After reading this chapter, you should be able to answer the following questions: Why is it hard for people to make good decisions? How do models help managers make better decisions? What are the key elements of decision support systems? How is data mining different from traditional statistical analysis? What is the purpose of OLAP? What is a digital dashboard? What are the advantages of an EIS? How can a GIS help managers make better decisions? | Introduction to MIS Chapter 8 Models and Decision Support Models Data Model Decision Output Strategy Operations Tactics Company Outline Biases in Decisions Introduction to Models Why Build Models? Decision Support Systems: Database, Model, Output Data Warehouse Data Mining and Analytical Processing Digital Dashboard and EIS DSS Examples Geographical Information Systems Cases: Computer Hardware Industry Appendix: Forecasting Decision Levels Business Operations Tactical Management Strategic Mgt. EIS ES DSS Transaction Processing Process Control Models Choose a Stock Company A’s share price increased by 2% per month. Company B’s share price was flat for 5 months and then increased by 3% per month. Which company would you invest in? Human Biases Acquisition/Input Data availability Selective perception Frequency Concrete information Illusory correlation Processing Inconsistency Conservatism Non-linear extrapolation Heuristics: Rules of thumb Anchoring and adjustment Representativeness Sample size Justifiability Regression bias Best guess strategies Complexity Emotional stress Social pressure Redundancy Output Question format Scale effects Wishful thinking Illusion of control Feedback Learning on irrelevancies Misperception of chance Success/failure attribution Logical fallacies in recall Hindsight bias Optimization 1 2 3 4 5 6 7 8 9 10 1 3 5 0 5 10 15 20 25 Output Input Levels Maximum Model: defined by the data points or equation Control variables Goal or output variables File: Why Build Models? Understanding the Process Optimization Prediction Simulation or "What If" Scenarios Dangers Prediction 0 5 10 15 20 25 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Time/quarters Output Moving Average Trend/Forecast Economic/ regression Forecast File: Simulation 0 5 10 15 20 25 1 2 3 4 5 6 7 8 9 10 Input Levels Output Goal or output variables Results from altering internal rules File: Object-Oriented Simulation Models Customer purchase order Order Entry . | Introduction to MIS Chapter 8 Models and Decision Support Models Data Model Decision Output Strategy Operations Tactics Company Outline Biases in Decisions Introduction to Models Why Build Models? Decision Support Systems: Database, Model, Output Data Warehouse Data Mining and Analytical Processing Digital Dashboard and EIS DSS Examples Geographical Information Systems Cases: Computer Hardware Industry Appendix: Forecasting Decision Levels Business Operations Tactical Management Strategic Mgt. EIS ES DSS Transaction Processing Process Control Models Choose a Stock Company A’s share price increased by 2% per month. Company B’s share price was flat for 5 months and then increased by 3% per month. Which company would you invest in? Human Biases Acquisition/Input Data availability Selective perception Frequency Concrete information Illusory correlation Processing Inconsistency Conservatism Non-linear extrapolation Heuristics: Rules of thumb Anchoring and adjustment Representativeness .
