Managing the Decision Making Process[管理决策过程](PPT-30).ppt

Managing the Decision Making ProcessDr Sherif KamelDepartment of ManagementSchool of Business,Economics and CommunicationCopyright 2005 Sherif KamelCopyright 2002 Turban,McLean and WetherbeOutlineqManagers decision making processqModeling and modelsqManagement support systemsqDecision support systemsqGroup decision support systemsqManaging dataqData warehousesqData martsqData,text and web miningqArtificial intelligenceCopyright 2005 Sherif KamelCopyright 2002 Turban,McLean and WetherbeqManagement is a process by which organizational goals are achieved through the use of resources(people,money,energy,materials,space,time)qThese resources are considered to be inputs,and the attainment of the goals is viewed as the output of the processqManagers oversee this process in an attempt to optimize itManagers and Decision MakingCopyright 2005 Sherif KamelCopyright 2002 Turban,McLean and WetherbeManagers Decision Making ProcessCopyright 2005 Sherif KamelCopyright 2002 Turban,McLean and WetherbeManagers Decision Making ProcessCopyright 2005 Sherif KamelCopyright 2002 Turban,McLean and WetherbeModeling and modelsqA model(in decision making)is a simplified representation or abstraction of realityqWith modeling,one can perform virtual experiments and an analysis on a model of reality,rather than on reality itselfCopyright 2005 Sherif KamelCopyright 2002 Turban,McLean and WetherbeWhy Managers need IT?qMaking decisions while processing information manually is growing increasingly difficult due to the following trendsoNumber of alternatives to be considered is ever increasingoMany decisions must be made under time pressureoDue to increased fluctuations and uncertainty in the decision environment,it is frequently necessary to conduct a sophisticated analysis to make a good decisionoIt is often necessary to access remote information,consult with experts,or have a group decision-making sessionCopyright 2005 Sherif KamelCopyright 2002 Turban,McLean and WetherbeManagement Support SystemsqFour major information technologies have been successfully used to support managersoDSSs-provide support primarily to analytical,quantitative types of decisionsoExecutive(enterprise)support systems-support the informational roles of executivesoGroup decision support systems-support managers working in groupsoIntelligent systems-provide mulitfunctional supportCopyright 2005 Sherif KamelCopyright 2002 Turban,McLean and WetherbeFramework for IT-based DecisionsqStructured problemsoAll phasesintelligence,design,and choiceare structured and the procedures for obtaining the best solution are knownqUnstructured problemsoNone of the three phases(intelligence,design,or choice)is structured,and human intuition is frequently the basis for decision makingqSemistructured problemsoRequires a combination of standard solution procedures and individual judgmentCopyright 2005 Sherif KamelCopyright 2002 Turban,McLean and WetherbeFramework for IT-based DecisionsqStrategic planningolong-range goals and policies for resource allocationqManagement controloacquisition and efficient utilization of resources in the accomplishment of organizational goalsqOperational controloefficient and effective execution of specific tasksCopyright 2005 Sherif KamelCopyright 2002 Turban,McLean and WetherbeDecision Support Systems(DSS)qDecision Support System(DSS)is a computer-based information system that combines models and data in an attempt to solve semistructure problems with extensive user involvementqDSS,like the terms MIS and MSS,means different things to different peopleCopyright 2005 Sherif KamelCopyright 2002 Turban,McLean and Wetherbe.Characteristics of DSSqProvides support for decision makers at all management levels,whether individuals or groups,by bringing together human judgment and objective informationqSupports several interdependent and/or sequential decisionsqSupports all phases of the decision-making process intelligence,design,choice,and implementationas well as a variety of decision-making processes and stylesqIs adaptable by the user over time to deal with changing conditionsCopyright 2005 Sherif KamelCopyright 2002 Turban,McLean and WetherbeDSS ComponentsqData Management Subsystemocontains all the necessary data that flow from several sources and are extracted prior to their entry to a DSS databaseqModel Management Subsystemocontains completed models and models building blocks necessary to develop DSS applications including standard software with financial,statistical,management science,or other quantitative modelsqModel Base Management System(MBMS)ocreates DSS models easily and quickly,either from scratch,existing models,or building blocksCopyright 2005 Sherif KamelCopyright 2002 Turban,McLean and WetherbeDSS ModelCopyright 2005 Sherif KamelCopyright 2002 Turban,McLean and WetherbeGroup Decision Support Systems(GDSS)qGDSS are interactive computer-based systems that facilitates the solution of semistructured and unstructured problems by a group of decision makersqThe goal of GDSS is to improve the productivity of decision-making meetings,either by speeding up the decision-making process or by improving the quality of the resulting decisions,or bothqThe first generation of GDSS was designed to support face2face meetings in what is called a decision roomoGDSS is composed of hardware,software,people and procedures+1 ChauffeurCopyright 2005 Sherif KamelCopyright 2002 Turban,McLean and WetherbeCharacteristics of EISqDrill down capability enables users to get details of any given informationqCritical success factors(CSFs)and key performance indicators are identifiedqTrend analysis can be done using forecasting models,which are included in many ESS/EISqExecutive support systems provide for ad hoc analysis capabilities,in which executives can make specific requests for data analysis as neededCopyright 2005 Sherif KamelCopyright 2002 Turban,McLean and WetherbeExamples of DSSqPriceWaterhouseCoopers offers online DSSs in retailing,financial servicesqMicrosofts Office Small Business edition contains“what-if”wizards that can be used to view the financial impacts of decisions,such as price and inventory decisionsqIBM offers many tools ranging from market-basket analysis to financial and manufacturing decision supportCopyright 2005 Sherif KamelCopyright 2002 Turban,McLean and WetherbeDifficulties of Managing DataqThe amount of data increases exponentiallyqData are scattered throughout organizations and are collected by many individuals using several methods and devicesqOnly small portions of an organizations data are relevant for any specific decisionqAn ever-increasing amount of external data needs to be considered in making organizational decisionsqData are frequently stored in several servers and locations in an organizationoInternetoExternaloPersonaloFormal/informalCopyright 2005 Sherif KamelCopyright 2002 Turban,McLean and WetherbeData WarehousesqThe purpose of a data warehouse is to establish a data repository that makes operational data accessible in a form readily acceptable for analytical processing activitiesqData warehouses include a companion called metadata,meaning data about dataoAbility to reach data quickly,as they are located in one placeoAbility to reach data easily,frequently by end-users themselves,using web browsersCopyright 2005 Sherif KamelCopyright 2002 Turban,McLean and WetherbeData WarehousesCopyright 2005 Sherif KamelCopyright 2002 Turban,McLean and WetherbeCharacteristics of Data WarehousesqOrganization:oData are organized by detailed subjectsqConsistencyoData in different operational databases may be encoded differently.In the warehouse they will be coded in a consistent mannerqTime variantoData are kept for 5 to 10 years so they can be used for trends,forecasting,and comparisons over timeqNon-volatileoOnce entered into the warehouse,data are not updatedqRelationaloData warehouse uses a relational structureqClient/serveroData warehouse uses the client/server to provide the end user an easy access to its dataCopyright 2005 Sherif KamelCopyright 2002 Turban,McLean and WetherbeData Warehouse SuitabilityqLarge amounts of data need to be accessed by end-usersqThe operational data are stored in different systemsqAn information-based approach to management is in useqThere is a large and diverse customer baseqSame data are represented differently in different systemsqData are stored in highly technical formats that are difficult to decipherqExtensive end-user computing is performedCopyright 2005 Sherif KamelCopyright 2002 Turban,McLean and WetherbeData MartsqData marts are an alternative used by many other firms is creation of a lower cost,scaled-down version of a data warehouseCopyright 2005 Sherif KamelCopyright 2002 Turban,McLean and WetherbeData MiningqData mining derives its name from the similarities between searching for valuable business information in a large databaseoGovernmentoMarketingoAirlinesoRetailing and salesoBankingoManufacturing and productionCopyright 2005 Sherif KamelCopyright 2002 Turban,McLean and WetherbeText and Web MiningqText mining is the application of data mining to non-structured or less structured text filesoText mining helps find the“hidden”content of documents,including additional useful relationshipsoGroup documents by common themes.qWeb Mining refers to mining tools used to analyze a large amount of data on the WebCopyright 2005 Sherif KamelCopyright 2002 Turban,McLean and WetherbeData VisualizationqIt refers to the presentation of data by technologies such as digital images,geographical information systems,graphical user interfaces,multidimensional tables and graphs,virtual reality,three-dimensional presentations,and animationCopyright 2005 Sherif KamelCopyright 2002 Turban,McLean and WetherbeKnowledge and Artificial IntelligenceqAI is frequently associated with the concept of knowledgeoKnowledge consists of facts,concepts,theories,procedures,and relationshipsqKnowledge Base represents an organized and stored collection of knowledge related to a specific problem(or an opportunity)to be used in an intelligent systemqOrganizational Knowledge Base is the collection of knowledge related to the operation of an organizationCopyright 2005 Sherif KamelCopyright 2002 Turban,McLean and WetherbeExpert SystemsqExpert systems(ES)are an attempt to imitate human expertsqExpert systems can either support decision makers or completely replace themqExpert systems are the most widely applied and commercially successful AI technologyCopyright 2005 Sherif KamelCopyright 2002 Turban,McLean and WetherbeExpertise and KnowledgeqExpertise is the extensive,task-specific knowledge acquired from training,reading,and experienceqThe transfer of expertise from an expert to a computer and then to the user involves four activitiesoKnowledge acquisition from experts or other sourcesoKnowledge representation in the computeroKnowledge inferencing,resulting in a recommendation for novicesoKnowledge transfer to the userCopyright 2005 Sherif KamelCopyright 2002 Turban,McLean and WetherbeComponents of Expert SystemsqThe knowledge base contains knowledge necessary for understanding,formulating,and solving problemsqThe“brain”of the ES is the inference engine,a computer program that provides a methodology for reasoning and formulating conclusionsqThe user interface allows for user-computer dialogue,which can be best carried out in a natural language,usually presented in a Q&As format and sometimes supplemented by graphicsqThe explanation subsystem can trace responsibility and explain the ESs behavior by interactively answering questionsqA knowledge-refining system enables the system to analyze its performance,learn from it,and improve it for future consultations