Decision Support System

1. Introduction
Electronic communication technologies are arguably the strongest driver of change in the last decade of the millennium. [Giarini, 1998]

Giarini [1998] also state that there are seven new different information and communication technology that has the potential to play a significant role in changing and shaping the international system. Those are fibre optics, computers, improved human-computer interaction, digital transmission and digital compression, communications satellites, cellular technologies, and networking. In application, these technologies are well-known in different forms. For instance, the largest application of networking is the Internet.

Marakas [2003] states that we face decisions every day. As managers, we establish our worth with our organizations by being able to cope with decisions such as whether to invest in an emerging technology that could create significant competitive advantage for the firm, or how we can best deploy the limited human resources available for a given project, or what mix of products is best for the current and future market conditions. In other words, the really important decisions are often difficult to make and require both a great deal of information and an increased level of decision support, which brings us to what this paper is all about: making and supporting managerial decisions with decision support system.

2. Decision Support Systems Definition

Decision is a choice made between alternative courses of action in a situation of uncertainty. Although too much uncertainty is undesirable, manageable uncertainty provides the freedom to make creative decisions. [Business Dictionary, 2009]

Decision making can be regarded as an outcome of mental processes (cognitive process) leading to the selection of a course of action among several alternatives. Every decision making process produces a final choice. The output can be an action or an opinion of choice. [Wikipedia, 2009]
A decision support system is a way to model data and make quality decisions based upon it. Making the right decision in business is usually based on the quality of your data and your ability to sift through and analyse the data to find trends in which you can create solutions and strategies for. DSS or decision support systems are usually computer applications along with a human component that can sift through large amounts of data and pick between the many choices. [Tech FAQ, 2009]

Decision Support Systems (DSS) are a specific class of computerized information systems that supports business and organizational decision-making activities. A properly-designed DSS is an interactive software-based system intended to help decision makers compile useful information from raw data, documents, personal knowledge, and/or business models to identify and solve problems and make decisions.[Wikipwdia, 2009]

Decision support systems are interactive, computer-based systems that aid users in judgment and choice activities. [Druzdzel and Flynn, 2002] They provide data storage and retrieval but enhance the traditional information access and retrieval functions with support for model building and model-based reasoning. They support framing, modeling, and problem solving. Typical application areas of DSSs are management and planning in business, health care, the military, and any area in which management will encounter complex decision situations. Decision support systems are typically used for strategic and tactical decisions faced by upper-level management decisions with a reasonably low frequency and high potential consequences in which the time taken for thinking through and modeling the problem pays generously in the long run.

A decision support system is a sys¬tem under the control of one or more decision makers that assists in the activity of deci¬sion making by providing an organized set of tools intended to impose structure on portions of the decision-making situation and to improve the ultimate effectiveness of the decision outcome. [Marakas2003]

3. Characterizations and Goals

Talking about Decision Support System, we must first discuss about 3 major themes. Those are:

1. Problem structure.
This dimension focuses on the degree to which a decision or decision-making situation displays certain structural characteristics. The role of the DSS is to provide support to the decision maker on the "structure-able" portions of the decision. With this support, the decision maker is free to focus his or her cognitive resources on the truly unstructured portions of the problem. The decision processes employed in addressing the unstructured portions of a decision situation can be thought of as the human processes we do not yet understand well enough to effectively simulate via automation.

2. Decision outcome
A key element of a tech¬nology that is intended to support the process associated with making a decision is the decision itself.. The effectiveness of a given decision, or the degree to which the decision succeeds in reaching its objectives, is an essential element in the decision-making process.

3. Managerial control
The ultimate responsibility for the outcomes associated with decisions lies with the man¬ager. The decision acts as the primary mechanism to reach the organization's strategic objectives and to fuel its successes. The control of this final selection lies with the decision maker(s). To that end, the DSS must provide support to the selection process but, ultimately, must be positioned to allow the final selection to be made by those managers directly responsible and accountable for the outcomes.

Based on these three major themes, we can conclude common DSS characterization. Those are:
• Employed in semi structured or unstructured decision contexts
• Intended to support decision makers rather than replace them
• Supports all phases of the decision-making process
• Focuses on the effectiveness of the decision-making process rather than its efficiency
• Is under control of the DSS user
• Uses underlying data and models
• Facilitates learning on the part of the decision maker
• Is interactive and user-friendly
• Is generally developed using an evolutionary, iterative process
• Provides support for all levels of management from top executives to line managers
• Can provide support for multiple independent or interdependent decisions
• Provides support for individual, group, and team-based decision-making contexts
According to Ari [2005] the goals of DSS have a strong related with those DSS’s characterization. Those are:
• To help manager or decision maker in making a decision with semi-structural problem
• To support manager’s decision instead to change or replace that decision
• To help manager or decision maker to make the decision process more effec¬tive

Table 1 Management Activity [Marakas, 2003]


4. Benefits and Limitations

The DSS clearly offers management a powerful tool and is rapidly becoming an inte¬gral component of managerial work.

To meet the demands of managerial work, a DSS must be able to provide the decision maker with certain key elements vital to his or her success. A DSS cannot offer benefits in all decision situations or by all decision makers, however. Its effectiveness depends on the degree of fit between the decision maker, the context of the decision, and the DSS itself.

DSS is expected to extend the decision maker's capacity in pro¬cessing the mountain of information involved in making a decision. Further, many components of a decision situation although structured, are nonetheless highly complex and time-consuming. The DSS can solve those portions of the problem, and save on cognitive resources and, more importantly, large blocks of precious time for the decision maker. As a result, using a DSS can be expected to decrease the overall time involved in reaching a complex, unstructured decision.
Additional benefits can be found in the areas of innovation and creativity. Simply using the DSS can provide the decision maker with potential alternatives that might otherwise go unnoticed or appear too complex and difficult to pursue. Finally, given the shrinking window of opportunity associated with the pace of business, the DSS may provide competitive advantage to organizations. To achieve some or all of these potential benefits, however, the manager must understand not only the appropriate application of a particular decision support tool but also its limits.

No matter how well a DSS is designed, its value is constrained by certain limita-tions.
Other drawbacks of the DSS include limits on its ability to perform reasoning processes that require distinctly human characteristics such as creativity, intuition, or imagination. Such cognitive activities still belong to human experience and do not lend themselves well to automation or machine simulation.

Further, the DSS must be designed to communicate its information to its user in an understandable manner that is useful within the context of the decision situation. Although humans can adapt their methods of communication readily to a given situation, computer systems such as DSSs cannot.

Finally is the understanding that a "universal DSS" does not exist and probably never will. A typical DSS is designed to be useful within a relatively narrow scope of problem-solving scenarios. Thus, to effectively solve a com¬plex problem or reach a decision of significant magnitude may require the use of sev¬eral DSSs. In that case, the decision maker must coordinate multiple systems that may require output from one as input to another.
In brief, decision support systems can make the decision process more effec¬tive for the human decision maker. They cannot, however, overcome or prevent the actions of a poor decision maker. The user ultimately controls the process and must understand when to use a DSS, what DSS(s) to use, and, most importantly, to what degree to depend on the output and information obtained from the DSS. The manager must see the DSS as a valuable tool in the decision process rather than as a mechanism that makes the decision.

From above discussion we can conclude about several common DSS’s benefits and limitation. Those are:

a. Benefits
• Extend the decision maker's ability to process information and knowledge
• Extend the decision maker's ability to tackle large-scale, time-consuming, complex problems
• Shorten the time associated with making a decision
• Improve the reliability of a decision process or outcome
• Encourage exploration and discovery on the part of the decision maker
• Reveal new approaches to thinking about a problem space or decision context
• Generate new evidence in support of a decision or confirmation of existing assumptions
• Create a strategic or competitive advantage over competing organizations

b. Limitations
• DSSs cannot yet be designed to contain distinctly human decision-making talents such as creativity, imagination, or intuition
• The power of a DSS is limited by the computer system upon which it is running, its design, and the knowledge it possesses at the time of its use
• Language and command interfaces are not yet sophisticated enough to allow for natural language processing of user directives and inquiries

5. Decision Support System’s Component

There are three fundamental components of DSSs

1. Database management system (DBMS).

A DBMS serves as a data bank for the DSS. It stores large quantities of data that are relevant to the class of problems for which the DSS has been designed and provides logical data structures (as opposed to the physical data structures) with which the users interact. A DBMS separates the users from the physical aspects of the database structure and processing. It should also be capable of informing the user of the types of data that are available and how to gain access to them.


General function of DBMS are:
a. Data Definition
• Provides a data definition language (DDL) that allows users to describe the data entities and their associated attributes and relationships
• Allows for the interrelation of data from multiple sources
b. Data Manipulation
• Provides the user with a query language to interact with the database
• Allows for capture and extraction of data
• Provides rapid retrieval of data for ad hoc queries and reports
• Allows for the construction of complex queries for retrieval and data manipulation
c. Data Integrity
• Allows the user to describe rules (integrity constraints) to maintain the integrity of the database
• Assists in the control of erroneous data entry based on the defined integrity constraints
d. Access Control
• Allows identification of authorized users
• Controls access to various data elements and data manipulation activities within the database
• Tracks usage and access to data by authorized users Concurrency Control
• Provides procedures for controlling simultaneous access to the same data by more than one user
e. Transaction Recovery
• Provides a mechanism for restart and reconciliation of the database in the event of hard-ware failure
• Records information on all transactions at certain points to enable satisfactory database restart

2. Model-base management system (MBMS).

The role of MBMS is analogous to that of a DBMS. Its primary function is providing independence between septic models that are used in a DSS from the applications that use them.
The purpose of an MBMS is to transform data from the DBMS into information that is useful in decision making. Since many problems that the user of a DSS will cope with may be unstructured, the MBMS should also be capable of assisting the user in model building.
General functions of MBMS are
a. Modeling Language
• Allows for the creation of decision models from scratch or from existing modules
• Provides a mechanism for the linking or chaining of multiple models to allow for sequential processing and data exchange
• Allows the user to modify models to reflect specific preferences
b. Model Library
• Stores and manages all models and solver algorithms for easy access and manipulation
• Provides a catalog and organizational schema of stored models along with brief descrip-tions of their individual functions or applications
c. Model Manipulation
• Allows for management and maintenance of the model base with functions similar to those found in a DBMS (i.e., run, store, query, delete, link, etc.)

3. Dialog generation and management system (DGMS).

The main product of an interaction with a DSS is insight. As their users are often managers who are not computer-trained, DSS need to be equipped with intuitive and easy-to-use interfaces. These interfaces aid in model building, but also in interaction with the model, such as gaining insight and recommendations from it. The primary responsibility of a DGMS is to enhance the ability of the system user to utilize and benefit from the DSS.

Figure 1 DSS Component [Druzdzel and Flynn, 2002]

6. Example of Decision Support System

Assume that there is a simple knowledge base that contains a select number of variables deemed by experts to be most important in evaluating a potential bor¬rower's creditworthiness.
1. Number of years of credit history (a numerical fact)
2. Quality of the credit history (a ranking fact: perfect, almost perfect, very good, good, not good, awful)
3. Number of years of employment in this job area (a numerical fact)
4. Total income of the borrower (a numerical fact)
5. Total debt obligations of the borrower (a numerical fact)
6. Amount of money the borrower wants to borrow (a numerical fact)
In addition to these facts, knowledge base also contains the relationships among them. In other words, we have also stored the manner in which one or more facts are related to each other. In this case, the objective is to make a decision regarding whether we should lend money to a specific person
Figure 2 graphically illustrates the relationships between the facts contained within our knowledge base.

Figure 2 [Marakas, 2003]

7. Conclusion

Decision support systems are interactive, computer-based systems that aid users in judgment and choice activities. [Druzdzel and Flynn, 2002]
The DSS is a decision support system, not a decision making system. DSS only assist the decision maker on how to make a decision [NEIWPCC, 2005]
The DSS assists users in evaluating appropriate rankings for differing types of studies (i.e., datasets). It does not provide the data rankings, but helps regulators and scientists develop their own quantitative rankings for different datasets based upon their understanding of the research process and perceptions (biases) regarding which attributes of the data are most valuable for regulatory decision-making. [NEIWPCC, 2005]
Finally is the understanding that a "universal DSS" does not exist and probably never will [Marakas, 200]

Referances
Business Dictionary. 2009. [online : accessed on May 5 2009] URL: http://www.businessdictionary.com/definition/decision.html
Druzdel M., J., and Flynn R., R.2002. Decission Support System. [online: accessed on May 6 2009] URL: http://www.pitt.edu/~druzdzel/psfiles/dss.pdf
Giarini, J., 1998. How Electronic Communication Thechnologies Change The Way People Communicate and Collaborate. Diktat Kuliah 2008.
Marakas, G., M. 2003. Decission Support Systems in the 21st Century. Pearson International Edition.
NEIWPCC, 2005. Decision Support System (Tutorial). [online : accessed on May 5 2009] URL : http://www.ndwrcdp.org/userfiles/DSS%20Tutorial.pdf
Tech FAQ, 2009. What is Decision Support System?. [online, accessed May 7 2009] URL: http://www.tech-faq.com/decision-support-system.shtml
Wikipedia, 2009. Decision support system .[online: accessed on May 10 2009] URL: http://en.wikipedia.org/wiki/Decision_support_systems