Model-Driven DSS

Most of the material on Model-Driven DSS is in the DSSResources.COM Subscriber Zone. About Model-Driven DSS Model-Driven DSS emphasize access to and manipulation of a model, for example, statistical, financial, optimization and/or simulation models. 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 both modeling and data retrieval and data summarization functionality. In general, model-driven DSS use complex financial, simulation, optimization or multi-criteria models to provide decision support. Model-driven DSS use data and parameters provided by decision makers to aid decision makers in analyzing a situation, but they are not usually data intensive, that is very large data bases are usually not need for model-driven DSS. Early versions of Model-Driven DSS were called Computationally Oriented DSS by Bonczek, Holsapple and Whinston (1981). Such systems have also been called model-oriented or model-based decision support systems. Key Terms Decision Analysis tools - DA tools help decision makers decompose and structure problems. The aim of these tools is to help a user apply models like decision trees, multi-attribute utility models, bayesian models, Analytical Hierarchy Process (AHP), and related models. Forecasting Support System - A computer-based system that supports users in making and evaluating forecasts. Users can analyse a time series of data. Linear Programming - A mathematical model for optimal solution of resource allocation problems. Simulation - A technique for conducting one or more experiments that test various outcomes resulting from a quantitative model of a system. Building Model-Driven DSS Introduction Modeling Decision Situations Modeling Model Assumptions General Types of Models A DSS with Multiple Model Types General Problem Types Accounting and Financial Models Break-Even Analysis Budget Financial Models Pro Forma Financial Statements Ratio Analysis Decision Analysis Models Analytical Hierarchy Process (AHP) Decision Trees and Multi-attribute Utility Models Influence Diagrams Forecasting Models Network and Optimization Models Simulation Models Major Characteristics of Simulation Advantages and Disadvantages of Simulation Simulation Methodology Types of Simulation Modeling Languages and Spreadsheets Electronic Spreadsheets Development Packages Conclusions and Commentary Questions and Exercises Model-Driven DSS Examples – Airline Industry Model-Driven DSS Software References Web Links Relevant Ask Dan! Links What are the main types or categories of decision models used in DSS model base software? What are the major spreadsheet programs? What factors indicate a special study is more appropriate than a DSS? What is a good replacement for models built using IFPS? What is/was IFPS? Why are transportation problems popular applications for DSS? Relevant Case Study Examples Decisioneering Staff, "SunTrust 'Banks' on Crystal Ball for assessing the risk of commercial loans", Decisioneering, Inc., November 1998, posted at DSSResources.COM March 16, 2001, HTML link. Palisade Staff, "Procter & Gamble Uses @RISK and PrecisionTree World-Wide", Palisade Corp., Spring 2001, posted at DSSResources.COM May 22, 2001, HTML link. Young, James R., Geoff Rabone, Scott Akenhead and Ed Gregr, HydroBasin: Relicensing Planning for Hydroelectric Watersheds, Facet Decision Making, 2000, posted at DSSResources.COM November 18, 2001, HTML link. Please help me keep this information current and useful. Contact me with new links, link updates, and suggestions. DJP