Chapter10

Introduction to Information Technology Turban, Rainer and Potter John Wiley & Sons, Inc.Copyright 2005

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Managerial Support Systems

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Chapter Outline

Managers and decision making Decision support systemsEnterprise and executive decision support Intelligent support systems: the basicsExpert systemsOther intelligent systems

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Learning ObjectivesDescribe the concepts of management, decision making and computerized support for decision making.Describe decision support system (DSSs) and their benefits, and describe the structure of DSSs.Describe computerized support for group decision making Describe organizational decision support and executive support systems.Describe artificial intelligence (AI).Define an expert system and its components Describe natural language processing and natural language generation. Describe artificial neural networks ( ANNs) and their major applications.

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10.1 Managers and Decision Making

Management is a process by which organizational goals are achieved through the use of resource (people, money, energy, materials, space, time) . These resources are considered to be inputs; the attainment of the goals is viewed as the output of the process. The ratio between inputs and outputs is an indication of the organization’s productivity.

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The Manager’s Job

Manager have three basic role (Mintzberg 1973) :

Interpersonal roles:: figurehead, leader, liaisonInformational roles: monitor, disseminator, spokespersonDecisional roles: entrepreneur, disturbance handler, resource allocator, negotiator.

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Decision Making

A decision refers to a choice made between two alternatives.

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The process and phases in decision making

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Model ( in decision making )

Model is a simplified representation, or abstraction of realityThe benefits of modeling in decision making are:

The cost of virtual experimentation is much lower than the cost of experimentation conducted with a real system.Models allow for the simulated compression of time. Years of operation can be simulated in seconds of computer timeManipulating the model ( by changing variable ) is much easier than manipulating the real system. Modeling allows a manager to better deal with the uncertainly by introducing many “ what- ifs” and calculating the risks involved in specific actions.

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Why Manager Need IT Support

A key to good decision making is to explore and compare many relevant alternatives. The more alternatives that exist, the more computer-assisted search and comparison are needed.Typically, decisions must be made under time pressure. Frequently it is not possible to manually process the needed information fast enough to be effective. It is usually necessary to conduct a sophisticated analysis in order to make a good decision. Such analysis requires the use of modeling.Decision makers can be in different locations and so is the information. Bringing them all together quickly and inexpensively may be a difficult task.

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Management Support Systems (MSSs)

Major IT technologies designed to support managers; decision support systems, executive support systems, groupware technologies and intelligent system.

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Decision Support Framework.

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10.2 Decision Support Systems(DSS)

A computer-based information system that combines models and data in an attempt to solve semi-structured and some unstructured problems with extensive user involvement.

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Characteristics and Capabilities of DSSs

Sensitivity analysis. The study of the impact that changes in one (or more) parts of a model have on other parts.What-if analysis. The study of the impact of a change in the assumptions (input data) on the proposed solution.Goal-seeking analysis. Study that attempts to find the value of the inputs necessary to achieve a desired level of output.

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Structure and Components of DSS.

Data management subsystem Model management subsystem User interfaceUsersKnowledge- based subsystems

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The DSS and its Computing Environment

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Emerging Types of DSS

Frontline decision making. The process by which companies automate decision process and push them down into the organization and sometimes out to partners.Real- Time Decision Support. The systems that supports business decisions that must be made at the right time and frequently under time pressure.

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Group Decision Support Systems

Virtual group. A group whose members are in different locations.Group decision support system (GDSS). An interactive computer-based system that supports the process of finding solutions by a group of decision makers. Decision room. A face- to-face setting for a group DSS, in which terminals are available to the participants.

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10.3 Enterprise and Executive Decision Support Systems

Organizational decision support system (ODSS): A DSS that focuses on an organizational task or activity involving a sequence of operations and decision makers.Executive information system (EIS): A computer-based technology designed in response to the specific needs of executive support system (ESS).

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The Capabilities of an ESS Capability Description

Drill- down Ability to go to details, at several levels; can be done by a series of menus or by direct queries (Using intelligent and natural language processing )

The factors most critical for the success of business. These can be organizational, industry departmental, etc.

The specific measures of CSFs. Example are provided in online file W10.6.

The latest data available on KPI or some other metric, ideally in real time.

Trend analysis Short, medium, and long–term trend of KPIs or metrics, which are projected using forecasting methods.

Ad-hoc analysis Analysis made any time. Upon demand and with any desired factors and relationships.

Exception reporting Report that highlight deviations larger than certain thresholds. Reports may include only deviations. Based on the concept of management by exception.

Critical success factors (CSF)

Key performance indicators (KPIs)

Status access

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10.4 Intelligent Support Systems: The Basics Intelligent support systems is a term that describes the

various commercial applications of artificial intelligence (AI).

Artificial intelligence (AI). A subfield of computer science concerned with studying the thought processes of humans and representing those processes via machines.Turning test. A test for artificial intelligence, in which a human interviewer, conversing with both an unseen human being and an unseen computer, cannot determine which is which; named for English mathematician Alan Turing.

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The Capabilities of an ESS Capability Natural Intelligence Artificial Intelligence

Perishable from an organizational point of view Permanent

Difficult, expensive, takes times Easy, fast and inexpensive once knowledge is in computer

Consistent and thorough

Fairly easy, inexpensive

Low, uninspired

Must be interpreted first; Limited

Machine learning still not as good as people in most cases, but in some cases can do better than people

Reasoning Making use of wide context of experiences

Good only in narrow, focused and stable domains

Can be erratic and inconsistent, incomplete at times

Difficult, expensive

Creativity Can be very high

Use of sensory experiences Direct and rich in possibilities

Recognizing patterns and relationship Fast, easy to explain

Preservation of knowledge

Duplication and dissemination of knowledge

Total cost of knowledge

Documentability of process and knowledge

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The Intelligent Systems Name Short Description

Expert System (ES) Computerized advisory systems usually based on rules

Enables computers to recognize and even understand human languages

Enables computers to recognized words and understand short voice sentences.

Programmable combination of mechanical and computer program. Recognize their environments via sensors.

Computer vision and scene recognition Enable computers to interpret the content of pictures captured by cameras.

Machine learning Enables computer to interpret the content of pictures captured by sensors ( see next three items)

Handwriting recognition Enables computers to recognized characters (letter, digits) written by hand.

Neural computing (networks) Using massive parallel processing, able to reorganize patterns in large amount of data.

Fuzzy logic Enables computers to reason with partial information

Intelligent agents Software programs that perform tasks for a human or machine master

Semantic web An intelligent software program that “ understands” content of web pages.

Natural Language Processing (NLP)

Speech understanding

Robotic and sensory systems

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10.5 Expert Systems (ES)

A computer system that attempts to mimic human experts by applying reasoning methodologies or knowledge in a specific domain.

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Expertise and knowledge

Expertise is the extensive, task-specific knowledge acquired from training, reading and experience. The transfer of expertise froman expert to computer and then to the user involves four activities:

Knowledge acquisition: Knowledge is from experts or from documented sources.Knowledge representation: Acquired knowledge is organized as rules or frames (objective-oriented) and stored electronically in a knowledge base.Knowledge inferencing: Given the necessary expertise stored in the knowledge base, the computer is programmed so that it can make inferences. The reasoning function is performed in a component called the inference engine, which is the brain of ES.Knowledge transfer: The inferenced expertise is transferred to the user in the form of a recommendation.

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Benefits of Expert Systems Benefit Description

Increased output and productivity ESs can configure for each custom order. Increasing production capabilities

ESs can provide consistent advise and reduce error rates.

Expertise from anywhere in the world can be obtained and used.

Sensors can collect information that an ES interprets, enabling human workers to avoid hot, humid, or toxic environments.

Accessibility to knowledge and help desks

ESs can increase the productivity of help – desk employee, or even automate this function.

Reliability ESs do not become tired or bored, call in sick or go on strike. They consistently pay attention to details.

Ability to work with incomplete or uncertain information

Even with answer of ‘ don’t know ‘ an ES can produce an answer, though it may not be a definite one.

Provision of training The explanation facility of an ES can serve as a teaching device and knowledge base for novices.

Enhancement of decision-making and problem-solving capabilities

ESs allow the integration of expert judgment into analysis (e.g., diagnosis of machine malfunction and even medical diagnosis).

Decreased decision-making time ESs usually can make faster decision than humans working alone.

Reduce downtime ESs can quickly diagnose faster decisions than humans and prescribe repairs.

Increased quality

Capture and dissemination of scarce expertise

Operation in hazardous environments

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The Components of Expert Systems

Knowledge base Inference engineUser interfaceBlackboardExplanation subsystem

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Structure and Process of an ES

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Ten Generic Categories of Expert Systems

Category Problem Addressed

Interpretation Inferring situation description from observations.

Inferring likely consequence of given situation.Inferring system malfunctions from observations.

Design Configuring objects under constraints.Developing plans to achieve goals.

Monitoring Comparing observations to plans, flagging exceptions.Debugging Prescribing remedies for malfunction.

Repair Executing a plan to administer a prescribed remedy.

Instruction Diagnosing , debugging, and correcting student performance

Control Interpreting, predicting, repairing and monitoring system behavior

Prediction Diagnosis

Planning

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10.6 Other Intelligent Systems

Natural language processing (NLP): Communicatngwith a computer in English or whatever language you may speak. Natural language understanding/speech (voice) recognition: The ability of a computer to comprehend instructions given in ordinary language, via the keyboard or by voice.Natural language generation/voice synthesis. Technology that enables computers to produce ordinary language, by “voice” or on the screen, so that people can understand computers more easily.

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Artificial Neural Networks (ANNs): Computer technology, modeled after concepts from biological neural systems, that attempts to simulate massively parallel processing of interconnected elements in a network architecture.Neural computing:. The application of artificial neural network technology.Pattern recognition:. The ability of a neural network to establish patterns and characteristics in situation where the logic or rules are not known, by analyzing large quantities of data.Fuzzy logic: . Computer reasoning that deal with uncertainties by simulating the process of human reasoning.

Other Intelligent Systems cont…

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