1. Supporting Decision Making Chapter 10 McGraw-Hill/IrwinCopyright © 2011 by The McGraw-Hill Companies, Inc. All rights reserved.

2. 10-2 Identify the changes taking place in the form and use of decision support in business Identify the role and reporting alternatives of management information systems Describe how online analytical processing can meet key information needs of managers Explain the decision support system concept and how it differs from traditional management information systems Learning Objectives

3. 10-3 Explain how the following information systems can support the information needs of executives, managers, and business professionals –Executive information systems –Enterprise information portals –Knowledge management systems Identify how neural networks, fuzzy logic, genetic algorithms, virtual reality, and intelligent agents can be used in business Learning Objectives

4. 10-4 Give examples of several ways expert systems can be used in business decision- making situations Learning Objectives

5. 10-5 Decision Support in Business Provide responses to: –Changing market conditions –Customer needs Several types of systems –Management information –Decision support –Other information systems

6. 10-6 RWC 1: Fact-Based Decision Making Decisions based on facts beat decisions based on gut Dashboard –Makes detailed statistics available in real-time Scorecard –Software compares details to defined metrics How prepared are organizations to synthesize and share key performance indicators? How prepared are executives to draw insight from information?

7. 10-7 Levels of Managerial Decision Making

8. 10-8 Attributes of Information Quality

9. 10-9 Decision Structure Structured (operational) –Procedures can be specified in advance Unstructured (strategic) –Not possible to specify procedures in advance Semi-structured (tactical) –Decision procedures can be pre-specified, but not enough to lead to the correct decision

10. 10-10 Decision Support Systems Management Information Systems Decision Support Systems Decision support provided Provide information about the performance of the organization Provide information and techniques to analyze specific problems Information form and frequency Periodic, exception, demand, and push reports and responses Interactive inquiries and responses Information format Prespecified, fixed formatAd hoc, flexible, and adaptable format Information processing methodology Information produced by extraction and manipulation of business data Information produced by analytical modeling of business data

11. 10-11 Decision Support Trends Add info from new paragraphs

12. 10-12 Business Intelligence Applications

13. 10-13 DSS Components

14. 10-14 Management Information Systems

15. 10-15 Online Analytical Processing

16. 10-16 GIS and DVS Systems

17. 10-17 Using Decision Support Systems

18. 10-18 Data Mining Provides decision support through knowledge discovery –Analyzes vast stores of historical business data –Looks for patterns, trends, and correlations –Goal is to improve business performance Types of analysis –Regression –Decision tree –Neural network –Cluster detection –Market basket analysis

19. 10-19 Market Basket Analysis One of the most common uses for data mining –Determines what products customers purchase together with other products Other uses –Cross Selling –Product Placement –Affinity Promotion –Survey Analysis –Fraud Detection –Analyze Customer Behavior

20. 10-20 Executive Information Systems (EIS) Combines many features of MIS and DSS Provides immediate and easy information Identifies critical success factors Features –Customizable graphical user interfaces –Exception reports –Trend analysis –Drill down capability

21. 10-21 Enterprise Information Portal Components

22. 10-22 Enterprise Knowledge Portal

23. 10-23 RWC 2: Shopping in Virtual Stores Benefits of virtual stores –Help understand customer behavior –Test products faster, more convenient and precise –Win shelf space –Focus on ways to get customers’ attention –Avoids tipping off competitors –Cuts testing time –Avoid displays that clash with store decor Environment of virtual shopping –Change variables with each test

24. 10-24 Attributes of Intelligent Behavior

25. 10-25 Domains of Artificial Intelligence

26. 10-26 Components of an Expert System

27. 10-27 Methods of Knowledge Representation Case-Based –Examples from the past Frame-Based –Collection of knowledge about an entity Object-Based –Data elements include both data and the methods or processes that act on those data Rule-Based –Factual statements in the form of a premise and a conclusion (If, Then)

28. 10-28 Expert System Application Categories Decision Management –Loan portfolio analysis –Employee performance evaluation –Insurance underwriting Diagnostic/Troubleshooting –Equipment calibration –Help desk operations –Medical diagnosis –Software debugging

29. 10-29 Expert System Application Categories Design/Configuration Selection/Classification Process Monitoring/Control

30. 10-30 Benefits of Expert Systems Captures human experience in a computer- based information system Limitations of Expert Systems Limited focus Inability to learn Maintenance problems Development cost Can only solve specific types of problems in a limited domain of knowledge

31. 10-31 Development Tool Expert System Shell –The easiest way to develop an expert system –A software package consisting of an expert system without its knowledge base –Has an inference engine and user interface programs

32. 10-32 Knowledge Engineering A knowledge engineer –Works with experts to capture the knowledge they possess Facts and rules of thumb –Builds the knowledge base if necessary, the rest of the expert system –Similar role to systems analysts

33. 10-33 Neural Networks Modeled after the brain’s mesh-like network of interconnected processing elements (neurons) –Interconnected processors operate in parallel and interact with each other –Allows the network to learn from the data it processes

34. 10-34 Example of Fuzzy Logic Rules and Query

35. 10-35 Genetic Algorithms Genetic algorithm software –Uses Darwinian, randomizing, and other mathematical functions –Simulates an evolutionary process, yielding increasingly better solutions to a problem –Used to model a variety of scientific, technical, and business processes –Useful when thousands of solutions are possible

36. 10-36 Virtual Reality (VR) Virtual reality is a computer-simulated reality –Fast-growing area of artificial intelligence –Originated from efforts to build natural, realistic, multi-sensory human-computer interfaces –Relies on multi-sensory input/output devices –Creates a three-dimensional world through sight, sound, and touch Telepresence –Using VR to perform a task in a different location

37. 10-37 Intelligent Agents Software surrogate for an end user or a process that fulfills a stated need or activity –Uses built-in and learned knowledge base to accomplish tasks Software robots or bots

38. 10-38 Types of Intelligent Agents User Interface Agents –Interface Tutors –Presentation Agents –Network Navigation Agents –Role-Playing Agents Information Management Agents –Search Agents –Information Brokers –Information Filters

39. 10-39 RWC 3: Driving Competitive Advantage Advanced technologies impact businesses –Goodyear reduced time to market –Public Utility Company JEA determines optimal combinations of oil and natural gas –The Ohio State University Medical Center (OSUMC) uses robots to move supplies 10-39

40. 10-40 RWC 4: Business Intelligence Deployments Analyze raw data (e.g., sales transactions) Extract useful insights Can transform business processes Can impact the bottom line Major impediment - most companies don’t understand their business processes well enough Uncovering flawed business processes beats merely to monitoring