Decision Support Systems for Business Intelligence

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This chapter delves into the nature of decision making, forms of rationality, causes of satisficing behavior, perception challenges, and the importance of using data to challenge assumptions in the realm of business intelligence. It emphasizes the significance of information attributes and describes the measures of success for BI projects, including improved business performance, enhanced data access, stakeholder support, and user perception.


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  1. Chapter 2 Decision Making Decision Support Systems For Business Intelligence

  2. Figure 2.1: Nature of Decision Making Sauter, V.L. , Decision Support Systems for Business Intelligence, John Wiley, 2010

  3. Figure 2.2: Forms of Rationality Sauter, V.L. , Decision Support Systems for Business Intelligence, John Wiley, 2010

  4. Figure 2.3: Causes of Satisficing Behavior Sauter, V.L. , Decision Support Systems for Business Intelligence, John Wiley, 2010

  5. Figure 2.4: Perception is Not Always Obvious Sauter, V.L. , Decision Support Systems for Business Intelligence, John Wiley, 2010

  6. Figure 2.5: Is This a Car or a Truck? Sauter, V.L. , Decision Support Systems for Business Intelligence, John Wiley, 2010

  7. Figure 2.6: Attributes of Information Sauter, V.L. , Decision Support Systems for Business Intelligence, John Wiley, 2010

  8. Figure 2.7: Using Data to Challenge Assumptions Sauter, V.L. , Decision Support Systems for Business Intelligence, John Wiley, 2010

  9. Figure 2.8: Using Data to Challenge Assumptions Sauter, V.L. , Decision Support Systems for Business Intelligence, John Wiley, 2010

  10. Figure 2.9: An Early View of BI Sauter, V.L. , Decision Support Systems for Business Intelligence, John Wiley, 2010

  11. Table 2.1: Measures of Success of BI Projects Measures of Success of BI Projects* Improved Business Performance Better Access to Data Support of Key Stakeholders User Perception that it is Mission Critical ROI % of Active Users Cost Savings Number of Defined Users Other measures of success included: Number of BI Applications Number of New Requests for BI Applications Number of Standard ad hoc Reports Elimination of independent (shadow) spreadsheets Increased Employee Satisfaction Increased Customer Service Time Reduced 70% 68% 53% 50% 43% 31% 31% 17% *Adapted from Howson, C., Successful Business Intelligence: Secrets to making BI a Killer Application, New York: McGraw Hill, 2008. Sauter, V.L. , Decision Support Systems for Business Intelligence, John Wiley, 2010

  12. Table 2.2: Necessary Features of Successful BI Necessary Features of Successful BI High data quality and clean data Reliability of the system Availability of relevant subject areas Appropriate and effective BI tools Fast query response time BI being continually improved (both data and tools) Integration of BI into organizational processes Near real time updates to the data warehouse Sauter, V.L. , Decision Support Systems for Business Intelligence, John Wiley, 2010

  13. Figure 2.10: Demonstration of Microsofts Tool, Pivot Sauter, V.L. , Decision Support Systems for Business Intelligence, John Wiley, 2010

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