Ch. 7
Building Data-Driven Decision Support Systems

The final type of Data-Driven DSS that should be defined is a Spatial Decision Support System (cf., Crossland, Wynne and Perkins, 1995) built using Geographic Information Systems (GIS) technologies. A GIS is a support system that represents data using maps. Spatial DSS help managers access, display, and analyze data that have geographic content and meaning. GIS have been available for many years. Some examples of Spatial DSS include systems for crime analysis and mapping, customer demographic analyses, and political voting patterns analysis.

Spatial DSS applications are common in routing and location analysis, marketing, and traditional application areas of GIS in disciplines such as geology, forestry, and land planning (cf., Keenan, 1997).

GIS software provides a development environment for Spatial DSS. Even limited functionality GIS software provides the ability to zoom in on a map and to display or highlight different data. A GIS provides database support that is designed to allow for the effective storage of spatial data. Also, GIS software provides a link between the user interface and database so a user can query and analyze the spatial data.

Data-Driven DSS have captured the imagination of managers because they can provide much easier access to a vast amount of business data. In a world of speeded up competition, rapid changes in markets and products, and increased electronic communication, managers want to find their own answers to business questions. Managers are NOT willing to wait while financial or marketing analysts create special reports from databases. Managers are the customers and advocates for Data-Driven Decision Support Systems. To build such systems we must identify and organize decision relevant data or DSS data. Now let’s compare and contrast DSS data and operating data. Matching decision situations and DSS data and information is the key to building Data-Driven DSS and making better fact-based managerial decisions.