A Decision Support System is a specialized information system used when a problem is unstructured or when circumstances are uncertain. Learn about the data and models used in a DSS.
Decision Support Systems
A Decision Support System, or DSS, is a specialized information system specifically designed to facilitate the decision making process in the operations of organizations. Compared to other types of information systems, a DSS is typically used when a problem is unstructured or when circumstances are difficult to predict.
A DSS may include other types of systems. For example, a database management system (DBMS) is often part of a DSS in order to have access to the necessary data. However, a DSS is more than a DBMS since it provides a structure to facilitate the process of making decisions.
Sources of Information
A DSS gathers information from internal sources of an organization over which there is a certain amount of control as well as from external sources over which control is more limited. Internal sources consist of all the various databases within an organization, such as those related to personnel, finances, assets, customers, etc. External sources consist of the various factors that influence how an organization operates, such as market trends, government regulations, competitors, etc. How this information is used is best illustrated using an example.
Consider a bank, which provides loans to customers. A customer comes to the bank to request a mortgage loan to buy a house. The bank employee working with the customer will collect information to decide whether the bank will provide a loan to the customer and under what conditions. The information collected includes things like the customer's employment, income, credit score, loan history and other financial information.
Since this loan is to buy a house, the bank also collects information on the property, such as the legal description and the assessed market value. The bank will also look at trends in the real estate market, including interest rates offered by other financial institutions. Finally, the bank needs to consider its own internal finances, such as the funds it has available for loans, how many mortgage loans it has already approved recently, its experience with loans given to similar customers, etc.
There is a lot of information to consider. Some of this can be used again for the next loan application, but some of it is very specific to this particular customer. Some of the information can also change very quickly, such as trends in the housing market. A DSS makes it possible for the bank employee to make an informed decision in a timely manner that considers all the different internal and external data sources.
In addition to lots of data, a DSS uses a model base. This provides access to a number of different models to support decision making. Many of these models consist of statistical analysis of data and can serve as guidelines for certain decisions. Some models are used to determine patterns in existing data, while others are used to try to predict trends in the future.
Models in a DSS provide relatively easy access to sophisticated analytical methods. Typically, such models have already been developed and tested in other contexts, so users can have some confidence in them. In the case of the mortgage loan, a DSS could include a model that predicts the likelihood that someone will default on their loan based on their financial profile.
A DSS uses many different data sources as well as a number of different models. A typical user, however, could easily get overwhelmed by all this information. A DSS therefore often has a custom-built user interface that makes it a lot easier to use. In the example of the mortgage loan, the bank employee enters the information into electronic forms within the DSS. The user interface helps the employee ask the right questions and collect all the necessary information. Some of the necessary information is also collected automatically using behind-the-scenes protocols.
The user interface structures the collection and organization of data and also reports the results in an easy-to-follow format. A certain amount of training may be needed to use the system, but the employee does not have to be a database expert or statistical analyst to make an informed decision.
Not a Black Box
It is important to recognize that a DSS does not automatically make decisions. Ultimately, the decisions are made by people, and a DSS is used to support these decisions. In other words, a DSS is not a black box that magically produces the best decision.
In the case of the mortgage loan application, a DSS transforms a large amount of information into a meaningful summary. This could be in the form of a numerical score, a list of strengths or weaknesses or some type of visual. The bank employee or bank manager is still the person making the decision to approve a loan or not.
It is also important to recognize that the user needs to have some general knowledge about how the DSS works. In the case of a mortgage loan, if the application is denied, the bank employee should be able to explain to the customer why. Perhaps the house the customer wants to buy is a bit too expensive relative to their income, or they have too many other loans already.
A Decision Support System (DSS) is a specialized information system designed to facilitate decision making in organizations. It is typically used when a problem is unstructured or when circumstances are uncertain. A DSS uses a combination of data and models in an easy-to-use interface. Data come from both internal and external sources. A DSS does not make decisions automatically, but ensures that a decision by a user is well informed and based on analysis.
Following this lesson, you should be able to:
- Explain the function of a decision support system (DSS)
- Describe and provide examples of the types of data utilized by a DSS
- Define model base in relation to a DSS
- Summarize the role of human decision making when using a DSS