1. McGraw-Hill/Irwin Copyright © 2008, The McGraw-Hill Companies, Inc. All rights reserved.McGraw-Hill/Irwin Copyright © 2008 The McGraw-Hill Companies, Inc. All rights reserved.

2. McGraw-Hill/Irwin Copyright © 2008, The McGraw-Hill Companies, Inc. All rights reserved.McGraw-Hill/Irwin Copyright © 2008 The McGraw-Hill Companies, Inc. All rights reserved. Decision Support Systems Chapter 10

3. 10-3 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

4. 10-4 Learning Objectives 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

5. 10-5 Learning Objectives Give examples of several ways expert systems can be used in business decision-making situations

6. 10-6 Decision Support in Business Companies are investing in data-driven decision support application frameworks to help them respond to Changing market conditions Customer needs This is accomplished by several types of Management information Decision support Other information systems

7. 10-7 Case 1: Dashboards for Executives Web-based “dashboards” Displays critical information in graphic form Assembled from data pulled in real time from corporate software and databases Managers see changes almost instantaneously Now available to smaller companies Potential problems Pressure on employees Divisions in the office Tendency to hoard information

8. 10-8 Case Study Questions What is the attraction of dashboards to CEOs and other executives? What real business value do they provide to executives? The case emphasizes that managers of small businesses and many business professionals now rely on dashboards. What business benefits do dashboards provide to this business audience?

9. 10-9 Case Study Questions What are several reasons for criticism of the use of dashboards by executives? Do you agree with any of this criticism?

10. 10-10 Levels of Managerial Decision Making

11. 10-11 Information Quality Information products made more valuable by their attributes, characteristics, or qualities Information that is outdated, inaccurate, or hard to understand has much less value Information has three dimensions Time Content Form

12. 10-12 Attributes of Information Quality

13. 10-13 Decision Structure Structured (operational) The procedures to follow when decision is needed can be specified in advance Unstructured (strategic) It is not possible to specify in advance most of the decision procedures to follow Semi-structured (tactical) Decision procedures can be pre-specified, but not enough to lead to the correct decision

14. 10-14 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

15. 10-15 Decision Support Trends The emerging class of applications focuses on Personalized decision support Modeling Information retrieval Data warehousing What-if scenarios Reporting

16. 10-16 Business Intelligence Applications

17. 10-17 Decision Support Systems Decision support systems use the following to support the making of semi-structured business decisions Analytical models Specialized databases A decision-maker’s own insights and judgments An interactive, computer-based modeling process DSS systems are designed to be ad hoc, quick-response systems that are initiated and controlled by decision makers

18. 10-18 DSS Components

19. 10-19 DSS Model Base Model Base A software component that consists of models used in computational and analytical routines that mathematically express relations among variables Spreadsheet Examples Linear programming Multiple regression forecasting Capital budgeting present value

20. 10-20 Applications of Statistics and Modeling Supply Chain: simulate and optimize supply chain flows, reduce inventory, reduce stock-outs Pricing: identify the price that maximizes yield or profit Product and Service Quality: detect quality problems early in order to minimize them Research and Development: improve quality, efficacy, and safety of products and services

21. 10-21 Management Information Systems The original type of information system that supported managerial decision making Produces information products that support many day-to-day decision-making needs Produces reports, display, and responses Satisfies needs of operational and tactical decision makers who face structured decisions

22. 10-22 Management Reporting Alternatives Periodic Scheduled Reports Prespecified format on a regular basis Exception Reports Reports about exceptional conditions May be produced regularly or when an exception occurs Demand Reports and Responses Information is available on demand Push Reporting Information is pushed to a networked computer

23. 10-23 Example of Push Reporting Insert Figure 10.10 here

24. 10-24 Online Analytical Processing OLAP Enables managers and analysts to examine and manipulate large amounts of detailed and consolidated data from many perspectives Done interactively, in real time, with rapid response to queries

25. 10-25 Online Analytical Operations Consolidation Aggregation of data Example: data about sales offices rolled up to the district level Drill-Down Display underlying detail data Example: sales figures by individual product Slicing and Dicing Viewing database from different viewpoints Often performed along a time axis

26. 10-26 OLAP Configuration Insert Figure 10.11

27. 10-27 Geographic Information Systems GIS DSS uses geographic databases to construct and display maps and other graphic displays Supports decisions affecting the geographic distribution of people and other resources Often used with Global Positioning Systems (GPS) devices

28. 10-28 Data Visualization Systems DVS Represents complex data using interactive, three-dimensional graphical forms (charts, graphs, maps) Helps users interactively sort, subdivide, combine, and organize data while it is in its graphical form

29. 10-29 DVS Example Insert Figure 10.14 here

30. 10-30 Using Decision Support Systems Using a decision support system involves an interactive analytical modeling process Decision makers are not demanding pre-specified information They are exploring possible alternatives What-If Analysis Observing how changes to selected variables affect other variables

31. 10-31 Using Decision Support Systems Sensitivity Analysis Observing how repeated changes to a single variable affect other variables Goal-seeking Analysis Making repeated changes to selected variables until a chosen variable reaches a target value Optimization Analysis Finding an optimum value for selected variables, given certain constraints

32. 10-32 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

33. 10-33 Analysis of Customer Demographics

34. 10-34 Market Basket Analysis One of the most common uses for data mining Determines what products customers purchase together with other products Results affect how companies Market products Place merchandise in the store Lay out catalogs and order forms Determine what new products to offer Customize solicitation phone calls

35. 10-35 Executive Information Systems EIS Combines many features of MIS and DSS Provide top executives with immediate and easy access to information Identify factors that are critical to accomplishing strategic objectives (critical success factors) So popular that it has been expanded to managers, analysis, and other knowledge workers

36. 10-36 Features of an EIS Information presented in forms tailored to the preferences of the executives using the system Customizable graphical user interfaces Exception reports Trend analysis Drill down capability

37. 10-37 Enterprise Information Portals An EIP is a Web-based interface and integration of MIS, DSS, EIS, and other technologies Available to all intranet users and select extranet users Provides access to a variety of internal and external business applications and services Typically tailored or personalized to the user or groups of users Often has a digital dashboard Also called enterprise knowledge portals

38. 10-38 Dashboard Example

39. 10-39 Enterprise Information Portal Components

40. 10-40 Enterprise Knowledge Portal

41. 10-41 Case 2: Automated Decision Making Automated decision making has been slow to materialize Early applications were just solutions looking for problems, contributing little to improved organizational performance A new generation of AI applications Easier to create and manage Decision making triggered without human intervention Can translate decisions into action quickly, accurately, and efficiently

42. 10-42 Case 2: Automated Decision Making AI is best suited for Decisions that must be made quickly and frequently, using electronic data Highly structured decision criteria High-quality data Common users of AI Transportation industry Hotels Investment firms and lenders

43. 10-43 Case Study Questions Why did some previous attempts to use artificial intelligence technologies fail? What key differences of the new AI-based applications versus the old cause the authors to declare that automated decision making is coming of age? What types of decisions are best suited for automated decision making?

44. 10-44 Case Study Questions What role do humans plan in automated decision-making applications? What are some of the challenges faced by managers where automated decision-making systems are being used? What solutions are needed to meet such challenges?

45. 10-45 Artificial Intelligence (AI) AI is a field of science and technology based on Computer science Biology Psychology Linguistics Mathematics Engineering The goal is to develop computers than can simulate the ability to think And see, hear, walk, talk, and feel as well

46. 10-46 Attributes of Intelligent Behavior Some of the 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

47. 10-47 Attributes of Intelligent Behavior Attributes of intelligent behavior (continued) Respond quickly and successfully to new situations Recognize the relative importance of elements in a situation Handle ambiguous, incomplete, or erroneous information

48. 10-48 Domains of Artificial Intelligence

49. 10-49 Cognitive Science Applications in the cognitive science of AI Expert systems Knowledge-based systems Adaptive learning systems Fuzzy logic systems Neural networks Genetic algorithm software Intelligent agents Focuses on how the human brain works and how humans think and learn

50. 10-50 Robotics AI, engineering, and physiology are the basic disciplines of robotics Produces robot machines with computer intelligence and humanlike physical capabilities This area include applications designed to give robots the powers of Sight or visual perception Touch Dexterity Locomotion Navigation

51. 10-51 Natural Interfaces Major thrusts in the area of AI and the development of natural interfaces Natural languages Speech recognition Virtual reality Involves research and development in Linguistics Psychology Computer science Other disciplines

52. 10-52 Latest Commercial Applications of AI Decision Support Helps capture the why as well as the what of engineered design and decision making Information Retrieval Distills tidal waves of information into simple presentations Natural language technology Database mining

53. 10-53 Latest Commercial Applications of AI Virtual Reality X-ray-like vision enabled by enhanced-reality visualization helps surgeons Automated animation and haptic interfaces allow users to interact with virtual objects Robotics Machine-vision inspections systems Cutting-edge robotics systems From micro robots and hands and legs, to cognitive and trainable modular vision systems

54. 10-54 Expert Systems An Expert System (ES) A knowledge-based information system Contain knowledge about a specific, complex application area Acts as an expert consultant to end users

55. 10-55 Components of an Expert System Knowledge Base Facts about a specific subject area Heuristics that express the reasoning procedures of an expert (rules of thumb) Software Resources An inference engine processes the knowledge and recommends a course of action User interface programs communicate with the end user Explanation programs explain the reasoning process to the end user

56. 10-56 Components of an Expert System

57. 10-57 Methods of Knowledge Representation Case-Based Knowledge organized in the form of cases Cases are examples of past performance, occurrences, and experiences Frame-Based Knowledge organized in a hierarchy or network of frames A frame is a collection of knowledge about an entity, consisting of a complex package of data values describing its attributes

58. 10-58 Methods of Knowledge Representation Object-Based Knowledge represented as a network of objects An object is a data element that includes both data and the methods or processes that act on those data Rule-Based Knowledge represented in the form of rules and statements of fact Rules are statements that typically take the form of a premise and a conclusion (If, Then)

59. 10-59 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

60. 10-60 Expert System Application Categories Design/Configuration Computer option installation Manufacturability studies Communications networks Selection/Classification Material selection Delinquent account identification Information classification Suspect identification Process Monitoring/Control

61. 10-61 Expert System Application Categories Process Monitoring/Control Machine control (including robotics) Inventory control Production monitoring Chemical testing

62. 10-62 Benefits of Expert Systems Captures the expertise of an expert or group of experts in a computer-based information system Faster and more consistent than an expert Can contain knowledge of multiple experts Does not get tired or distracted Cannot be overworked or stressed Helps preserve and reproduce the knowledge of human experts

63. 10-63 Limitations of Expert Systems The major 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

64. 10-64 Developing Expert Systems Suitability Criteria for Expert Systems Domain: the domain or subject area of the problem is small and well-defined Expertise: a body of knowledge, techniques, and intuition is needed that only a few people possess Complexity: solving the problem is a complex task that requires logical inference processing

65. 10-65 Developing Expert Systems Suitability Criteria for Expert Systems Structure: the solution process must be able to cope with ill-structured, uncertain, missing, and conflicting data and a changing problem situation Availability: an expert exists who is articulate, cooperative, and supported by the management and end users involved in the development process

66. 10-66 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

67. 10-67 Knowledge Engineering A knowledge engineer Works with experts to capture the knowledge (facts and rules of thumb) they possess Builds the knowledge base, and if necessary, the rest of the expert system Performs a role similar to that of systems analysts in conventional information systems development

68. 10-68 Neural Networks Computing systems 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

69. 10-69 Fuzzy Logic Fuzzy logic Resembles human reasoning Allows for approximate values and inferences and incomplete or ambiguous data Uses terms such as “very high” instead of precise measures Used more often in Japan than in the U.S. Used in fuzzy process controllers used in subway trains, elevators, and cars

70. 10-70 Example of Fuzzy Logic Rules and Query

71. 10-71 Genetic Algorithms Genetic algorithm software Uses Darwinian, randomizing, and other mathematical functions Simulates an evolutionary process, yielding increasingly better solutions to a problem Being uses to model a variety of scientific, technical, and business processes Especially useful for situations in which thousands of solutions are possible

72. 10-72 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 Also called telepresence

73. 10-73 Typical VR Applications Current applications of virtual reality Computer-aided design Medical diagnostics and treatment Scientific experimentation Flight simulation Product demonstrations Employee training Entertainment

74. 10-74 Intelligent Agents A software surrogate for an end user or a process that fulfills a stated need or activity Uses built-in and learned knowledge base to make decisions and accomplish tasks in a way that fulfills the intentions of a user Also call software robots or bots

75. 10-75 User Interface Agents Interface Tutors – observe user computer operations, correct user mistakes, provide hints/advice on efficient software use Presentation Agents – show information in a variety of forms/media based on user preferences Network Navigation Agents – discover paths to information, provide ways to view it based on user preferences Role-Playing – play what-if games and other roles to help users understand information and make better decisions

76. 10-76 Information Management Agents Search Agents – help users find files and databases, search for information, and suggest and find new types of information products, media, resources Information Brokers – provide commercial services to discover and develop information resources that fit business or personal needs Information Filters – Receive, find, filter, discard, save, forward, and notify users about products received or desired, including e-mail, voice mail, and other information media

77. 10-77 Case 3: Centralized Business Intelligence A reinventing-the-wheel approach to business intelligence implementations can result in High development costs High support costs Incompatible business intelligence systems A more strategic approach Standardize on fewer business intelligence tools Make them available throughout the organization, even before projects are planned

78. 10-78 Case 3: Centralized Business Intelligence About 10 percent of the 2,000 largest companies have a business intelligence competency center Centralized or virtual Part of the IT department or independent Cost reduction is often the driving force behind creating competency centers and consolidating business intelligence systems Despite the potential savings, funding for creating and running a BI center can be an issue

79. 10-79 Case Study Questions What is business intelligence? Why are business intelligence systems such a popular business application of IT? What is the business value of the various BI applications discussed in the case? Is the business intelligence system an MIS or a DSS?

80. 10-80 Case 4: Robots, the Common Denominator In early 2004, 22 patients underwent complex laparoscopic operations The operations included colon cancer procedures and hernia repairs The primary surgeon was 250 miles away A three-armed robot was used to perform the procedures Left arm, right arm, camera arm

81. 10-81 Case 4: Robots, the Common Denominator Automakers heavily use robotics Ford has a completely wireless assembly factory It also have a completely automated body shop BMW has two wireless plants in Europe and is setting one up in the U.S. Vehicle tracking and material replenishment are automated as well

82. 10-82 Case Study Questions What is the current and future business value of robotics? Would you be comfortable with a robot performing surgery on you? The robotics being used by Ford Motor Co. are contributing to a streamlining of its supply chain What other applications of robots can you envision to improve supply chain management beyond those described in the case?