Bài giảng Information Systems in Business - Chapter 10 Supporting Decision Making

Supporting Decision MakingChapter10McGraw-Hill/IrwinCopyright © 2011 by The McGraw-Hill Companies, Inc. All rights reserved.Identify the changes taking place in the form and use of decision support in businessIdentify the role and reporting alternatives of management information systemsDescribe how online analytical processing can meet key information needs of managersExplain the decision support system concept and how it differs from traditional management information systemsLearning ObjectivesExplain how the following information systems can support the information needs of executives, managers, and business professionalsExecutive information systemsEnterprise information portalsKnowledge management systemsIdentify how neural networks, fuzzy logic, genetic algorithms, virtual reality, and intelligent agents can be used in businessLearning ObjectivesGive examples of several ways expert systems can be used in business decision-making situationsLearning ObjectivesDecision StructureStructured (operational)Procedures can be specified in advanceUnstructured (strategic)Not possible to specify procedures in advance Semi-structured (tactical)Decision procedures can be pre-specified, but not enough to lead to the correct decisionData MiningProvides decision support through knowledge discoveryAnalyzes vast stores of historical business dataLooks for patterns, trends, and correlationsGoal is to improve business performanceTypes of analysisRegressionDecision treeNeural networkCluster detectionMarket basket analysisMarket Basket AnalysisOne of the most common uses for data miningDetermines what products customers purchase together with other productsOther usesCross Selling Product PlacementAffinity PromotionSurvey Analysis Fraud DetectionAnalyze Customer Behavior Executive Information Systems (EIS)Combines many features of MIS and DSSProvides immediate and easy informationIdentifies critical success factorsFeaturesCustomizable graphical user interfacesException reportsTrend analysisDrill down capabilityBenefits of Expert SystemsCaptures human experience in a computer-based information systemLimitations of Expert SystemsLimited focusInability to learnMaintenance problemsDevelopment costCan only solve specific types of problems in a limited domain of knowledgeKnowledge EngineeringA knowledge engineerWorks with experts to capture the knowledge they possessFacts and rules of thumbBuilds the knowledge baseif necessary, the rest of the expert systemSimilar role to systems analysts10-10Neural NetworksModeled after the brain’s mesh-like network of interconnected processing elements (neurons)Interconnected processors operate in parallel and interact with each otherAllows the network to learn from the data it processesGenetic AlgorithmsGenetic algorithm software Uses Darwinian, randomizing, and other mathematical functionsSimulates an evolutionary process, yielding increasingly better solutions to a problemUsed to model a variety of scientific, technical, and business processesUseful when thousands of solutions are possibleVirtual Reality (VR)Virtual reality is a computer-simulated realityFast-growing area of artificial intelligenceOriginated from efforts to build natural, realistic, multi-sensory human-computer interfacesRelies on multi-sensory input/output devicesCreates a three-dimensional world through sight, sound, and touchTelepresenceUsing VR to perform a task in a different locationIntelligent AgentsSoftware surrogate for an end user or a process that fulfills a stated need or activityUses built-in and learned knowledge base to accomplish tasks Software robots or botsTypes of Intelligent AgentsUser Interface AgentsInterface Tutors Presentation AgentsNetwork Navigation AgentsRole-Playing AgentsInformation Management AgentsSearch Agents Information BrokersInformation Filters