Book Contents

Ch. 1
Supporting Business Decision-Making

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Five Main Categories of DSS

Data-Driven DSS

Letís call the first category of Decision Support Systems Data-Driven DSS. These systems include file drawer and management reporting systems, data warehousing and analysis systems, Executive Information Systems (EIS) and Geographic Information Systems (GIS). Business Intelligence Systems are also examples of Data-Driven DSS. Data-Driven DSS emphasize access to and manipulation of large databases of structured data and especially a time-series of internal company data and some times external data. Simple file systems accessed by query and retrieval tools provide the most elementary level of functionality. Data warehouse systems that allow the manipulation of data by computerized tools tailored to a specific task and setting or by more general tools and operators provide additional functionality. Data-Driven DSS with Online Analytical Processing (OLAP) provide the highest level of functionality and decision support that is linked to analysis of large collections of historical data (cf., Dhar and Stein, 1997). Professor Paul Gray argues that in approximately 1993, "the data warehouse and the EIS people found one another, with the data warehouses obtaining their needed application and the EIS people receiving a new breath of life from expanding beyond the pretty screen."

Model-Driven DSS

A second category, Model-Driven DSS, includes systems that use accounting and financial models, representational models, and optimization models. Model-Driven DSS emphasize access to and manipulation of a model. Simple statistical and analytical tools provide the most elementary level of functionality. Some OLAP systems that allow complex analysis of data may be classified as hybrid DSS systems providing modeling, data retrieval and data summarization functionality. Model-Driven DSS use data and parameters provided by decision-makers to aid them in analyzing a situation, but they are not usually data intensive. Very large databases are usually not needed for Model-Driven DSS.

Knowledge-Driven DSS

The terminology for the this category of DSS is still evolving. Currently, the best term seems to be Knowledge-Driven DSS. Sometimes it seems equally appropriate to use Alter's term Suggestion DSS or the narrower term Management Expert System. Knowledge-Driven DSS can suggest or recommend actions to managers. These DSS are person-computer systems with specialized problem-solving expertise. The "expertise" consists of knowledge about a particular domain, understanding of problems within that domain, and "skill" at solving some of these problems. A related concept is Data Mining. It refers to a class of analytical applications that search for hidden patterns in a database. Data mining is the process of sifting through large amounts of data to produce data content relationships. Tools used for building these systems are also called Intelligent Decision Support methods (cf., Dhar and Stein, 1997). Data Mining tools can be used to create hybrid Data-Driven and Knowledge-Driven DSS.

Document-Driven DSS

A new type of DSS, a Document-Driven DSS or Knowledge Management System, is evolving to help managers retrieve and manage unstructured documents and Web pages. A Document-Driven DSS integrates a variety of storage and processing technologies to provide complete document retrieval and analysis. The Web provides access to large document databases including databases of hypertext documents, images, sounds and video. Examples of documents that would be accessed by a Document-Based DSS are policies and procedures, product specifications, catalogs, and corporate historical documents, including minutes of meetings, corporate records, and important correspondence. A search engine is a powerful decision-aiding tool associated with a Document-Driven DSS (cf., Fedorowicz, 1993, pp. 125-136).

Communications-Driven and Group DSS

Group Decision Support Systems (GDSS) came first, but now a broader category of Communications-Driven DSS or groupware can be identified. This type of DSS includes communication, collaboration and decision support technologies that do not fit within those DSS types identified by Steven Alter. Therefore, Communications-Driven DSS need to be identified as a specific category of DSS. We will call these systems Communications-Driven DSS even though many people are more familiar with the term GDSS. A GDSS is a hybrid DSS that emphasizes both the use of communications and decision models. A Group Decision Support System is an interactive computer-based system intended to facilitate the solution of problems by decision-makers working together as a group. Groupware supports electronic communication, scheduling, document sharing, and other group productivity and decision support enhancing activities. We have a number of technologies and capabilities in this category in the framework -- GDSS Decision Rooms, two-way interactive video, White Boards, Bulletin Boards, and Email.


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