BASICS OF DECISION SUPPORT SYSTEM

DECISION SUPPORT SYSTEM

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 analyze 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.

While many people think of decision support systems as a specialized part of a business, most companies have actually integrated this system into their day to day operating activities. For instance, many companies constantly download and analyze sales data, budget sheets and forecasts and they update their strategy once they analyze and evaluate the current results. Decision support systems have a definite structure in businesses, but in reality, the data and decisions that are based on it are fluid and constantly changing.

The key to decision support systems is to collect data, analyze and shape the data that is collected and then try to make sound decisions or construct strategies from analysis. Whether computers, databases or people are involved usually doesn't matter, however it is this process of taking raw or unstructured data, containing and collecting it and then using it to help aid decision making.

It is important to note that although computers and artificial intelligence is at work or in play with data, it is ultimately up to humans to execute these strategies or comprehend the data into a usable hypothesis.

It is important to note that the field of DSS does not have a universally accepted model, meaning that there are many theories vying for supremacy in this broad field. Because of there are many working theories in the topic of DSS, there are many ways to classify DSS.

For instance, one of the DSS models available is with the relationship of the user in mind. This model takes into consideration passive, active and cooperative DSS models.

Decision support systems that just collect data and organize it effectively are usually called passive models, they do not suggest a specific decision, and they only reveal the data. An active decision support system actually processes data and explicitly shows solutions based upon that data. While there are many systems that are able to be active, many organizations would be hard pressed to put all their faith into a computer model without any human intervention.

A cooperative decision support system is when data is collected, analyzed and then is provided to a human component which then can help the system revise or refine it. It means that both a human component and computer component work together to come up with the best solution.

While the above DSS model takes the relationship of the user in mind, another popular DSS model takes into consideration the mode of assistance as the underlying basis of the DSS model. This includes the Model Driven DSS, Communications Driven DSS, Data Driven DSS, Document Driven DSS, and Knowledge Driven DSS.

Model Driven DSS is when decision makers use statistical, simulations or financial models to come up with a solution or strategy. Keep in mind that these decisions are based on models; however they do not have to be overwhelming data intensive.

A Communications Driven DSS models is when many collaborators work together to come up with a series of decisions to set in motion a solution or strategy. This communications driven DSS model can be in an office environment or on the web.

A Data Driven DSS model puts its emphasis on collected data that is then manipulated to fit the decision maker's needs. This data can be internal, external and in a variety of formats. It is important that usually data is collected and categorized as a time series which is a collection of data that forms a sequence, such as daily sales, operating budgets from one quarter to the next, inventory leels over the previous year, etc.

A Document Driven DSS model uses documents in a variety of data types such a text documents, spreadsheets and database records to come up with decisions a well as further manipulate the information to refine strategies.

A Knowledge Driven DSS model uses special rules stored in a computer or used by a human to determine whether a decision should be made. For instance, for many day traders a stop loss limit can be seen as a knowledge driven DSS model. These rules or facts are used in order to make a decision.

You can also look at the scope in which decisions are made as a model of DSS. For instance, an organizational wide decision, department decision or single user decision, can be seen in the scope wide model.