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Page 1: McLeod CH11

© 2007 by Prentice Hall© 2007 by Prentice Hall Management Information Systems, 10/e RManagement Information Systems, 10/e Raymond McLeod and George Schell aymond McLeod and George Schell

11

Management Management Information Systems, Information Systems,

10/e10/eRaymond McLeod Jr. and George P. Raymond McLeod Jr. and George P.

Schell Schell

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© 2007 by Prentice Hall© 2007 by Prentice Hall Management Information Systems, 10/e RManagement Information Systems, 10/e Raymond McLeod and George Schell aymond McLeod and George Schell

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Chapter 11Chapter 11

Decision Support SystemsDecision Support Systems

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Learning ObjectivesLearning Objectives

►Understand the fundamentals of Understand the fundamentals of decision making and problem solving.decision making and problem solving.

►Know how the decision support system Know how the decision support system (DSS) concept originated.(DSS) concept originated.

►Know the fundamentals of Know the fundamentals of mathematical modeling.mathematical modeling.

►Know how to use an electronic Know how to use an electronic spreadsheet as a mathematical model.spreadsheet as a mathematical model.

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Learning Objectives (Cont’d)Learning Objectives (Cont’d)

►Be familiar with how artificial Be familiar with how artificial intelligence emerged as a computer intelligence emerged as a computer application and know its main areas.application and know its main areas.

►Know the four basic parts of an expert Know the four basic parts of an expert system.system.

►Know what a group decision support Know what a group decision support system (GDSS) is and the different system (GDSS) is and the different environmental settings that can be environmental settings that can be used.used.

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Problem-Solving and Decision Problem-Solving and Decision Making ReviewMaking Review

►Problem solvingProblem solving consists of response consists of response to things going well and also to things to things going well and also to things going badly.going badly.

►ProblemProblem is a condition or event that is is a condition or event that is harmful or potentially harmful to a firm harmful or potentially harmful to a firm or that is beneficial or potentially or that is beneficial or potentially beneficial.beneficial.

►Decision makingDecision making is the act of selecting is the act of selecting from alternative problem solutions.from alternative problem solutions.

►DecisionDecision is a selected course of action. is a selected course of action.

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Problem-Solving PhasesProblem-Solving Phases

►Herbert A. Simon’sHerbert A. Simon’s four basic phases: four basic phases: Intelligence activityIntelligence activity–Searching the –Searching the

environment for conditions calling for a environment for conditions calling for a solution.solution.

Design activityDesign activity–inventing, developing, –inventing, developing, and analyzing possible course of actions.and analyzing possible course of actions.

Choice activityChoice activity–Selecting a particular –Selecting a particular course of action from those available.course of action from those available.

Review activityReview activity–Assessing past choices.–Assessing past choices.

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Frameworks and Systems Frameworks and Systems ApproachApproach

►Problem-solving frameworksProblem-solving frameworks General systems model of the firm.General systems model of the firm. Eight-element environmental model.Eight-element environmental model.

►Systems approach to problem-solving, Systems approach to problem-solving, involves a series of steps grouped into involves a series of steps grouped into three phases–preparation effort, three phases–preparation effort, definition effort, and solution effort.definition effort, and solution effort.

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The Importance of a Systems The Importance of a Systems ViewView

► Systems viewSystems view which regards business operations as which regards business operations as systems embedded within a larger environmental systems embedded within a larger environmental setting; abstract way of thinking; potential value to the setting; abstract way of thinking; potential value to the manager.manager. Prevents the manager from getting lost in the Prevents the manager from getting lost in the

complexity of the organizational structure and details complexity of the organizational structure and details of the job.of the job.

Recognizes the necessity of having good objectives.Recognizes the necessity of having good objectives. Emphasizes the importance of all of the parts of the Emphasizes the importance of all of the parts of the

organization working together.organization working together. Acknowledges the interconnections of the Acknowledges the interconnections of the

organization with its environment.organization with its environment. Places a high value on feedback information that can Places a high value on feedback information that can

only be achieved by means of a closed-loop system.only be achieved by means of a closed-loop system.

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Building on the ConceptsBuilding on the Concepts► Elements of a problem-solving phase.Elements of a problem-solving phase.

Desired stateDesired state–what the system should achieve.–what the system should achieve. Current stateCurrent state–what the system is now achieving.–what the system is now achieving. Solution criterionSolution criterion–difference between the current –difference between the current

state and the desired state.state and the desired state.► Constraints.Constraints.

InternalInternal take the form of limited resources that exist take the form of limited resources that exist within the firm.within the firm.

EnvironmentalEnvironmental take the form of pressures from take the form of pressures from various environmental elements that restrict the flow various environmental elements that restrict the flow of resources into and out of the firm.of resources into and out of the firm.

► When all of these elements exist and the manager When all of these elements exist and the manager understands them, a solution to the problem is possible!understands them, a solution to the problem is possible!

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Figure 11.1 Elements of the Figure 11.1 Elements of the Problem-Solving ProcessProblem-Solving Process

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Selecting the Best SolutionSelecting the Best Solution

►Henry MintzbergHenry Mintzberg, management theorist, , management theorist, has identified three approaches:has identified three approaches:

►AnalysisAnalysis–a systematic evaluation of –a systematic evaluation of options.options.

►JudgmentJudgment–the mental process of a –the mental process of a single manager.single manager.

►BargainingBargaining–negotiations between –negotiations between several managers.several managers.

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Problem vs. SymptomsProblem vs. Symptoms

► SymptomSymptom is a condition produced by the problem. is a condition produced by the problem.► Structured problemStructured problem consists of elements and consists of elements and

relationships between elements, all of which are relationships between elements, all of which are understood by the problem solver.understood by the problem solver.

►Unstructured problemUnstructured problem is one that contains no is one that contains no elements or relationships between elements that elements or relationships between elements that are understood by the problem solver.are understood by the problem solver.

► Semistructured problemSemistructured problem is one that contains is one that contains somesome elements or relationships that are understood elements or relationships that are understood by the problem solver and some that are not.by the problem solver and some that are not.

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Types of DecisionsTypes of Decisions

► Programmed decisionsProgrammed decisions are are “repetitive and “repetitive and routine, to the extent that a definite routine, to the extent that a definite procedure has been worked out for handling procedure has been worked out for handling them so that they don’t have to be treated de them so that they don’t have to be treated de novo (as new) each time they occur.”novo (as new) each time they occur.”

► Nonprogrammed decisionsNonprogrammed decisions are “ are “novel, novel, unstructured, and unusually consequential. unstructured, and unusually consequential. There’s no cut-and-dried method for handling There’s no cut-and-dried method for handling the problem because its precise nature and the problem because its precise nature and structure are elusive or complex, and or structure are elusive or complex, and or because it is so important that it deserves a because it is so important that it deserves a custom-tailored treatment.”custom-tailored treatment.”

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Decision Support SystemsDecision Support Systems

► Gorry and Scott Morton (1971) argued that an Gorry and Scott Morton (1971) argued that an information system that focused on single problems information system that focused on single problems faced by single managers would provide better faced by single managers would provide better support.support.

► Central to their concept was a table, called the Gorry-Central to their concept was a table, called the Gorry-Scott Morton grid (Figure 11.2) that classifies problems Scott Morton grid (Figure 11.2) that classifies problems in terms of problem structure and management level. in terms of problem structure and management level.

► The top level is called the The top level is called the strategic planning levelstrategic planning level, the , the middle level-the middle level-the management control levelmanagement control level, and the , and the lower level-the lower level-the operational control level.operational control level.

► Gorry and Scott Morton also used the term Gorry and Scott Morton also used the term decision decision support system (DSS)support system (DSS) to describe the systems that to describe the systems that could provide the needed support.could provide the needed support.

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Figure 11.2 The Gorry and Scott-Figure 11.2 The Gorry and Scott-Morton GridMorton Grid

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A DSS ModelA DSS Model

► Originally the DSS was conceived to produce periodic Originally the DSS was conceived to produce periodic and special reports (responses to database queries), and special reports (responses to database queries), and outputs from mathematical models.and outputs from mathematical models.

► An ability was added to permit problem solvers to An ability was added to permit problem solvers to work in groups.work in groups.

► The addition of groupware enabled the system to The addition of groupware enabled the system to function as a group decision support system (GDSS).function as a group decision support system (GDSS).

► Figure 11.3 is a model of a DSS. The arrow at the Figure 11.3 is a model of a DSS. The arrow at the bottom indicates how the configuration has expanded bottom indicates how the configuration has expanded over time. over time.

► More recently, artificial intelligence (AI) capability has More recently, artificial intelligence (AI) capability has been added, along with an ability to engage in on-line been added, along with an ability to engage in on-line analytical programming (OLAP).analytical programming (OLAP).

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Figure 11.3 A DSS Model that Figure 11.3 A DSS Model that Incorporates Group Decision Support, Incorporates Group Decision Support,

OLAP, and Artificial IntelligenceOLAP, and Artificial Intelligence

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Mathematical ModelingMathematical Modeling

► ModelModel is an abstraction of something. It represents is an abstraction of something. It represents some object or activity, which is called an some object or activity, which is called an entity.entity.

► There are four basic types of models:There are four basic types of models: Physical modelPhysical model is a three-dimensional is a three-dimensional

representation of its entity. representation of its entity. Narrative modelNarrative model, which describes its entity with , which describes its entity with

spoken or written words. spoken or written words. Graphic modelGraphic model represents its entity with an represents its entity with an

abstraction of lines, symbols, or shapes (Figure abstraction of lines, symbols, or shapes (Figure 11.4).11.4).►Economic order quantity (EOQ)Economic order quantity (EOQ) is the optimum is the optimum

quantity of replenishment stock to order from a supplier. quantity of replenishment stock to order from a supplier. Mathematical modelMathematical model is any mathematical is any mathematical

formula or equation.formula or equation.

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Formula to Compute Economic Formula to Compute Economic Order Quantity (EOQ)Order Quantity (EOQ)

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Figure 11.4 A Graphical Concept Model Figure 11.4 A Graphical Concept Model of the Economic Order Quantityof the Economic Order Quantity

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Uses of ModelsUses of Models

► Facilitate Understanding: Facilitate Understanding: Once a simple model is Once a simple model is understood, it can gradually be made more complex understood, it can gradually be made more complex so as to more accurately represent its entity.   so as to more accurately represent its entity.   

► Facilitate Communication: Facilitate Communication: All four types of All four types of models can communicate information quickly and models can communicate information quickly and accurately.   accurately.   

► Predict the Future:Predict the Future:  The mathematical model can   The mathematical model can predict what might happen in the future but a predict what might happen in the future but a manager must use judgment and intuition in manager must use judgment and intuition in evaluating the output. evaluating the output.

► A mathematical model can be classified in terms of A mathematical model can be classified in terms of three dimensions: the influence of time, the degree three dimensions: the influence of time, the degree of certainty, and the ability to achieve optimization.of certainty, and the ability to achieve optimization.

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Classes of Mathematical Classes of Mathematical ModelsModels

► Static modelStatic model doesn’t include time as a variable doesn’t include time as a variable but deals only with a particular point in time. but deals only with a particular point in time.

► DynamicDynamic modelmodel includes time as a variable; includes time as a variable; it it represents the behavior of the entity over time.represents the behavior of the entity over time.

► Probabilistic modelProbabilistic model includes probabilities. includes probabilities. Otherwise, it is a Otherwise, it is a deterministicdeterministic modelmodel.. ProbabilityProbability is the chance that something will happen. is the chance that something will happen.

► Optimizing modelOptimizing model is one that selects the best is one that selects the best solution among the alternatives. solution among the alternatives.

► SuboptimizingSuboptimizing model (satisficing model)model (satisficing model) does does not identify the decisions that will produce the best not identify the decisions that will produce the best outcome but leaves that task to the manager.outcome but leaves that task to the manager.

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SimulationSimulation► The act of using a model is called The act of using a model is called simulationsimulation while while

the term the term scenarioscenario is used to describe the conditions is used to describe the conditions that influence a simulation.that influence a simulation.

► For example, if you are simulating an inventory For example, if you are simulating an inventory system, as shown in Figure 11.5, the scenario system, as shown in Figure 11.5, the scenario specifies the beginning balance and the daily sales specifies the beginning balance and the daily sales units. units.

► Models can be designed so that the Models can be designed so that the scenario data scenario data elementselements are variables, thus enabling different are variables, thus enabling different values to be assigned.values to be assigned.

► The input values the manager enters to gauge their The input values the manager enters to gauge their impact on the entity are known as impact on the entity are known as decision decision variables.variables.

► Figure 11.5 gives an example of decision variables Figure 11.5 gives an example of decision variables such as order quantity, reorder point, and lead time.such as order quantity, reorder point, and lead time.

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Figure 11.5 Scenario Data and Figure 11.5 Scenario Data and Decision Variables from a Decision Variables from a

SimulationSimulation

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Simulation Technique and Simulation Technique and Format of Simulation OutputFormat of Simulation Output

► The manager usually executes an optimizing The manager usually executes an optimizing model only a single time.model only a single time.

► Suboptimizing models, however, are run over Suboptimizing models, however, are run over and over, in a search for the combination of and over, in a search for the combination of decision variables that produces a satisfying decision variables that produces a satisfying outcome (known as playing the outcome (known as playing the what-if what-if gamegame).).

► Each time the model is run, only one decision Each time the model is run, only one decision variable should be changed, so its influence variable should be changed, so its influence can be seen. can be seen.

► This way, the problem solver systematically This way, the problem solver systematically discovers the combination of decisions discovers the combination of decisions leading to a desirable solution.leading to a desirable solution.

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A Modeling ExampleA Modeling Example► A firm’s executives may use a math model to assist in making A firm’s executives may use a math model to assist in making

key decisions and to simulate the effect of:key decisions and to simulate the effect of:

PricePrice of the product; of the product; Amount of Amount of plant investment;plant investment; Amount to be invested in Amount to be invested in marketing marketing

activity; activity; Amount to be invested in Amount to be invested in R & D.R & D.

► Furthermore, executives want to simulate 4 quarters of activity Furthermore, executives want to simulate 4 quarters of activity and produce 2 reports: an operating statement and an income and produce 2 reports: an operating statement and an income statement.statement.

► Figures 11.6 and 11.7 shows the input screen used to enter the Figures 11.6 and 11.7 shows the input screen used to enter the scenario data elements for the prior quarter and next quarter, scenario data elements for the prior quarter and next quarter, respectively.respectively.

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Figure 11.6 A Model Input Screen for Figure 11.6 A Model Input Screen for Entering Scenario Data for the Prior Entering Scenario Data for the Prior

QuarterQuarter

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Figure 11.7 A Model Input Screen for Figure 11.7 A Model Input Screen for Entering Scenario Data for the Next Entering Scenario Data for the Next

QuarterQuarter

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Model OutputModel Output

► The next quarter’s activity (Quarter 1) is simulated, The next quarter’s activity (Quarter 1) is simulated, and the after-tax profit is displayed on the screen. and the after-tax profit is displayed on the screen.

► The executives then study the figure and decide on The executives then study the figure and decide on the set of decisions to be used in Quarter 2. These the set of decisions to be used in Quarter 2. These decisions are entered and the simulation is decisions are entered and the simulation is repeated. repeated.

► This process continues until all four quarters have This process continues until all four quarters have been simulated. At this point the screen has the been simulated. At this point the screen has the appearance shown in Figure 11.8.appearance shown in Figure 11.8.

► The operating statement in Figure 11.9 and the The operating statement in Figure 11.9 and the income statement in Figure 11.10 are displayed on income statement in Figure 11.10 are displayed on separate screens.separate screens.

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Figure 11.8 Summary Output Figure 11.8 Summary Output from the Modelfrom the Model

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Figure 11.9 The Operating Statement Figure 11.9 The Operating Statement Shows Nonmonetary Results of the Shows Nonmonetary Results of the

SimulationSimulation

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Figure 11.10 The Income Statement Figure 11.10 The Income Statement Shows Monetary Results of the Shows Monetary Results of the

SimulationSimulation

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Modeling Advantages and Modeling Advantages and DisadvantagesDisadvantages

► Advantages:Advantages: The modeling process is a The modeling process is a learning experience.learning experience. The speed of the simulation process enables the The speed of the simulation process enables the

consideration of a larger number of alternatives.consideration of a larger number of alternatives. Models provide a Models provide a predictive powerpredictive power-a look into the future--a look into the future-

that no other information-producing method offers.that no other information-producing method offers. Models are Models are less expensiveless expensive than the trial-and-error method. than the trial-and-error method.

► Disadvantages:Disadvantages: The The difficulty of modeling a business systemdifficulty of modeling a business system will produce a will produce a

model that does not capture all of the influences on the model that does not capture all of the influences on the entity.entity.

A A high degree of mathematical skillhigh degree of mathematical skill is required to develop is required to develop and properly interpret the output of complex models.and properly interpret the output of complex models.

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Mathematical Modeling Using Mathematical Modeling Using Electronic SpreadsheetsElectronic Spreadsheets

► The technological breakthrough that enabled problem The technological breakthrough that enabled problem solvers to develop their own math models was the solvers to develop their own math models was the electronic spreadsheet.electronic spreadsheet.

► Static modelStatic model: Figure 11.11 shows an operating budget in : Figure 11.11 shows an operating budget in column form. The columns are for: the budgeted expenses, column form. The columns are for: the budgeted expenses, actual expenses, and variance, while rows are used for the actual expenses, and variance, while rows are used for the various expense items. various expense items.

► A spreadsheet is especially well-suited for use as a A spreadsheet is especially well-suited for use as a dynamic modeldynamic model. The columns are excellent for the time . The columns are excellent for the time periods, as illustrated in Figure 11.12.periods, as illustrated in Figure 11.12.

► A spreadsheet also lends itself to playing the “what-if” A spreadsheet also lends itself to playing the “what-if” game, where the problem solver manipulates 1 or more game, where the problem solver manipulates 1 or more variables to see the effect on the outcome of the variables to see the effect on the outcome of the simulation.simulation.

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Figure 11.11 Spreadsheet Rows and Figure 11.11 Spreadsheet Rows and Columns Provide the Format for Columns Provide the Format for

Columnar ReportColumnar Report

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Figure 11.12 Spreadsheet Columns Are Figure 11.12 Spreadsheet Columns Are Excellent for Time Periods in a Dynamic Excellent for Time Periods in a Dynamic

ModelModel

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Spreadsheet Model InterfaceSpreadsheet Model Interface

► When using a spreadsheet as a mathematical model, When using a spreadsheet as a mathematical model, the user can enter data or make changes directly to the user can enter data or make changes directly to the spreadsheet cells, or by using a GUI. the spreadsheet cells, or by using a GUI.

► The pricing model described earlier in Figures 11.6-The pricing model described earlier in Figures 11.6-11.10 could have been developed using a 11.10 could have been developed using a spreadsheet, and had the graphical user interface spreadsheet, and had the graphical user interface added. added.

► The interface could be created using a programming The interface could be created using a programming language such as Visual Basic and would likely language such as Visual Basic and would likely require an information specialist to develop.require an information specialist to develop.

► A development approach would be for the user to A development approach would be for the user to develop the spreadsheet and then have the interface develop the spreadsheet and then have the interface added by an information specialist.added by an information specialist.

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Artificial IntelligenceArtificial Intelligence

► Artificial intelligence (AI)Artificial intelligence (AI) is the activity of is the activity of providing such machines as computers with the providing such machines as computers with the ability to display behavior that would be regarded ability to display behavior that would be regarded as intelligent if it were observed in humans. as intelligent if it were observed in humans.

► AI is being applied in business in AI is being applied in business in knowledge-knowledge-based systemsbased systems, which use human knowledge to , which use human knowledge to solve problems.solve problems.

► The most popular type of knowledge-based system The most popular type of knowledge-based system are are expert systemsexpert systems, which are computer , which are computer programs that try to represent the knowledge of programs that try to represent the knowledge of human experts in the form of heuristics.human experts in the form of heuristics.

► These heuristics allow an expert system to consult These heuristics allow an expert system to consult on how to solve a problem: called a consultationon how to solve a problem: called a consultation--the user consults the expert system for advice.the user consults the expert system for advice.

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Areas of AIAreas of AI

► Expert systemExpert system is a computer program that is a computer program that attempts to represent the knowledge of attempts to represent the knowledge of human experts in the form of heuristics.human experts in the form of heuristics.

►HeuristicHeuristic is a rule of thumb or a rule of is a rule of thumb or a rule of good guessing.good guessing.

► ConsultationConsultation is the act of using an expert is the act of using an expert system.system.

►Knowledge engineerKnowledge engineer has special expertise has special expertise in artificial intelligence; adept in obtaining in artificial intelligence; adept in obtaining knowledge from the expert.knowledge from the expert.

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Areas of AI (Cont’d)Areas of AI (Cont’d)

►Neural networksNeural networks mimic the mimic the physiology of the human brain.physiology of the human brain.

►Genetic algorithmsGenetic algorithms apply the apply the “survival of the fittest” process to “survival of the fittest” process to enable problem solvers to produce enable problem solvers to produce increasingly better problem solutions.increasingly better problem solutions.

►Intelligent agentsIntelligent agents are used to are used to perform repetitive computer-related perform repetitive computer-related tasks; i.e., data mining.tasks; i.e., data mining.

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The Expert System The Expert System ConfigurationConfiguration

►User interfaceUser interface enables the manager to enables the manager to enter instructions and information into the enter instructions and information into the expert system and to receive information expert system and to receive information from it.from it.

►Knowledge baseKnowledge base contains both facts that contains both facts that describe the problem area and knowledge describe the problem area and knowledge representation techniques that describe how representation techniques that describe how the facts fit together in a logical manner.the facts fit together in a logical manner.

► Problem domainProblem domain is used to describe the is used to describe the problem area.problem area.

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The Expert System The Expert System Configuration (Cont’d)Configuration (Cont’d)

►RuleRule specifies what to do in a given specifies what to do in a given situation and consists of two parts:situation and consists of two parts: A cA conditionondition that may or may not be true, and that may or may not be true, and An An actionaction to be taken when the condition is true. to be taken when the condition is true.

► Inference engine is the portion of the expert Inference engine is the portion of the expert system that performs reasoning by using system that performs reasoning by using the contents of the knowledge base in a the contents of the knowledge base in a particular sequence.particular sequence.

►Goal variableGoal variable is assigning a value to the is assigning a value to the problem solution.problem solution.

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The Expert System The Expert System Configuration (Cont’d)Configuration (Cont’d)

► Expert system shellExpert system shell is a ready-made is a ready-made processor that can be tailored to a specific processor that can be tailored to a specific problem domain through the addition of the problem domain through the addition of the appropriate knowledge base.appropriate knowledge base.

► Case-based reasoningCase-based reasoning ( (CBRCBR) uses ) uses historical data as the basis for identifying historical data as the basis for identifying problems and recommending solutions.problems and recommending solutions.

►Decision treeDecision tree is a network-like structure is a network-like structure that enables the user to progress from the that enables the user to progress from the root through the network of branches by root through the network of branches by answering questions relating to the problem. answering questions relating to the problem.

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Figure 11.13 An Expert System Figure 11.13 An Expert System ModelModel

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Group Decision Support Group Decision Support SystemSystem

►Group decision support systemGroup decision support system ( (GDSSGDSS) is “a ) is “a computer-based system that supports groups of computer-based system that supports groups of people engaged in a common task (or goal) and people engaged in a common task (or goal) and that provides an interface to a shared that provides an interface to a shared environment”.environment”.

► Aliases Aliases group support systemgroup support system ( (GSSGSS), ), computer-supported cooperative workcomputer-supported cooperative work ((CSCWCSCW), ), computerized collaborative workcomputerized collaborative work supportsupport, and , and electronic meeting systemelectronic meeting system ((EMSEMS).).

►GroupwareGroupware the software used in these settings. the software used in these settings.► Improved communications make possible Improved communications make possible

improved decisions.improved decisions.

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GDSS Environmental SettingsGDSS Environmental Settings

► Synchronous exchangeSynchronous exchange when members meet at when members meet at the same time. the same time.

► Asynchronous exchange Asynchronous exchange when members meet at when members meet at different times.different times.

► Decision roomDecision room is the setting for small groups of is the setting for small groups of people meeting face-to-face.people meeting face-to-face.

► FacilitatorFacilitator is the person whose chief task is to is the person whose chief task is to keep the discussion on track.keep the discussion on track.

► Parallel communicationParallel communication is when all participants is when all participants enter comments at the same time. enter comments at the same time.

► Anonymity Anonymity is is when nobody is able to tell who when nobody is able to tell who entered a particular comment; participants say entered a particular comment; participants say what they REALLY think without fearwhat they REALLY think without fear..

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Figure 11.14 Group Size and Location Figure 11.14 Group Size and Location Determine DSS Environmental SettingsDetermine DSS Environmental Settings

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GDSS Environmental Settings GDSS Environmental Settings (Cont’d)(Cont’d)

► Local area decision network-Local area decision network-when it is impossible when it is impossible for small groups of people to meet face-to-face, the for small groups of people to meet face-to-face, the members can interact by means of a local area members can interact by means of a local area network, or LAN.network, or LAN.

► Legislative session-Legislative session-when the group is too large for a when the group is too large for a decision room.decision room. Imposes certain constraints on communications such as equal Imposes certain constraints on communications such as equal

participation by each member is removed or less time is participation by each member is removed or less time is available.available.

► Computer-mediated conference-Computer-mediated conference-several virtual several virtual office applications permit communication between office applications permit communication between large groups with geographically dispersed members.large groups with geographically dispersed members. Teleconferencing applicationsTeleconferencing applications include computer conferencing, include computer conferencing,

audio conferencing, and videoconferencing.audio conferencing, and videoconferencing.