Ch. 9
Building Model-Driven Decision Support Systems

Models can be developed in a variety of programming languages like Java and C++ and with a wide variety of software packages including spreadsheets and modeling packages. Spreadsheets are commonly used for desktop Model-Driven DSS. Modeling packages attempt to help users create and manipulate models. A model management system tries to provide support for various phases of the decision modeling life cycle.

DSS development packages for OLAP and modeling have a variety of quantitative models in areas like statistics, financial analysis, accounting, and management science. These small models can be executed using a single command, such as: AVERAGE or NPV. AVERAGE calculates the average of a number and may be used in a larger model; and NPV calculates the net present value of a collection of future cash flows for a given interest rate. It also may be a part of a make-versus-buy model.

Functions are often building blocks for other quantitative models. For example, a regression model can be a part of a forecasting model that supports a financial planning model. Several statistical functions are built into DSS generators. All major spreadsheet packages have extensive statistical tools. For example, Excel has analysis of variance, correlation, covariance, descriptive statistics, exponential smoothing, f-test, histograms, and moving average.

In addition, many DSS generators can interface with quantitative stand-alone packages. Such packages are usually much more powerful than the built-in routines. "Canned" or preprogrammed models can reduce the programming time of the DSS builder.