Subject Ante and Title:    INF 314    DECISION SUPPORT SYSTEMS

Prerequisite:             None

Course Description
The course introduces tools, techniques and design principles of developing and managing decision support systems. The course covers aspects of practical applications of decision support systems.

Subject Expected Learning Outcomes:
By the end of the course students should be able to: -

  1. Examine the concept of decision support systems (DSS) and the role of it in the context of enterprise information management to support the enterprise activities
  2. Apply appropriate IT tools in the development of DSS
  3. Use computational intelligence technologies such as expert systems, case-based reasoning, fuzzy logic, etc., in the design of DSS
  4. Design a DSS, and apply it to variable environment
  5. Apply suitable tools in designing and developing of DSS, and to recognise their limitations on the development

Course Contents:
Examines concerns of decision support in both non-automated and automated environments; Focus on structures, modeling, and the application of various decision support systems in today's corporate environment. Additional emphasis is placed on the use of executive information and expert system applications. Case studies examine applications of each of these types of technology.

Required Readings

  • Efraim Turban, et al. (1998).Decision Support Systems and Intelligent Systems, 5th edition, Prentice Hall,

Recommended Readings

  • Galliers R D. (1998).Information Technology and Organizational Transformation: Innovation for the 21stCentury Organization John Wiley & Son Ltd
  • Dhar,V. (1997). Intelligent Decision Support Methods: The Science of Knowledge Work, Prentice Hall,
  • Hossein Bidgoli, (1998).Intelligent Management Support Systems, Greenwood Publishing, Group; March,.



  1. Decision Supports Systems (DSS) are computer-based information systems designed in such a way that help
    managers to select one of the many alternative solutions to a problem.
  2. A DSS is an interactive computer based information system with an organized collection of models, people, procedures, software, databases, telecommunication, and devices, which helps decision makers to solve unstructured or semi-structured business problems.
  3. A Decision Support System (DSS) is an interactive, flexible, and adaptable computer based information system
    that utilizes decision rules, models, and model base coupled with a comprehensive database and the decision
    maker’s own insights, leading to specific, implementable decisions in solving problems that would not be
    amenable to management science models.

Characteristics of DSS

  1. Employed in semi-structured or unstructured decision contexts
  2. Intended to support decision makers rather than replace them
  3. Supports all phases of the decision-making process
  4. Focuses on effectiveness of the process rather than efficiency
  5. Is under control of the DSS user
  6. Uses underlying data and models
  7. Facilitates learning on the part of the decision maker
  8. Is interactive and user-friendly
  9. Is generally developed using an evolutionary, iterative process
  10. Can support multiple independent or interdependent decisions
  11. Supports individual, group or team-based decision-making

Capabilities of DSS

  1. Support for problem-solving phases including the intelligence, design, choice, implementation and
  2. Support for different decision frequencies that range from one-of-a-kind (i.e., merging with another
    company) to repetitive (i.e., how much inventory to purchase this week)
  3. One-of-a-kind decisions are handled by an ad hoc DSS
  4. Repetitive decisions are handled by institutional DSS
  5. Support for different problem structures ranging from high structured and programmed to unstructured
    and non-programmed
  6. Support for various decision-making levels including operational-level decisions, tactical-level
    decisions and strategic decisions

in other words

  1. The DSS is expected to extend the decision maker’s capacity to process information.
  2. The DSS solves the time-consuming portions of a problem, saving time for the user.
  3. Using the DSS can provide the user with alternatives that might go unnoticed.
  4. It is constrained, however, by the knowledge supplied to it.
  5. A DSS also has limited reasoning processes.
  6. Finally, a “universal DSS” does not exist.

Structured vs. Semi-Structured

For each decision you make, the decision will fall into one of the following categories:

  1. Structured Decisions
  2. Unstructured
  3. Semi-Structured

Structured Decisions is often called “programmed decisions” because they are routine and there are usually specific policies, procedures, or actions that can be identified to help make the decision. “This is how we usually solve this type of problem”

Unstructured Decisions - Decision scenarios that often involve new or unique problems and the individual has little or no programmatic or routine procedure for addressing the problem or making a decision


Components of Decision Support System

A DSS application can be composed of following subsystems:

  1. Data Management subsystem: The database management subsystem includes a database, which contains relevant data for the situation and is managed by software called the database management system (DBMS). The database management subsystem can be interconnected with the corporate data warehouse, a repository for corporate relevant decision-making data.
  2. Model Management subsystem: The model base gives decision makers access to a variety of models and assist them in decision making. The model base can include the model base management software (MBMS) that coordinates the use of models in a DSS. This component can be connected to external storage of data.
  3. Knowledge-based Management subsystem: This subsystem can support any of the other subsystem or act as an independent component. It provides intelligence to augment the decision maker’s own. It can be interconnected with the organization’s knowledge repository, which is called the organizational knowledge base.
  4. User Interface subsystem: The user interface, also called the dialog management facility, it allows users to
    interact with the DSS to obtain information. The user interface requires two capabilities; the action language that tells the DSS what is required and passes the data to the DSS and the presentation language that transfers and presents the user results. The DSS generator acts as a buffer between the user and the other DSS components,
    interacting with the database, the model base and the user interface

Decision Making and Problem Solving Process

A Problem occurs when a system does not meet its established goals or does not work as planned. Problem solving may also deal with identifying new opportunities. Problem solving is the most critical activity a business organization undertakes. Problem solving begins with decision making.

The Decision making process starts with the intelligence phase, where, potential problems and /or opportunities are identified and defined. In the design stage, alternative solutions to the problem are developed. In the choice stage, a course of action is selected. In the implementation stage, action is taken to put the solution into effect. In the monitoring stage, the implementation of the solution is evaluated to determine if the anticipated results were achieved and modify the process.

Design and Development of DSS







  1. What common characteristics of a decision support system relate to the decision-making process?
  2. Why is a DSS a powerful tool for decision makers?
  3. Is a "universal DSS" possible? Why or why not?
  4. Why is the concept of procedurality important to the design and implementation of a DSS?
  5. List and briefly describe the five basic components of a DSS.
  6. What is a database? What are the possible sources of data collected in a database? Why is the ability to combine data records from multiple sources so important to DSS users?
  7. What is a DBMS? Explain its two main responsibilities and how they contribute to the functionality of a DSS.
  8. What is a model? How can a model base support decision makers in the problem-solving process?
  9. Describe the two main responsibilities of the MBMS and the role of an MBMS in a decision support system.
  10. What is reasoning? Why is reasoning important to the decision-making process?
  11. What is a knowledge base? What is its role in a DSS?
  12. How does knowledge get into the DSS? How can it be retrieved and organized into useful information?
  13. What must be present in order for the user to be able to communicate well with the DSS?
  14. Explain the roles of the various types of users of a DSS.
  15. Compare the benefits and limitations of highly procedural languages and less or nonprocedural languages.
  16. List the major components of the decision-making process.
  17. In which portion of the decision-making process is a DSS most helpful for decision makers? Why?
  18. Define individual decision makers and describe the various traits that affect the way they make decisions.
  19. Specify the unique differences between decisions made in a group environment and a team environment.
  20. Identify the characteristics of decision makers at the organizational level. What is the special type of DSS developed for them?
  21. Describe the three forces that affect a particular individual's decision style.
  22. Why is the understanding of decision makers' decision styles important to the design and implementation of DSS?
  23. List and briefly describe the forces that can act on a problem context and on a decision maker during the course of making a decision.
  24. Briefly describe the classifications of decision styles based on the nature of problem context, cognitive complexity, and value orientation.
  25. How do personal and emotional forces act upon the decision process?
  26. How do organizational forces and constraints influence the decision process?
  27. What is the role of a DSS in relation to a decision maker?
  28. State the difficulties of decision making from the perspective of problem structure.
  29. Why is the understanding of a decision typology so important to the design of a DSS?
  30. Describe the activity-based typology of decisions. Give an example of each class.
  31. Briefly describe the components of Simon's problem-solving model.
  32. Is it possible to make an optimal decision? Why or why not?
  33. What is satisficing?
  34. Why is the concept of bounded rationality important to the decision process?
  35. What is the difference between a problem and a symptom?
  36. What is the impact of confusing a problem and a symptom during the decision-making process?
  37. What are the dangers associated with simplifying a decision context?
  38. Describe the effect of a decision maker's perception on the decision-making process.
  39. What is the effect of a decision maker's judgment on decision making?
  40. What are the benefits of using a heuristic search (heuristic programming) approach?
  41. Define heuristic bias.
  42. List and briefly describe the four most common heuristic biases.
  43. Compare and contrast the concepts of effectiveness and efficiency.


Define operational control, managerial control, and strategic planning. Provide two examples of each.

  1. Operational control is the efficient and effective execution of specific tasks. Examples: scheduling computer storage backups, planning next weeks’ company cafeteria menu.

  2. Management control is the acquisition and efficient use of resources to accomplish organizational goals. Examples: hiring a production coordinator, planning an advertising program.

  3. Strategic planning is defining long-range goals and policies for resource allocation. Examples: choosing which of three new products to develop, deciding whether or not to outsource customer telephone support to a region with lower labor costs than where it is now based.

How can computers provide support to semi-structured and unstructured decisions?

  1. Unstructured decisions can be only partially supported by standard computerized quantitative methods. Usually it is necessary to develop a customized solution. Intuition and judgment play a larger role in this type of decision than they do in making structured decisions. They may benefit from computerized communication and collaboration technologies and from knowledge management. Intelligent systems can also sometimes provide expertise that such solutions require.

  2. Making semistructured decisions may involve a combination of both standard solution procedures and human judgment. Management Science can provide models for the portion of the decision-making problem that is structured. For the unstructured portion, a DSS can improve the quality of the information on which the decision is based by providing, for example, not only a single solution but also a range of alternative solutions along with their potential impacts. These capabilities help managers to better understand the nature of problems and thus to make better decisions.

What are some of the drivers and benefits of computerized decision support?

  • Companies work in an unstable or rapidly changing economy.
  • There are difficulties in tracking the numerous business operations.
  • Competition has increased especially global competition.
  • Electronic commerce is changing the ways business is done.
  • Existing information systems do not fully support decision making.
  • The information systems department is too busy to address all of management’s inquiries.
  • Special analysis of profitability and efficiency is needed.
  • Accurate information is needed.
  • Computerized support is viewed as an organizational winner.
  • New information is needed.
  • Management mandates computerized decision support.
  • Higher decision quality is needed.


  • Improved communication
  • Improved customer and employee satisfaction is derived.
  • Timely information is provided.
  • Cost reduction is achieved.
  • Employees’ productivity has been improved.


DSS software