A decision support system is a form of a management information system (MIS). Other MIS methods include transaction processing systems and operations information systems. Management information systems are computer programs that provide the management in any organization with information essential for effective running of the organization, for example, an MIS can be designed to improve communication among staff and to provide a platform for recording information regarding the organization’s revenue and expenditure.
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Decision support systems (DSS), similar to other MISs, are computer programs that aid managers in their day-to-day decision making processes without requiring the presence of computer experts. A DSS has three major elements:
- Database management system (DBMS) that stocks huge volumes of data that is vital in finding solutions to problems for which the DSS has been designed to solve;
- Model-based management systems (MBMS) that processes data received from the DBMS in information that is vital for decision-making;
- Dialog generation and management system (DGMS) that gives an easy-to-use interface between the system and the managers who lack a broad knowledge of computer-based applications (Turban & Liang, 2008, pp. 574).
A Brief History of DSS
DSS has developed from two core areas of study: the theoretical study of decision-making undertaken at the Carnegie Institute of Tech. during the late 1950s, and the scientific research on interactive computer systems largely done at Massachusetts Institute of Technology (Keen, 1978, pp. 10) in the late 1960s.
Research and study of DSS gained momentum in the mid-1970s, it was during this time that scientists began to identify a part that computer-based information systems (CBIS) could be of assistance to managers in their decision making processes.
Since then, DSS became a major area of study and in the 1980s, several DSS systems emerged from a sole user and model-oriented DSS, these included the group decision support systems (GDSS) and executive information systems (EIS). EIS is a important tool for firm executives as it provides real-time and vital information that has been processed for tracking and managerial purposes.
In the early 1990s, data warehousing and on-line analytical processing (OLAP) started widening the scope of DSS and by the turn of the millennium, new web-based DSS programs were launched. Technological advancements have seen the DSS emerge as an important constituent of the management sector. The introduction of new and better tools has seen the DSS to form an integral element of management design.
Decision Support Systems
DSSs transform data in such a way that they become useful and quality decisions can be made from them. Coming up with the right decisions usually depends on the quality of data fed into the DSS and the user’s ability to filter the data and identify trends to which one can find solutions. Generally, DSS are simply computer applications along with a human interface that can sort out, process large amounts of data, and carry out the required analyses (Druzdel, 2002, pp. 6).
A majority of people think that DSSs are a specific division of an organization, however, a majority of companies have incorporated this systems into their daily routines, for example, a number of firms frequently download and study income and revenue data, projected growth, and budget sheets, and they refresh their plans once the analysis of the current results is complete. DSSs have a solid position in firms, yet the data and decisions they are founded on are ever changing.
The main function of DSSs is to collect data, analyze, identify trends in the collected data, and then create strategic decisions or plans from the analyses. Whether computers, databases or persons participate in the process is usually not important, however, it is this procedure of taking unstructured records, collecting it, and after analysis, using it to assist in decision-making.
DSS can be categorized in to several models, the number of categories vary from one person to another. For example, we can have two categories when we consider the extent of data processing: passive and inactive, passive DSS only collects and analyzes data while an active DSS goes a step further and processes it. Another categorization system that considers the mode of assistance gives rise to five categories:
- A Model driven DSS is when managers use statistical, replication, or financial models as a basis of their decisions;
- A Communication driven DSS is when a number of people work together in coming up with a solution or plan;
- A Document driven DSS utilizes documents in a number of data type to make decisions and strategic plans;
- A Knowledge driven DSS provides specifically designed rules in a computer to come up with a decision; and
- A data driven DSS focuses on collected data that is then operated on to correspond the manager’s needs (Topbits, 2010, para. 8).
Advantages of DSS
There are several advantage that are associated with DSSs, especially in comparison with earlier methods of making decisions. These are outlined below:
- DSSs enhance personal efficiency- when data is collected and analyzed using scientific DSS methods, there is a drastic reduction of errors collectively known as human errors. After the data is analyzed, managers are able to make informed decisions based on the findings of the DSS procedure;
- DSSs hasten the pace of problem solving in an organization since the processes are done by automated systems. After installing the appropriate scientific formulas in the computer, the rest of the procedure is taken over by the computer and the analytic process is swift. Besides, the DSS system filters the data for easier management and hence shortens the duration between data collection and decision-making.
- DSSs enhance information tracking since the analysis process is systematic and each stage can be tracked easily. Care should be taken during the data collection process, and when feeding it into the computer.
- Other merits of decision support systems include: enhancing interpersonal communication, reveals new fronts of handling organizational needs; and increases the competitive advantage of a firm.
- Reduced “user friendliness”. Although DSSs have been simplified in the recent years, it still remains a hurdle for some companies, especially those that do not have the resources required to implement it. There are costs incurred during the installation stage and staff training, small companies that cannot meet the costs have to resort to traditional methods of making decisions.
- Hard to quantify. Another problem in using decision support systems stems from the fact that if decision makers do not how to combine the output, the whole process will be in vain. Most decision support systems give outputs that are mathematical in nature, and they require mathematical calculations to find out the type of decision to be made.
- Finding solutions to model inadequacies. Another problem that comes with the use of DSSs is that the manager/user may not fully understand the inadequacies/ limitations of the DSS model under use. There may be instances where the user knows the knowledge that is required, but not the way to retrieve that knowledge. This problem is common in statistical analysis of data. The majority of statistical packages have a number of tests to be carried out on data irrespective of whether it is suitable or not.
Effectiveness of the system
A number of new tools and technologies are currently being developed to be added on to the DSS platform, these changes will reshape decision-making in organizations (Eom, 2001, pp. 11). New tools include hardware and computer software, artificial intelligence systems, data mining, OLAP, and internet analysis gadgets.
In short, the future of decision support systems is bright. Any company or organization that does not embrace DSS methods and practices will have no place in the future as a majority of companies will have adopted DSSs. Such companies will lack a competitive advantage and will only watch as rivals register huge growth margins. However, we do not have to base growth on future innovations since the competition has already began.
Adoption of DSS methods has a couple of benefits as earlier discussed. A firm’s expenses are reduced when it implements DSS methods, for example, fewer staff is required since most of the computerized systems will do most of the work. Besides, the analyses will be carried out in real-time and enable the manager to make even the most urgent decisions. Looking back at the advantages and disadvantages of the system, the decision to adopt a decision support system was a positive one.
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Druzdel, M. J. (2002). Decision Support Systems. Encyclopedia of Library and Information Science. New York: Marcel Dekker, Inc
Eom, S. B. (2001). Decision Support Systems. International Encyclopedia of Business and Management. London: International Thomson Business Publishing.
Keen, P. G. W. (1978). Decision support systems: an organizational perspective. Reading: Addison-Wesley Pub. Co
TopBits. (2010). Decision support system. Retrieved from http://www.tech-faq.com/decision-support-system.html
Turban, E., Aronson, J. E., and Liang, T. (2008). Decision Support Systems and Intelligent Systems. California: Pearson/Prentice hall