Chapter 10 Decision Support Systems

1. Chapter 10 Decision Support Systems James A. O'Brien, and George Marakas. ManagementInformation Systems with MISource 2007, 8th ed.  Boston, MA: McGraw-Hill, Inc., 2007.  ISBN: 13 9780073323091

2. Learning Objectives • Identify the changes taking place in the form and use of decision support in business • Identify the role and reporting alternatives of MIS • Describe how online analytical processing can meet key information needs of managers • Explain the decision support system concept and how it differs from traditional MIS • Explain how the following IS can support the information needs of executives, managers, and business professionals: Executive information systems, Enterprise information portals, and Knowledge management systems • Identify how neural networks, fuzzy logic, genetic algorithms, virtual reality, and intelligent agents can be used in business • Give examples of several ways expert systems can be used in business decision-making situations Chapter 10 Decision Support Systems

3. 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 Chapter 10 Decision Support Systems

4. 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 Chapter 10 Decision Support Systems

5. 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? • What are several reasons for criticism of the use of dashboards by executives? • Do you agree with any of this criticism? Chapter 10 Decision Support Systems

6. Levels of Managerial Decision Making Chapter 10 Decision Support Systems

7. 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 Chapter 10 Decision Support Systems

8. Attributes of Information Quality Chapter 10 Decision Support Systems

9. 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 Chapter 10 Decision Support Systems

10. Decision Support Systems Chapter 10 Decision Support Systems

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

12. Business Intelligence Applications Chapter 10 Decision Support Systems

13. 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 Chapter 10 Decision Support Systems

14. DSS Components Chapter 10 Decision Support Systems

15. 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 Chapter 10 Decision Support Systems

16. 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 Chapter 10 Decision Support Systems

17. 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 Chapter 10 Decision Support Systems

18. 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 Chapter 10 Decision Support Systems

19. 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 Chapter 10 Decision Support Systems

20. 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 Chapter 10 Decision Support Systems

21. Geographic Information Systems • 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 Chapter 10 Decision Support Systems

22. Data Visualization Systems • 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 Chapter 10 Decision Support Systems

23. 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 • 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 Chapter 10 Decision Support Systems

24. 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 Chapter 10 Decision Support Systems

25. Analysis of Customer Demographics Chapter 10 Decision Support Systems

26. 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 Chapter 10 Decision Support Systems

27. Executive Information Systems • 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 Chapter 10 Decision Support Systems

28. 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 Chapter 10 Decision Support Systems

29. 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 Chapter 10 Decision Support Systems

30. Dashboard Example Chapter 10 Decision Support Systems

31. Enterprise Information Portal Components Chapter 10 Decision Support Systems

32. Enterprise Knowledge Portal Chapter 10 Decision Support Systems

33. 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 Chapter 10 Decision Support Systems

34. 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 Chapter 10 Decision Support Systems

35. 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? • 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? Chapter 10 Decision Support Systems

36. 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 Chapter 10 Decision Support Systems

37. 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 • Respond quickly and successfully to new situations • Recognize the relative importance of elements in a situation • Handle ambiguous, incomplete, or erroneous information Chapter 10 Decision Support Systems

38. Domains of Artificial Intelligence Chapter 10 Decision Support Systems

39. 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 Chapter 10 Decision Support Systems

40. 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 Chapter 10 Decision Support Systems

41. 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 Chapter 10 Decision Support Systems

42. 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 Chapter 10 Decision Support Systems

43. 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 Chapter 10 Decision Support Systems

44. 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 Chapter 10 Decision Support Systems

45. 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 Chapter 10 Decision Support Systems

46. Components of an Expert System Chapter 10 Decision Support Systems

47. 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 Chapter 10 Decision Support Systems

48. 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) Chapter 10 Decision Support Systems

49. 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 Chapter 10 Decision Support Systems

50. 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 Chapter 10 Decision Support Systems