1. 9-1 McGraw-Hill/Irwin Copyright © 2007 by The McGraw-Hill Companies, Inc. All rights reserved.

2. Decision Support Systems Decision Support MIS and DSS Artificial Intelligence Expert Systems Chapter 9 McGraw-Hill/Irwin Copyright © 2007 by The McGraw-Hill Companies, Inc. All rights reserved.

3. 9-3 Learning Objectives 1. Identify the changes taking place in the form and use of decision support in business. 2. Identify the role and reporting alternatives of management information systems. 3. Describe how online analytical processing can meet key information needs of managers. 4. Explain the decision support system concept and how it differs from traditional management information systems.

4. 9-4 Learning Objectives 5. Explain how the following information systems can support the information needs of executives, managers, and business professionals: a. Executive information systems b. Enterprise information portals c. Knowledge management systems

5. 9-5 Learning Objectives 5. Identify how neural networks, fuzzy logic, genetic algorithms, virtual reality, and intelligent agents can be used in business. 6. Give examples of several ways expert systems can be used in business decision-making situations.

6. 9-6 Case 1: Centralized Business Intelligence at Work Starting each business-intelligence project from scratch leads to Reinventing the wheel High development and support costs Incompatible systems Some companies are standardizing on fewer business-intelligence tools and making them available throughout the organization and Business-intelligence competency centers

7. 9-7 Case Study Questions 1. What is business intelligence? Why are business intelligence systems such a popular business application of IT? 2. What is the business value of the various BI applications discussed in the case? 3. Is a business-intelligence system an MIS or a DSS?

8. 9-8 Real World Internet Activity 1. Companies are taking advantage of the competitive edge they enjoy from high-quality business intelligence. To meet the demand for applications to support the process, vendors are developing a wide variety of offerings. Using the Internet, See if you can find several examples of software products to support the management of business intelligence. Do they all take the same approach, or are there different ways of managing the process?

9. 9-9 Real World Group Activity Business intelligence competency centers can be quite costly to start and maintain. There prevalence, however, suggests the benefits are worth the costs. In small groups, Discuss the various skills and job roles necessary for a competitive business intelligence competency center. Can such centers be considered competitive advantage or simply competitive necessity?

10. 9-10 Information required at different management levels

11. 9-11 Levels of Management Decision Making Strategic management Executives develop organizational goals, strategies, policies, and objectives As part of a strategic planning process Tactical management Managers and business professionals in self-directed teams Develop short- and medium-range plans, schedules and budgets Specify the policies, procedures and business objectives for their subunits

12. 9-12 Levels of Management Decision Making Operational management Managers or members of self-directed teams Develop short-range plans such as weekly production schedules

13. 9-13 Information Quality Information products whose characteristics, attributes, or qualities make the information more value Information has 3 dimensions: Time Content Form

14. 9-14 Attributes of Information Quality

15. 9-15 Decision Structure Structured – situations where the procedures to follow when a decision is needed can be specified in advance Unstructured – decision situations where it is not possible to specify in advance most of the decision procedures to follow Semistructured - decision procedures that can be prespecified, but not enough to lead to a definite recommended decision

16. 9-16 Information Systems to support decisions 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

17. 9-17 Decision Support Trends Personalized proactive decision analytics Web-Based applications Decisions at lower levels of management and by teams and individuals Business intelligence applications

18. 9-18 Business Intelligence Applications

19. 9-19 Decision Support Systems DSS Provide interactive information support to managers and business professionals during the decision- making process Use: Analytical models Specialized databases A decision maker’s own insights and judgments Interactive computer-based modeling To support semistructured business decisions

20. 9-20 DSS components

21. 9-21 DSS Model base Model base A software component that consists of models used in computational and analytical routines that mathematically express relations among variables Examples: Linear programming models, Multiple regression forecasting models Capital budgeting present value models

22. 9-22 Management Information Systems MIS Produces information products that support many of the day-to-day decision-making needs of managers and business professionals Prespecified reports, displays and responses Support more structured decisions

23. 9-23 MIS Reporting Alternatives Periodic Scheduled Reports Prespecified format on a regular basis Exception Reports Reports about exceptional conditions May be produced regularly or when exception occurs Demand Reports and Responses Information available when demanded Push Reporting Information pushed to manager

24. 9-24 Online Analytical Processing OLAP Enables mangers and analysts to examine and manipulate large amounts of detailed and consolidated data from many perspectives Done interactively in real time with rapid response

25. 9-25 OLAP Analytical Operations Consolidation Aggregation of data Drill-down Display detail data that comprise consolidated data Slicing and Dicing Ability to look at the database from different viewpoints

26. 9-26 OLAP Technology

27. 9-27 Geographic Information Systems GIS DSS that uses geographic databases to construct and display maps and other graphics displays That support decisions affecting the geographic distribution of people and other resources Often used with Global Position Systems (GPS) devices

28. 9-28 Data Visualization Systems DVS DSS that represents complex data using interactive three-dimensional graphical forms such as charts, graphs, and maps DVS tools help users to interactively sort, subdivide, combine, and organize data while it is in its graphical form.

29. 9-29 Using DSS What-if Analysis End user makes changes to variables, or relationships among variables, and observes the resulting changes in the values of other variables Sensitivity Analysis Value of only one variable is changed repeatedly and the resulting changes in other variables are observed

30. 9-30 Using DSS Goal-Seeking Set a target value for a variable and then repeatedly change other variables until the target value is achieved How can analysis Optimization Goal is to find the optimum value for one or more target variables given certain constraints One or more other variables are changed repeatedly until the best values for the target variables are discovered

31. 9-31 Data Mining Main purpose is to provide decision support to managers and business professionals through knowledge discovery Analyzes vast store of historical business data Tries to discover patterns, trends, and correlations hidden in the data that can help a company improve its business performance Use regression, decision tree, neural network, cluster analysis, or market basket analysis

32. 9-32 Market Basket Analysis One of most common data mining for marketing The purpose is to determine what products customers purchase together with other products

33. 9-33 Executive Information Systems EIS Combine many features of MIS and DSS Provide top executives with immediate and easy access to information About the factors that are critical to accomplishing an organization’s strategic objectives (Critical success factors) So popular, expanded to managers, analysts and other knowledge workers

34. 9-34 Features of an EIS Information presented in forms tailored to the preferences of the executives using the system Customizable graphical user interfaces Exception reporting Trend analysis Drill down capability

35. 9-35 Enterprise Interface Portals EIP Web-based interface Integration of MIS, DSS, EIS, and other technologies Gives all intranet users and selected extranet users access To a variety of internal and external business applications and services Typically tailored to the user giving them a personalized digital dashboard

36. 9-36 Enterprise Information Portal Components

37. 9-37 Knowledge Management Systems The use of information technology to help gather, organize, and share business knowledge within an organization Enterprise Knowledge Portals EIPs that are the entry to corporate intranets that serve as knowledge management systems

38. 9-38 Enterprise Knowledge Portals

39. 9-39 Case 2 Artificial Intelligence The Dawn of the Digital Brain Numenta will translate the way the brain works into an algorithm that can run on a new type of computer The human brain does not work like a computer Intelligence, according to Hawkins, is pattern recognition

40. 9-40 Case Study Questions 1. What is the business value of AI technologies in business today? What value might exist if Jeff Hawkins can build a machine to think like humans? 2. Why has artificial intelligence become so important to business? 3. Why do you think banks and other financial institutions are leading users of AI technologies? What are the benefits and limitations of this technology?

41. 9-41 Real World Internet Activity 1. The concept of human thought is still a mystery despite the development of our understanding of the fundamental processes of the human brain. For many years, scientists have worked hard to develop humanlike machines, but none have been able to perform as well as the human brain when it comes to reasoning. Using the Internet, See if you can find evidence of other projects similar to that of Hawkins. What is the current state of the art in this area of research and development?

42. 9-42 Real World Group Activity The case ends by asking the question of whether we can ever build a machine more intelligent than a human. The real question is what will we do with it, or with us, if we are successful. In small groups, Brainstorm about a future with machines that can equal or exceed the intelligence of humans. What good would come of such an accomplishment? What potential risks might occur?

43. 9-43 Artificial Intelligence (AI) A field of science and technology based on disciplines such as computer science, biology, psychology, linguistics, mathematics, and engineering Goal is to develop computers that can simulate the ability to think, as well as see, hear, walk, talk, and feel

44. 9-44 Attributes of Intelligent Behavior Think and reason Use reason to solve problems Learn or understand from experience Acquire and apply knowledge Exhibit creativity and imagination Deal with complex or perplexing situations Respond quickly and successfully to new situations Recognize the relative importance of elements in a situation Handle ambiguous, incomplete, or erroneous information

45. 9-45 Domains of Artificial Intelligence

46. 9-46 Cognitive Science Based in biology, neurology, psychology, etc. Focuses on researching how the human brain works and how humans think and learn

47. 9-47 Robotics Based in AI, engineering and physiology Robot machines with computer intelligence and computer controlled, humanlike physical capabilities

48. 9-48 Natural Interfaces Based in linguistics, psychology, computer science, etc. Includes natural language and speech recognition Development of multisensory devices that use a variety of body movements to operate computers Virtual reality Using multisensory human-computer interfaces that enable human users to experience computer-simulated objects, spaces and “worlds” as if they actually exist

49. 9-49 Expert Systems ES A knowledge-based information system (KBIS) that uses its knowledge about a specific, complex application to act as an expert consultant to end users KBIS is a system that adds a knowledge base to the other components on an IS

50. 9-50 Expert System Components Knowledge Base Facts about specific subject area Heuristics that express the reasoning procedures of an expert (rules of thumb) Software Resources Inference engine processes the knowledge and makes inferences to make recommend course of action User interface programs to communicate with end user Explanation programs to explain the reasoning process to end user

51. 9-51 Expert System Components

52. 9-52 Methods of Knowledge Representation Case-Based – knowledge organized in form of cases Cases: examples of past performance, occurrences and experiences Frame-Based – knowledge organized in a hierarchy or network of frames Frames: entities consisting of a complex package of data values

53. 9-53 Methods of Knowledge Representation Object-Based – knowledge organized in network of objects Objects: data elements and the methods or processes that act on those data Rule-Based – knowledge represented in rules and statements of fact Rules: statements that typically take the form of a premise and a conclusion Such as, If (condition) then (conclusion)

54. 9-54 Expert System Benefits Faster and more consistent than an expert Can have the knowledge of several experts Does not get tired or distracted by overwork or stress Helps preserve and reproduce the knowledge of experts

55. 9-55 Expert System Limitations Limited focus Inability to learn Maintenance problems Developmental costs Can only solve specific types of problems in a limited domain of knowledge

56. 9-56 Suitability Criteria for Expert Systems Domain: subject area relatively small and limited to well-defined area Expertise: solutions require the efforts of an expert Complexity: solution of the problem is a complex task that requires logical inference processing (not possible in conventional information processing) Structure: solution process must be able to cope with ill-structured, uncertain, missing and conflicting data Availability: an expert exists who is articulate and cooperative

57. 9-57 Development Tool Expert System Shell Software package consisting of an expert system without its knowledge base Has inference engine and user interface programs

58. 9-58 Knowledge Engineer A professional who works with experts to capture the knowledge they possess Builds the knowledge base using an iterative, prototyping process

59. 9-59 Neural Networks Computing systems modeled after the brain’s mesh- like network of interconnected processing elements, called neurons Interconnected processors operate in parallel and interact with each other Allows network to learn from data it processes

60. 9-60 Fuzzy Logic Method of reasoning that resembles human reasoning Allows for approximate values and inferences and incomplete or ambiguous data instead of relying only on crisp data Uses terms such as “very high” rather than precise measures

61. 9-61 Genetic Algorithms Software that uses Darwinian (survival of the fittest), randomizing, and other mathematical functions To simulate an evolutionary process that can yield increasingly better solutions to a problem

62. 9-62 Virtual Reality (VR) Computer-simulated reality Relies on multisensory input/output devices such as a tracking headset with video goggles and stereo earphones, a data glove or jumpsuit with fiber-optic sensors that track your body movements, and a walker that monitors the movement of your feet

63. 9-63 Intelligent Agents A software surrogate for an end user or a process that fulfills a stated need or activity Uses its built-in and learned knowledge base To make decisions and accomplish tasks in a way that fulfills the intentions of a user Also called software robots or bots

64. 9-64 User Interface Agents Interface Tutors – observe user computer operations, correct user mistakes, and provide hints and advice on efficient software use Presentation – show information in a variety of forms and media based on user preferences Network Navigation – discover paths to information and provide ways to view information based on user preferences Role-Playing – play what-if games and other roles to help users understand information and make better decisions

65. 9-65 Information Management Agents Search Agents – help users find files and databases, search for desired information, and suggest and find new types of information products, media, and resources Information Brokers – provide commercial services to discover and develop information resources that fit the business or personal needs of a user Information Filters – receive, find, filter, discard, save, forward, and notify users about products received or desired

66. 9-66 Case 3: Robots are the common denominator Telerobotic-assisted medical procedures Flexible automobile body shop with wireless inventory replenishment

67. 9-67 Case Study Questions 1. What is the current and future business value of robotics? 2. Would you be comfortable with a robot performing surgery on you? Why or why not? 3. The robots being used by Ford Motor Co. are contributing to a streamlining of their supply chain. What other applications of robots can you envision to improve supply chain management beyond those described in the case?

68. 9-68 Real World Internet Activity 1. Applications for robots are being explored in every possible setting. Using the Internet, See if you can find some examples where robots have been used to improve a process, reduce costs, or make the impossible possible.

69. 9-69 Real World Group Activity The previous case in the chapter described the development of a machine that could think just like humans. Combined with advanced robotics, such a machine could conceivably perform most actions as well, or possibly better, than humans. In small groups, Discuss how the combination of advanced AI and robotics could be used to create business value. What would we want such machines to be able to do or not do?