© Prentice Hall 2002 6.1 CHAPTER 6 Managerial Support Systems.

6.1

© Prentice Hall 2002

CHAPTER 6CHAPTER 6

Managerial Support Managerial Support

Systems Systems

6.2


MANAGERIAL SUPPORT MANAGERIAL SUPPORT SYSTEMSSYSTEMS

• DECISION SUPPORT SYSTEMSDECISION SUPPORT SYSTEMS• DATA MININGDATA MINING• GROUP SUPPORT SYSTEMSGROUP SUPPORT SYSTEMS• GEOGRAPHIC INFO SYSTEMSGEOGRAPHIC INFO SYSTEMS• EXECUTIVE INFO SYSTEMSEXECUTIVE INFO SYSTEMS• EXPERT SYSTEMSEXPERT SYSTEMS• NEURAL NETWORKSNEURAL NETWORKS• VIRTUAL REALITYVIRTUAL REALITY

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6.3


DECISION SUPPORT SYSTEMSDECISION SUPPORT SYSTEMS

• COMPUTER-BASED SYSTEM, COMPUTER-BASED SYSTEM, USUALLY INTERACTIVE, DESIGNED USUALLY INTERACTIVE, DESIGNED TO ASSIST MANAGERS IN MAKING TO ASSIST MANAGERS IN MAKING DECISIONSDECISIONS

• INCORPORATES BOTH DATA AND INCORPORATES BOTH DATA AND MODELS, INTENDED TO ASSIST IN MODELS, INTENDED TO ASSIST IN THE SOLUTION OF SEMI- OR THE SOLUTION OF SEMI- OR UNSTRUCTURED PROBLEMSUNSTRUCTURED PROBLEMS

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6.4


DSSDSS COMPONENTS COMPONENTS

• MODEL MANAGEMENT: MODEL MANAGEMENT: Helps Helps user determine appropriate user determine appropriate analytic toolsanalytic tools

• DATA MANAGEMENT: DATA MANAGEMENT: Provides Provides access to select, handle dataaccess to select, handle data

• USER INTERFACE: USER INTERFACE: Allows user to Allows user to interact with systeminteract with system

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6.5


TYPICAL TYPICAL DSSDSS APPLICATIONS APPLICATIONS

• PROFIT & LOSS MODELPROFIT & LOSS MODEL• MACHINE LOADING OF MACHINES MACHINE LOADING OF MACHINES

IN A JOB SHOPIN A JOB SHOP• COST/BENEFIT ANALYSISCOST/BENEFIT ANALYSIS• PRO FORMA FINANCIAL PRO FORMA FINANCIAL

STATEMENTSTATEMENT• ““WHAT-IF” ANALYSISWHAT-IF” ANALYSIS

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6.6


DATA MININGDATA MINING

EMPLOYS TECHNIQUES (SUCH AS EMPLOYS TECHNIQUES (SUCH AS DECISION TREES OR NEURAL DECISION TREES OR NEURAL NETWORKS) TO SEARCH OR “MINE” NETWORKS) TO SEARCH OR “MINE” FOR SMALL “NUGGETS” OF FOR SMALL “NUGGETS” OF INFORMATION FROM VAST INFORMATION FROM VAST QUANTITIES OF DATA STORED IN QUANTITIES OF DATA STORED IN AN ORGANIZATION’S DATA AN ORGANIZATION’S DATA WAREHOUSEWAREHOUSE

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6.7


DATA MINING TECHNIQUESDATA MINING TECHNIQUES

• ONLINE ANALYTICAL PROCESSING: ONLINE ANALYTICAL PROCESSING: Human-driven analysis querying a Human-driven analysis querying a database with specific criteriadatabase with specific criteria

• DECISION TREES DECISION TREES • NEURAL NETWORKSNEURAL NETWORKS• MATHEMATICAL PROGRAMMINGMATHEMATICAL PROGRAMMING• STATISTICAL ANALYSISSTATISTICAL ANALYSIS

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6.8


USES OF DATAMININGUSES OF DATAMININGAPPLICATION DESCRIPTION

CROSS-SELLING TAILOR SALES TO CUSTOMER SEGMENTS

CUSTOMER CHURN PREDICT RISK OF LOSING CUSTOMERS

CUSTOMER RETENTION DETERMINE LONG TERM CUSTOMERS

DIRECT MARKETING IDENTIFY, TARGET MOST LIKELY PROSPECTS

FRAUD DETECTION IDENTIFY FRAUDULENT TRANSACTIONS

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USES OF DATAMININGUSES OF DATAMININGAPPLICATION DESCRIPTION

INTERACTIVE MARKETING PREDICT CUSTOMER'S WEB DESIRES

MARKET BASKET ANALYSIS WHAT ITEMS COMMONLY PURCHASED TOGETHER?

MARKET SEGMENTATION SEGMENT CUSTOMERS INTO APPROPRIATE GROUPS

PAYMENT OR DEFAULT ANALYSIS WHY DO CUSTOMERS DEFAULT ON PAYMENTS?

TREND ANALYSIS DETECT CHANGE IN SALES PATTERNS OVER TIME

6.10


GROUP SUPPORT SYSTEMS GROUP SUPPORT SYSTEMS (GPS)(GPS)

• SYSTEM DESIGNED TO MAKE GROUP SYSTEM DESIGNED TO MAKE GROUP SESSIONS MORE PRODUCTIVE: SESSIONS MORE PRODUCTIVE: Brainstorming, issue structuring, Brainstorming, issue structuring, voting, conflict resolutionvoting, conflict resolution

• A VARIANT OF A VARIANT OF DSSDSS IN WHICH THE IN WHICH THE SYSTEM IS DESIGNED TO SUPPORT A SYSTEM IS DESIGNED TO SUPPORT A GROUPGROUP

• A SPECIALIZED TYPE OF GROUPWAREA SPECIALIZED TYPE OF GROUPWARE

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6.11


GSSGSS CHARACTERISTICS CHARACTERISTICS

• PARALLEL HUMAN PROCESSINGPARALLEL HUMAN PROCESSING• EQUAL OPPORTUNITY FOR EQUAL OPPORTUNITY FOR

PARTICIPATIONPARTICIPATION• ANONYMITYANONYMITY• COMPLETE RECORD OF MEETINGCOMPLETE RECORD OF MEETING• OUTPUT OF ONE PHASE LEADS TO OUTPUT OF ONE PHASE LEADS TO

NEXTNEXT• CAN MORE EASILY APPLY STRUCTURECAN MORE EASILY APPLY STRUCTURE

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6.12


GEOGRAPHIC INFORMATION GEOGRAPHIC INFORMATION SYSTEMS SYSTEMS (GIS)(GIS)

• A COMPUTER-BASED SYSTEM A COMPUTER-BASED SYSTEM DESIGNED TO COLLECT, STORE, DESIGNED TO COLLECT, STORE, RETRIEVE, MANIPULATE, AND RETRIEVE, MANIPULATE, AND DISPLAY SPATIAL DATADISPLAY SPATIAL DATA

• A SPATIALLY BASED A SPATIALLY BASED DSSDSS• TYPICALLY A DIGITIZED MAP WITH TYPICALLY A DIGITIZED MAP WITH

OTHER DATA LINKED TO THE MAP OTHER DATA LINKED TO THE MAP COORDINATESCOORDINATES

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6.13


TWO TYPES OF TWO TYPES OF GISGIS

• RASTER RASTER – Grids of equal-sized cells grouped

or linked to make lines and shapes– Values of cells vary– Example: Satellite images, pixels on screen

• VECTORVECTOR– Points, Lines, and Polygons– Approximates curves, can link into networks– Example: Property boundaries, sales territories

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6.14


GISGIS COVERAGE MODEL COVERAGE MODEL

• WHAT IS ADJACENT TO FEATURE?WHAT IS ADJACENT TO FEATURE?• WHICH IS NEAREST SITE?WHICH IS NEAREST SITE?• WHAT DOES AREA CONTAIN?WHAT DOES AREA CONTAIN?• WHICH FEATURES DOES THIS WHICH FEATURES DOES THIS

ELEMENT CROSS?ELEMENT CROSS?• HOW MANY FEATURES ARE A HOW MANY FEATURES ARE A

CERTAIN DISTANCE FROM SITE?CERTAIN DISTANCE FROM SITE?

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6.15


NEW DIRECTIONS FOR NEW DIRECTIONS FOR GISGIS

• 3-D, DYNAMIC SIMULATION3-D, DYNAMIC SIMULATION• MAP-ENABLED INTERNET SITESMAP-ENABLED INTERNET SITES• GISGIS EMBEDDED IN EMBEDDED IN

APPLICATIONSAPPLICATIONS• REAL-TIME TRACKING OF REAL-TIME TRACKING OF

ASSETS-IN-MOTIONASSETS-IN-MOTION

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6.16


EXECUTIVE INFORMATION EXECUTIVE INFORMATION SYSTEMS SYSTEMS (EIS)(EIS)

COMPUTER APPLICATION USED COMPUTER APPLICATION USED DIRECTLY BY TOP MANAGERS, DIRECTLY BY TOP MANAGERS, WITHOUT THE ASSISTANCE OF WITHOUT THE ASSISTANCE OF INTERMEDIARIES, TO PROVIDE INTERMEDIARIES, TO PROVIDE THEM ON-LINE ACCESS TO THEM ON-LINE ACCESS TO CURRENT INFORMATION ABOUT CURRENT INFORMATION ABOUT STATUS OF ORGANIZATION AND STATUS OF ORGANIZATION AND ITS ENVIRONMENTITS ENVIRONMENT

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6.17


CHARACTERISTICS OF CHARACTERISTICS OF EISEIS

• PRIMARILY USED FOR TRACKING AND PRIMARILY USED FOR TRACKING AND CONTROLCONTROL

• CUSTOMIZED TO THE INDIVIDUAL CUSTOMIZED TO THE INDIVIDUAL EXECUTIVE EXECUTIVE

• GRAPHICALGRAPHICAL• EASY TO USEEASY TO USE• INCORPORATES BOTH HARD AND INCORPORATES BOTH HARD AND

SOFT DATASOFT DATA

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6.18


ARTIFICIAL INTELLIGENCE ARTIFICIAL INTELLIGENCE (AI)(AI)

USING THE COMPUTER TO PERFORM USING THE COMPUTER TO PERFORM TASKS DONE BY HUMANS IN TASKS DONE BY HUMANS IN SELECTED AREAS:SELECTED AREAS:

• NATURAL LANGUAGESNATURAL LANGUAGES• ROBOTICSROBOTICS• PERCEPTIVE SYSTEMSPERCEPTIVE SYSTEMS• EXPERT SYSTEMSEXPERT SYSTEMS• NEURAL NETWORKSNEURAL NETWORKS

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6.19


EXPERT SYSTEMSEXPERT SYSTEMS

• ONE BRANCH OF ARTIFICIAL ONE BRANCH OF ARTIFICIAL INTELLIGENCE INTELLIGENCE (AI)(AI)

• CONCERNED WITH BUILDING CONCERNED WITH BUILDING SYSTEMS THAT INCORPORATE SYSTEMS THAT INCORPORATE DECISION-MAKING LOGIC OF A DECISION-MAKING LOGIC OF A HUMAN EXPERT IN A SPECIFIC HUMAN EXPERT IN A SPECIFIC SKILLSKILL

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6.20



• KNOWLEDGE BASE: KNOWLEDGE BASE: Model of Human Model of Human KnowledgeKnowledge

• RULE - BASED EXPERT SYSTEM: RULE - BASED EXPERT SYSTEM: AIAI system based on IF - THEN statements system based on IF - THEN statements (Bifurcation); Rule Base: Collection of IF - (Bifurcation); Rule Base: Collection of IF - THEN knowledgeTHEN knowledge

• KNOWLEDGE FRAMES: KNOWLEDGE FRAMES: Knowledge Knowledge organizes in chunks based on shared organizes in chunks based on shared relationshipsrelationships

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6.21



• AI SHELL: AI SHELL: Programming environment of Programming environment of expert systemexpert system

• INFERENCE ENGINE: INFERENCE ENGINE: Search through Search through rule baserule base

– FORWARD CHAINING:FORWARD CHAINING: Uses input, searches rules for answer

– BACKWARD CHAINING:BACKWARD CHAINING: Begins with hypothesis, seeks information until hypothesis accepted or rejected

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6.22


EXAMPLES OF EXPERT SYSTEMSEXAMPLES OF EXPERT SYSTEMS

• MYCINMYCIN:: Diagnose, treat blood diseasesDiagnose, treat blood diseases

• CATS-1CATS-1:: Diagnose locomotive problemsDiagnose locomotive problems

• MARKET SURVEILLANCE: MARKET SURVEILLANCE: Detects Detects insider trading on stock marketinsider trading on stock market

• FINANCIAL ANALYSIS SUPPORT FINANCIAL ANALYSIS SUPPORT TECHNIQUE: TECHNIQUE: Credit analysis in banksCredit analysis in banks

• INDIVIDUAL DEVELOPMENT PLAN INDIVIDUAL DEVELOPMENT PLAN GOAL ADVISOR: GOAL ADVISOR: Helps set career goalsHelps set career goals

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6.23


NEURAL NETWORKSNEURAL NETWORKS

• BASED ON HOW HUMAN NERVOUS BASED ON HOW HUMAN NERVOUS SYSTEM WORKSSYSTEM WORKS

• USE STATISTICAL ANALYSIS TO USE STATISTICAL ANALYSIS TO RECOGNIZE PATTERNS FROM VAST RECOGNIZE PATTERNS FROM VAST AMOUNTS OF DATA BY A PROCESS OF AMOUNTS OF DATA BY A PROCESS OF ADAPTIVE LEARNING ADAPTIVE LEARNING

• CONSIST OF SOFTWARE THAT CONSIST OF SOFTWARE THAT ATTEMPTS TO EMULATE PROCESSING ATTEMPTS TO EMULATE PROCESSING PATTERNS OF BIOLOGICAL BRAIN PATTERNS OF BIOLOGICAL BRAIN

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6.24


EXAMPLES OF NEURAL NETWORKSEXAMPLES OF NEURAL NETWORKS

• BANKAMERICA: BANKAMERICA: Neural network Neural network evaluates commercial loan applicationsevaluates commercial loan applications

• AMERICAN EXPRESS: AMERICAN EXPRESS: System reads System reads handwriting on credit card slipshandwriting on credit card slips

• STATE OF WYOMING: STATE OF WYOMING: System reads System reads hand-printed numbers on tax formshand-printed numbers on tax forms

• ARCO AND TEXACO: ARCO AND TEXACO: Neural network Neural network helps pinpoint oil and gas depositshelps pinpoint oil and gas deposits

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6.25


EXAMPLES OF NEURAL NETWORKSEXAMPLES OF NEURAL NETWORKS

• SPIEGEL: SPIEGEL: Prune mailing list to Prune mailing list to eliminate those unlikely to order eliminate those unlikely to order againagain

• DEERE & COMPANY: DEERE & COMPANY: Pension Pension fund managementfund management

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6.26


VIRTUAL REALITY VIRTUAL REALITY (VR)(VR)

• USE OF COMPUTER-BASED SYSTEMS TO USE OF COMPUTER-BASED SYSTEMS TO CREATE AN ENVIRONMENT THAT SEEMS CREATE AN ENVIRONMENT THAT SEEMS REAL TO ONE OR MORE SENSE REAL TO ONE OR MORE SENSE (USUALLY INCLUDING SIGHT)(USUALLY INCLUDING SIGHT)

• USED IN VIDEO GAMES, TRAINING & USED IN VIDEO GAMES, TRAINING & EDUCATION, PROVIDING SERVICE AT A EDUCATION, PROVIDING SERVICE AT A DISTANCE, PRODUCT DESIGN, DISTANCE, PRODUCT DESIGN, INTERACTIVE WORLD WIDE WEB INTERACTIVE WORLD WIDE WEB APPLICATIONSAPPLICATIONS

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6.27


CHAPTER 6CHAPTER 6

Managerial Support Managerial Support

Systems Systems

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© Prentice Hall 2002 6.1 CHAPTER 6 Managerial Support Systems.

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