1. Model Based DSS Creating Information Under Conditions of Uncertainty and Complexity Interface MODEL BASE DATA BASE MBMSDBMS DATA WAREHOUSING ON LINE ANALYTICAL PROCESSING GUI, Intelligent Objects, Voice, GroupWare, etc. External Models External Data Information Technology for Enterprise Strategic Systems

2. Developing and Using Models Processes for Analyzing Problem/Opportunities Situations Model Representation Deterministic Analysis Probabilistic Analysis Evaluation of Alternatives Decision Analysis Models Statistical, OR/MS, Financial Models Sensitivity Analyses (1-way, n-way) Goal Seeking and Optimization Using Probabilities (Decision Analyses) Using Probability Distributions (Simulation) Using Heuristics, Consensus Methods Goal Maximization, Internal Consistency

3. Profit (Outcome) INPUT Variables  Compares one-way sensitivity analysis  Most sensitive variable is at top and descends in sensitivity  Shows sensitivity range  Produces a tornado appearance Measuring the sensitivity (changes) in the outcome due to changes in the input variable n-way Sensitivity Analysis  Changes in several inputs  Helps evaluate scenarios  Scenario manger in Excel One-way Sensitivity Analysis Controllable Uncontrollabl e Intermediate Model Outcome Evaluating Uncertainty Using Models Deterministic Analyses for answering “what-if” questions

4. Evaluating Uncertainty Using Models Probability Analyses for answering “what-if” questions Controllable Uncontrollabl e Intermediate Model Outcome Regression Analyses Simple Linear Regression (One -Way Probabilistic) Multiple Linear Regression (N -Way Probabilistic) Model uncertain relationships using data Monte-Carlo Simulation Model uncertain variables using probability distributions