2010 Dr. Qusai Abuein
(2.3) Models
The benefits of models
MMS uses models for the following reasons:
Model manipulation is much easier than manipulating a real system
Models enable the compression of time (simulation)
The cost of modeling analysis is much lower
The cost of making mistakes during a trial-and-error experiment is much lower when models are used than with real systems
2nd semester 2010 Dr. Qusai Abuein

18. 2nd semester 2010 Dr. Qusai Abuein
(2.3) Models
The benefits of models
With modeling, a manager can estimate the risks resulting from specific actions within the uncertainty of the business environment
Mathematical models enable the analysis of a very large number of possible solutions
Models enhance and reinforce learning and training
Models and solution methods are readily available on the Web
Many Java applets are available to readily solve models
2nd semester 2010 Dr. Qusai Abuein

19. (2.4) Phases of the Decision-Making Process
2nd semester 2010 Dr. Qusai Abuein

20. (2.4) Phases of the Decision-Making Process
It advisable to follow a systematic decision-making process:
Intelligence phase
The initial phase of problem definition in decision making
Design phase
The second decision-making phase, which involves constructing a model and finding possible alternatives in decision making and assessing their contributions
2nd semester 2010 Dr. Qusai Abuein

21. (2.4) Phases of the Decision-Making Process
Choice phase
The third phase in decision making, in which an alternative is selected
Implementation phase
The fourth decision-making phase, involving actually putting a recommended solution to work
2nd semester 2010 Dr. Qusai Abuein

22. (2.5) Decision Making: The Intelligence Phase
It includes problem (or opportunity) identification. Some issues that may arise during data collection:
Data are not available
Obtaining data may be expensive
Data may not be accurate or precise enough
Data estimation is often subjective
Data may be insecure
Important data that influence the results may be qualitative
2nd semester 2010 Dr. Qusai Abuein

23. (2.5) Decision Making: The Intelligence Phase
Some issues that may arise during data collection
Information overload (too many data)
Outcomes (or results) may occur over an extended period
If future data is not consistent with historical data, the nature of the change has to be predicted and included in the analysis
2nd semester 2010 Dr. Qusai Abuein

24. (2.5) Decision Making: The Intelligence Phase
Problem classification
The conceptualization of a problem in an attempt to place it in a definable category, possibly leading to a standard solution approach
Problem decomposition
Dividing complex problems into simpler subproblems may help in solving the complex ones
Problem ownership
Is the process of assigning authority to solve a problem
2nd semester 2010 Dr. Qusai Abuein

25. (2.6) Decision Making: The Design Phase
The design phase involves finding or developing and analyzing possible courses of action. These include:
Understanding the problem
Testing solutions for feasibility
A model of the decision-making problem is constructed, tested, and validated
2nd semester 2010 Dr. Qusai Abuein

26. (2.6) Decision Making: The Design Phase
Modeling involves conceptualizing a problem and abstracting it to quantitative and/or qualitative form
Models have:
Decision variables
Principle of choice
2nd semester 2010 Dr. Qusai Abuein

27. (2.6) Decision Making: The Design Phase
Decision variables
A variable in a model that can be changed and manipulated by the decision maker. Decision variables correspond to the decisions to be made, such as quantity to produce, amounts of resources to allocate, and so on
Principle of choice
The criterion that describes the acceptability of a solution approach.
Q) What is the difference between Criterion and constraint? (See technology insight 2.1 page 59)
2nd semester 2010 Dr. Qusai Abuein

28. (2.6) Decision Making: The Design Phase
Among the many principles of choice, normative and descriptive are important.
Normative models
Models in which the chosen alternative is demonstrably (proven to be) the best of all possible alternatives
Optimization
The process of examining all the alternatives and proving that the one selected is the best
Suboptimization
An optimization-based procedure that does not consider all the alternatives for or impacts on an organization because a decision made in one area may affect other areas. (details P61,62 are important)
2nd semester 2010 Dr. Qusai Abuein

29. (2.6) Decision Making: The Design Phase
Descriptive model
A model that describes things as they are. These models are typically mathematically based.
Simulation
Is an imitation of reality and the most common descriptive modeling method.
Narrative is another descriptive decision-making model, it is a story that helps a decision maker uncover the important aspects of the situation and leads to better understanding and framing
2nd semester 2010 Dr. Qusai Abuein

30. (2.6) Decision Making: The Design Phase
Good enough or satisficing
Satisficing
A process by which one seeks a solution that will satisfy a set of constraints. In contrast to optimization, which seeks the best possible solution, satisficing simply seeks a solution that will work well enough up to a predetermined level of performance.
Q) Why accepting satisficing solution?
Due to time pressure (timely decision)
The ability to achieve optimization
Marginal benefit of a better decision does not worth the marginal cost to obtain it
2nd semester 2010 Dr. Qusai Abuein

31. (2.6) Decision Making: The Design Phase
Good enough or satisficing
Satisficing is a form of suboptimization.
There may be a best solution (optimum), but it would be difficult (impossible) to attain:
With a normative model: too much computation may be involved
With descriptive model: it may not be possible to evaluate all alternatives
Q) Since rationality and the use of normative models lead to good decisions, why are so many bad decisions made in practice? H.W.
2nd semester 2010 Dr. Qusai Abuein

32. (2.6) Decision Making: The Design Phase
Developing (generating) alternatives
In optimization models (linear programming) the alternatives may be generated automatically by the model
In most MSS situations it is necessary to generate alternatives manually (a lengthy, costly process); issues such as when to stop generating alternatives are very important
The search for alternatives usually occurs after the criteria for evaluating the alternatives are determined (this way it is easy to find alternatives)
The outcome of every proposed alternative must be established
2nd semester 2010 Dr. Qusai Abuein

33. (2.6) Decision Making: The Design Phase
Measuring outcomes
The value of an alternative is evaluated in terms of goal attainment
Ex.(1):
Goal Profit maximization
Outcome  Profit
Ex.(2):
Goal Customer Satisfaction maximization
Outcome  Customer Satisfaction
Q) What is an AHP? H.W.
Measured by JD
Measured by # of complaints, level of loyalty to product, or surveys
2nd semester 2010 Dr. Qusai Abuein

34. (2.6) Decision Making: The Design Phase
Risk
One important task of a decision maker is to attribute a level of risk to the outcome associated with each potential alternative being considered
Decisions that lead to unacceptable risks in terms of success are discarded.
Risk is an important issue when developing BI/DSS
2nd semester 2010 Dr. Qusai Abuein

35. (2.6) Decision Making: The Design Phase
Scenario
Is a statement of assumptions about the operating environment of a particular system at a given time; that is, it is a narrative description of the decision-situation setting
Scenarios are especially helpful in simulations and what-if analyses
In simulation and what-if analysis, scenarios are changes and results are examined
2nd semester 2010 Dr. Qusai Abuein

36. (2.6) Decision Making: The Design Phase
Scenarios play an important role in MSS because they:
Help identify opportunities and problem areas
Provide flexibility in planning
Identify the leading edges of changes that management should monitor
Help validate major modeling assumptions
Allow the decision maker to explore the behavior of a system through a model
Help to check the sensitivity of proposed solutions to changes in the environment
2nd semester 2010 Dr. Qusai Abuein

37. (2.6) Decision Making: The Design Phase
Possible scenarios
The worst possible scenario
The best possible scenario
The most likely scenario
The average scenario
Scenario determines the context of analysis to be performed.
2nd semester 2010 Dr. Qusai Abuein

38. (2.6) Decision Making: The Design Phase
Errors in decision making
The model is a critical component in the decision-making process
A decision maker may make a number of errors in its development and use
Validating the model before it is used is critical
Gathering the right amount of information, with the right level of precision and accuracy is also critical
2nd semester 2010 Dr. Qusai Abuein

39. (2.7) Decision Making: The Choice Phase
The choice phase is the one in which the actual decision is made and involves following appropriate course of action
Q) Why boundary between design and choice phases are not clear? H.W.
The choice phase includes the search for, evaluation of, and recommendation of an appropriate solution to a model.
Solving a model is not as solving the problem the model represents.
Solution to a model is considered a recommended solution to a problem.
When the recommended solution is successful, then the problem is solved.
2nd semester 2010 Dr. Qusai Abuein

40. (2.7) Decision Making: The Choice Phase
Solving a model involves searching for appropriate course of action. Searching approaches include:
Analytical techniques (solving a formula)
Algorithms (step-by-step procedures)
Heuristics (rules of thumb)
Blind searches
2nd semester 2010 Dr. Qusai Abuein

41. (2.7) Decision Making: The Choice Phase
Analytical techniques
Methods that use mathematical formulas to derive an optimal solution directly or to predict a certain result, mainly in solving structured problems
Algorithm
A step-by-step search in which improvement is made at every step until the best solution is found
2nd semester 2010 Dr. Qusai Abuein

42. (2.7) Decision Making: The Choice Phase
Heuristics
Informal, judgmental knowledge of an application area that constitutes the rules of good judgment in the field. Heuristics also encompasses the knowledge of how to solve problems efficiently and effectively, how to plan steps in solving a complex problem, how to improve performance, and so forth
2nd semester 2010 Dr. Qusai Abuein

43. (2.7) Decision Making: The Choice Phase
Sensitivity analysis
A study of the effect of a change in one or more input variables on a proposed solution
What-if analysis
A process that involves asking a computer what the effect of changing some of the input data or parameters would be
2nd semester 2010 Dr. Qusai Abuein

44. (2.8) Decision Making: The Implementation Phase
The implementation to a proposed solution is the introduction of change.
Change which includes user expectation must be managed.
Implementation phase involves putting a recommended solution to work.
Generic implementation issues important in dealing with MSS include:
Resistance to change
Degree of support of top management
User training
2nd semester 2010 Dr. Qusai Abuein

45. (2.9) How Decisions Are Supported
The decision making process (Figure 2.2 next slide) can be improved with computer support.
Specific MSS technologies to decision making process include:
Database
Data warehouse
2nd semester 2010 Dr. Qusai Abuein

46. (2.9) How Decisions Are Supported
2nd semester 2010 Dr. Qusai Abuein

47. (2.9) How Decisions Are Supported
Support for the intelligence phase
The ability to scan external and internal information sources for opportunities and problems and to interpret what the scanning discovers
Web tools and sources are extremely useful for environmental scanning
Web browsers provide useful front ends for a variety of tools (OLAP, data mining, data warehouses)
Internal data sources may be accessible via a corporate intranet
External sources are many and varied
2nd semester 2010 Dr. Qusai Abuein

48. (2.9) How Decisions Are Supported
Support for the design phase
The generation of alternatives for complex problems requires expertise that can be provided only by a human, brainstorming software, or an ES
2nd semester 2010 Dr. Qusai Abuein

49. (2.9) How Decisions Are Supported
Support for the choice phase
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
KMS helps identify similar past experiences
CRM, ERP, and SCM systems are used to test the impacts of decisions in establishing their value, leading to an intelligent choice
An ES can be used to assess the desirability of certain solutions and to recommend an appropriate solution
A GSS can provide support to lead to consensus in a group
2nd semester 2010 Dr. Qusai Abuein

50. (2.9) How Decisions Are Supported
Support for the implementation phase
DSS can be used in implementation activities such as decision communication, explanation, and justification.
DSS benefits are partly due to the vividness and detail of analyses and reports.
Decision implementation can also be supported by ES.
ES can be used as an advisory system and provide training that may smooth the implementation.
2nd semester 2010 Dr. Qusai Abuein

51. (2.9) How Decisions Are Supported
New technology support for decision making
Web-based systems have clearly influenced how decision making is supported
Mobile commerce (m-commerce)
Personal devices
Personal digital assistants [PDAs]
Cell phones
Tablet computers
laptop computers
Advanced AI can be utilized in decision making.
2nd semester 2010 Dr. Qusai Abuein

52. 2nd semester 2010 Dr. Qusai Abuein
End Of Chapter 2
Thank you
2nd semester 2010 Dr. Qusai Abuein