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Chapter 9

Chapter 9. Decision Support Systems. Learning Objectives. 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.

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Chapter 9

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  1. Chapter 9 Decision Support Systems

  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 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.

  3. 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

  4. Learning Objectives • 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.

  5. Information required at different management levels

  6. 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

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

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

  9. Attributes of Information Quality

  10. 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

  11. 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

  12. DSS components

  13. 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

  14. 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

  15. 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

  16. 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

  17. 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.

  18. 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

  19. 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

  20. 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

  21. 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

  22. 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

  23. 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

  24. 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

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

  26. Robotics • Based in AI, engineering and physiology • Robot machines with computer intelligence and computer controlled, humanlike physical capabilities

  27. 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

  28. 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

  29. 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

  30. Expert System Components

  31. 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

  32. 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)

  33. 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

  34. 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

  35. 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

  36. 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

  37. 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

  38. 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

  39. 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

  40. 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 • NetworkNavigation – 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

  41. 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

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