Mc GrawHillIrwin Copyright 2008 Copyright 2008 by The
Mc. Graw-Hill/Irwin Copyright©© 2008, Copyright 2008 by The. Mc. Graw-Hill. Companies, Inc. Allrightsreserved.
Chapter 10 Decision Support Systems Mc. Graw-Hill/Irwin Copyright © 2008, The Mc. Graw-Hill Companies, Inc. All rights reserved.
Learning Objectives • Identify the changes taking place in the form and use of decision support in business • Identify the role and reporting alternatives of management information systems • 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 10 -3
Learning Objectives • Explain how the following information systems can support the information needs of executives, managers, and business professionals • Executive information systems • Enterprise information portals • Knowledge management systems • Identify how neural networks, fuzzy logic, genetic algorithms, virtual reality, and intelligent agents can be used in business 10 -4
Learning Objectives • Give examples of several ways expert systems can be used in business decision-making situations 10 -5
Decision Support in Business • Companies are investing in data-driven decision support application frameworks to help them respond to • Changing market conditions • Customer needs • This is accomplished by several types of • Management information • Decision support • Other information systems 10 -6
Levels of Managerial Decision Making 10 -7
Information Quality • Information products made more valuable by their attributes, characteristics, or qualities • Information that is outdated, inaccurate, or hard to understand has much less value • Information has three dimensions • Time • Content • Form 10 -8
Attributes of Information Quality 10 -9
Decision Support Systems Management Information Systems Decision Support Systems Decision support provided Provide information about the performance of the organization Provide information and techniques to analyze specific problems Information form and frequency Periodic, exception, demand, and push reports and responses Interactive inquiries and responses Information format Prespecified, fixed format Ad hoc, flexible, and adaptable format Information produced by extraction and manipulation of business data Information produced by analytical modeling of business data Information processing methodology 10 -10
Business Intelligence Applications 10 -11
Decision Support Systems • Decision support systems use the following to support the making of semi-structured business decisions • • Analytical models Specialized databases A decision-maker’s own insights and judgments An interactive, computer-based modeling process • DSS systems are designed to be ad hoc, quick-response systems that are initiated and controlled by decision makers 10 -12
Management Information Systems • The original type of information system that supported managerial decision making • Produces information products that support many day-to-day decision-making needs • Produces reports, display, and responses • Satisfies needs of operational and tactical decision makers who face structured decisions 10 -13
Management Reporting Alternatives • Periodic Scheduled Reports • Prespecified format on a regular basis • Exception Reports • Reports about exceptional conditions • May be produced regularly or when an exception occurs • Demand Reports and Responses • Information is available on demand • Push Reporting • Information is pushed to a networked computer 10 -14
Online Analytical Processing • OLAP • Enables managers and analysts to examine and manipulate large amounts of detailed and consolidated data from many perspectives • Done interactively, in real time, with rapid response to queries 10 -15
Online Analytical Operations • Consolidation • Aggregation of data • Example: data about sales offices rolled up to the district level • Drill-Down • Display underlying detail data • Example: sales figures by individual product • Slicing and Dicing • Viewing database from different viewpoints • Often performed along a time axis 10 -16
Geographic Information Systems • GIS • DSS uses geographic databases to construct and display maps and other graphic displays • Supports decisions affecting the geographic distribution of people and other resources • Often used with Global Positioning Systems (GPS) devices 10 -17
Data Visualization Systems • DVS • Represents complex data using interactive, three-dimensional graphical forms (charts, graphs, maps) • Helps users interactively sort, subdivide, combine, and organize data while it is in its graphical form 10 -18
Using Decision Support Systems • Using a decision support system involves an interactive analytical modeling process • Decision makers are not demanding pre-specified information • They are exploring possible alternatives • What-If Analysis • Observing how changes to selected variables affect other variables 10 -19
Using Decision Support Systems • Sensitivity Analysis • Observing how repeated changes to a single variable affect other variables • Goal-seeking Analysis • Making repeated changes to selected variables until a chosen variable reaches a target value • Optimization Analysis • Finding an optimum value for selected variables, given certain constraints 10 -20
Data Mining • Provides decision support through knowledge discovery • Analyzes vast stores of historical business data • Looks for patterns, trends, and correlations • Goal is to improve business performance • Types of analysis • • • Regression Decision tree Neural network Cluster detection Market basket analysis 10 -21
Market Basket Analysis • One of the most common uses for data mining • Determines what products customers purchase together with other products • Results affect how companies • • • Market products Place merchandise in the store Lay out catalogs and order forms Determine what new products to offer Customize solicitation phone calls 10 -22
Executive Information Systems • EIS • Combines many features of MIS and DSS • Provide top executives with immediate and easy access to information • Identify factors that are critical to accomplishing strategic objectives (critical success factors) • So popular that it has been expanded to managers, analysis, and other knowledge workers 10 -23
Features of an EIS • Information presented in forms tailored to the preferences of the executives using the system • • Customizable graphical user interfaces Exception reports Trend analysis Drill down capability 10 -24
Enterprise Information Portals • An EIP is a Web-based interface and integration of MIS, DSS, EIS, and other technologies • Available to all intranet users and select extranet users • Provides access to a variety of internal and external business applications and services • Typically tailored or personalized to the user or groups of users • Often has a digital dashboard • Also called enterprise knowledge portals 10 -25
Dashboard Example 10 -26
Expert Systems • An Expert System (ES) • A knowledge-based information system • Contain knowledge about a specific, complex application area • Acts as an expert consultant to end users 10 -27
Components of an Expert System • Knowledge Base • Facts about a specific subject area • Heuristics that express the reasoning procedures of an expert (rules of thumb) • Software Resources • An inference engine processes the knowledge and recommends a course of action • User interface programs communicate with the end user • Explanation programs explain the reasoning process to the end user 10 -28
Neural Networks • Computing systems modeled after the brain’s mesh-like network of interconnected processing elements (neurons) • Interconnected processors operate in parallel and interact with each other • Allows the network to learn from the data it processes 10 -29
Fuzzy Logic • Fuzzy logic • Resembles human reasoning • Allows for approximate values and inferences and incomplete or ambiguous data • Uses terms such as “very high” instead of precise measures • Used more often in Japan than in the U. S. • Used in fuzzy process controllers used in subway trains, elevators, and cars 10 -30
Genetic Algorithms • Genetic algorithm software • Uses Darwinian, randomizing, and other mathematical functions • Simulates an evolutionary process, yielding increasingly better solutions to a problem • Being uses to model a variety of scientific, technical, and business processes • Especially useful for situations in which thousands of solutions are possible 10 -31
Virtual Reality (VR) • Virtual reality is a computer-simulated reality • Fast-growing area of artificial intelligence • Originated from efforts to build natural, realistic, multi-sensory human-computer interfaces • Relies on multi-sensory input/output devices • Creates a three-dimensional world through sight, sound, and touch • Also called telepresence 10 -32
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