Decision Support System Its Characteristics And Components

IT Trends & Technology / By ashish/ July 13, 2019 July 21, 2022 / 5 minutes of reading What is Decision Support System
Decision Support System are information processing systems frequently used by accountants, managers and auditors to assist them for decision-making purposes. The concept of DSS was developed in 1960’s, after studying decision making several in organizations. These studies noted that managers require flexible systems which can respond to adhoc questions. Advances in hardware technology, interactive computing design, graphics capabilities and programming languages contributed to this development. Today Decision Support Systems are widely used in accounting and auditing.

Characteristic features of Decision Support System
1. DSS supports management decision making: Generally these systems are used by top management for decision making purposes (For example, to decide whether to drop a product line or not, to increase the advertisement expenditure or not). These are also used by operational managers for management planning decisions (For example, to solve scheduling problems). DSS enhances (=increases) the quality of decisions. The system will recommend a particular alternative and the final decision is taken by the user.
2. Decision support systems solve unstructured problems: Problems that do not have easy solutions and problems in which some managerial judgment is necessary are called unstructured problems and such problems can be easily solved by DSS. Generally decision support systems use non-routine data as input. It is difficult to collect such data and sometimes it may require estimates. An important characteristic of many decision support systems is that they allow users to ask what-if questions and to examine the results of these questions.
3. Friendly computer interface: Generally Decision support systems are operated by managers and other decision makers, who are non programmers. So these systems must be easy to use. With the help of non procedural languages, users can easily communicate with the decision support system.

Components of Decision Support Systems
1. Users: Usually, the user of a DSS is a manager with some unstructured or semi-structured problem. The manager may be at any level of authority in the organization (e.g. either top level or middle level or bottom level managers). Generally, users do not need computer knowledge to use a decision support system.
2. Databases: Decision support systems include one or more databases. These databases contain both routine and non-routine data from both internal and external sources. The data from external sources include data about operating environment – for example, data about economic conditions, market demand for the organizations goods or services and industry competition.
DSS users may construct additional databases. Some data may come from internal sources. An organization generates this type of data in the normal course of operations – for example, data from financial and managerial accounting systems. The database may also capture data from other subsystems such as marketing, production and personnel. External data include assumptions about variables such as interest rates, market prices and level of competition. . Planning languages: Two types of planning languages that are commonly used in decision support systems are: (1) general purpose planning language and (2) special purpose planning language.
4. Model base: The model base is the “brain” of the decision support system because it processes data with the help of data provided by the user and the database. There are many types of model bases, but most of them are custom developed models that do some type of mathematical functions – for example, regression analysis, time series analysis, linear programming and financial computations. The analysis provided by model base is the key for user’s decision.

Some Examples of Decision Support System
Decision support systems are widely used as part of an organizations AIS. Many DSS’s are developed in-house, to solve specific problems. Below are some of the illustrations of these systems.

1. Cost Accounting system: Cost structure is very complex in health care industry. It is very difficult to divide costs in the areas of supplies, expensive machinery, technology and a variety of personnel. Cost accounting applications help health care organizations to calculate product costs for individual products or services.
2. Capital Budgeting System: Companies require new tools to evaluate high-technology investment decisions. Decision makers need to supplement analytical techniques such as NPV and IRR with decision support systems. For example AutoMan is a DSS, designed to support decisions about investments in automated manufacturing technology, which allow decision makers to consider financial, non financial, quantitative and qualitative factors in their decision-making process. Using this DSS, they can evaluate up-to 7 investment alternatives at a time.
3. Budget Variance Analysis System: Financial institutions rely heavily on their budgeting systems for controlling costs and evaluating managerial performance. For example, an organization can use DSS to generate monthly variance reports for each division. With the help of this system one can view, analyze, budget variances. After analyzing the variances, organization can create one-year and five-year budgets.
4. General DSS: DDSs use general purpose planning languages that can analyze different types of problems. In a sense these systems act as tools to decision makers. To use this type of systems the user has to input data and answer questions about a specific problem. An example is a program called
5. Expert Choice. This program supports a variety of problems requiring decisions. For example, the system may ask whether cash inflows are important or initial cash outlay is important. The decision maker also makes judgments about such questions. Expert Choice analyzes these judgments and presents the best alternative to the user.