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Management Information System

8. Management Information System. Decision Support System. Judi Prajetno Sugiono jpsugiono@gmail.com (2008). Learning Objectives. Identify the changes taking place in the form and use of decision support in e-business enterprises.

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Management Information System

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  1. 8 Management Information System Decision Support System Judi Prajetno Sugiono jpsugiono@gmail.com (2008)

  2. Learning Objectives • Identify the changes taking place in the form and use of decision support in e-business enterprises. • Identify the role and reporting alternatives of management information systems.

  3. Learning Objectives (continued) • 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.

  4. Learning Objectives (continued) • Explain how the following information systems can support the information needs of executives, managers, and business professionals: • Executive information systems • Enterprise information portals • Enterprise knowledge portals

  5. Learning Objectives (continued) • Identify how neural networks, fuzzy logic, genetic algorithms, virtual reality, and intelligent agents can be used in business. • How can expert systems be used in business decision-making situations?

  6. Section I • Decision Support in Business

  7. Business and Decision Support • To succeed, companies need information systems that can support the diverse information and decision-making needs of their managers and business professionals.

  8. Business and Decision Support (continued) • Information, Decisions, & Management • The type of information required by decision makers is directly related to the level of management and the amount of structure in the decision situations.

  9. Business and Decision Support (continued)

  10. Business and Decision Support (continued) • Information Quality • Timeliness • Provided WHEN it is needed • Up-to-date when it is provided • Provided as often as needed • Provided about past, present, and future time periods as necessary

  11. Business and Decision Support (continued) • Information Quality (continued) • Content • Free from errors • Should be related to the information needs of a specific recipient for a specific situation • Provide all the information that is needed • Only the information that is needed should be provided • Can have a broad or narrow scope, or an internal or external focus • Can reveal performance

  12. Business and Decision Support (continued) • Information Quality (continued) • Form • Provided in a form that is easy to understand • Can be provided in detail or summary form • Can be arranged in a predetermined sequence • Can be presented in narrative, numeric, graphic, or other forms • Can be provided in hard copy, video, or other media.

  13. Business and Decision Support (continued)

  14. Business and Decision Support (continued) • Decision Structure • Structured decisions • Involve situations where the procedures to be followed can be specified in advance • Unstructured decisions • Involve situations where it is not possible to specify most of the decision procedures in advance

  15. Business and Decision Support (continued) • Decision structure (continued) • Semistructured decisions • Some decision procedures can be specified in advance, but not enough to lead to a definite recommended decision

  16. Business and Decision Support (continued) • Amount of structure is typically tied to management level • Operational – more structured • Tactical – more semistructured • Strategic – more unstructured

  17. Decision Support Trends • The growth of corporate intranets, extranets and the Web has accelerated the development and use of “executive class” information delivery & decision support software tools to virtually every level of the organization.

  18. Management Information Systems • The original type of information system • Produces many of the products that support day-to-day decision-making • These information products typically take the following forms: • Periodic scheduled reports • Exception reports • Demand reports and responses • Push reports

  19. Management Information Systems (continued) • Management reporting alternatives • Periodic scheduled reports • Prespecified format • Provided on a scheduled basis • Exception reports • Produced only when exceptional conditions occur • Reduces information overload

  20. Management Information Systems (continued) • Management reporting alternatives (continued) • Demand reports and responses • Available when demanded. • Ad hoc • Push reports • Information is sent to a networked PC over the corporate intranet. • Not specifically requested by the recipient

  21. Online Analytical Processing • Enables managers and analysts to interactively examine & manipulate large amounts of detailed and consolidated data from many perspectives • Analyze complex relationships to discover patterns, trends, and exception conditions • Real-time

  22. Online Analytical Processing (continued) • Involves.. • Consolidation • The aggregation of data. • From simple roll-ups to complex groupings of interrelated data • Drill-Down • Display detail data that comprise consolidated data

  23. Online Analytical Processing (continued) • Slicing and Dicing • The ability to look at the database from different viewpoints. • When performed along a time axis, helps analyze trends and find patterns

  24. Decision Support Systems • Computer-based information systems that provide interactive information support during the decision-making process • DSS’s use • Analytical models • Specialized databases • The decision maker’s insights & judgments • An interactive, computer-based modeling process to support making semistructured and unstructured business decisions

  25. Decision Support Systems (continued) • Designed to be ad hoc, quick-response systems that are initiated and controlled by the decision maker • DSS Models and Software • Rely on model bases as well as databases • Might include models and analytical techniques used to express complex relationships

  26. Decision Support Systems (continued) • DSS models and software (continued) • Can combine model components to create integrated models in support of specific types of business decisions

  27. Decision Support Systems (continued) • Geographic Information & Data Visualization Systems • Special categories of DSS that integrate computer graphics with other DSS features • GIS • A DSS that uses geographic databases to construct and display maps and other graphics displays

  28. Decision Support Systems (continued) • Geographic information and data visualization systems (continued) • Data visualization systems • Represent complex data using interactive three-dimensional graphic forms • Helps discover patterns, links, and anomalies

  29. Using Decision Support Systems • An interactive modeling process • Four types of analytical modeling • What-if analysis • Sensitivity analysis • Goal-seeking analysis • Optimization analysis

  30. Using Decision Support Systems (continued) • What-If Analysis • End user makes changes to variables, or relationships among variables, and observes the resulting changes in the values of other variables

  31. Using Decision Support Systems (continued) • Sensitivity Analysis • A special case of what-if analysis • The value of only one variable is changed repeatedly, and the resulting changes on other variables are observed • Typically used when there is uncertainty about the assumptions made in estimating the value of certain key variables

  32. Using Decision Support Systems (continued) • Goal-Seeking Analysis • Instead of observing how changes in a variable affect other variables, goal-seeking sets a target value (a goal) for a variable, then repeatedly changes other variables until the target value is achieved

  33. Using Decision Support Systems (continued) • Optimization Analysis • A more complex extension of goal-seeking • The goal is to find the optimum value for one or more target variables, given certain constraints

  34. Using Decision Support Systems (continued) • Data Mining for Decision Support • Software analyzes vast amounts of data • Attempts to discover patterns, trends, & correlations • May perform regression, decision tree, neural network, cluster detection, or market basket analysis

  35. Executive Information Systems • EIS’s combine many of the features of MIS and DSS • Originally intended to provide top executives with immediate, easy access to information about the firm’s “critical success factors” • Alternative names • Enterprise information systems • Executive support systems

  36. Executive Information Systems (continued) • Features of an EIS • Information presented in forms tailored to the preferences of the users • Most stress use of graphical user interface and graphics displays • May also include exception reporting and trend analysis

  37. Enterprise Portals and Decision Support • A Web-based interface and integration of intranet and other technologies that gives all intranet users and selected extranet users access to a variety of internal & external business applications and services

  38. Enterprise Portals and Decision Support (continued) • Business benefits • More specific and selective information • Easy access to key corporate intranet website resources • Industry and business news • Access to company data for stakeholders • Less time spent on unproductive surfing

  39. Knowledge Management Systems • IT that helps gather, organize, and share business knowledge within an organization • Hypermedia databases that store and disseminate business knowledge. May also be called knowledge bases • Best practices, policies, business solutions • Entered through the enterprise knowledge portal

  40. Section II • Artificial Intelligence Technologies in Business

  41. Business and AI • “Designed to leverage the capabilities of humans rather than replace them,…AI technology enables an extraordinary array of applications that forge new connections among people, computers, knowledge, and the physical world.”

  42. Artificial Intelligence • A field of science and technology based on disciplines such as computer science, biology, psychology, linguistics, mathematics, & engineering • Goal is to develop computers that can think, see, hear, walk, talk, and feel • Major thrust – development of computer functions normally associated with human intelligence – reasoning, learning, problem solving

  43. Artificial Intelligence (continued) • Domains of AI • Three major areas • Cognitive science • Robotics • Natural interfaces

  44. Artificial Intelligence (continued) • Cognitive science • Focuses on researching how the human brain works & how humans think and learn • Applications • Expert systems • Adaptive learning systems • Fuzzy logic systems • Neural networks • Intelligent agents

  45. Artificial Intelligence (continued) • Robotics • Produces robot machines with computer intelligence and computer controlled, humanlike physical capabilities • Natural interfaces • Natural language and speech recognition • Talking to a computer and having it understand • Virtual reality

  46. Neural Networks • Computing systems modeled after the brain’s meshlike network of interconnected processing elements, called neurons • Goal – the neural network learns from data it processes

  47. Fuzzy Logic Systems • A method of reasoning that resembles human reasoning • Allows for approximate values and inferences • Allows for incomplete or ambiguous data • Allows “fuzzy” systems to process incomplete data and provide approximate, but acceptable, solutions to problems

  48. Genetic Algorithms • Uses Darwinian, randomizing, & other mathematical functions to simulate an evolutionary process that can yield increasingly better solutions • Especially useful for situations in which thousands of solutions are possible & must be evaluated

  49. Virtual Reality • Computer-simulated reality • Relies on multisensory input/output devices • Allows interaction with computer-simulated objects, entities, and environments in three dimensions

  50. 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 about a person or process to make decisions and accomplish tasks

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