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CHAPTER 6

CHAPTER 6. Managerial Support Systems. MANAGERIAL SUPPORT SYSTEMS. DECISION SUPPORT SYSTEMS DATA MINING GROUP SUPPORT SYSTEMS GEOGRAPHIC INFO SYSTEMS EXECUTIVE INFO SYSTEMS EXPERT SYSTEMS NEURAL NETWORKS VIRTUAL REALITY *. DECISION SUPPORT SYSTEMS.

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CHAPTER 6

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  1. CHAPTER 6 Managerial Support Systems

  2. MANAGERIAL SUPPORT SYSTEMS • DECISION SUPPORT SYSTEMS • DATA MINING • GROUP SUPPORT SYSTEMS • GEOGRAPHIC INFO SYSTEMS • EXECUTIVE INFO SYSTEMS • EXPERT SYSTEMS • NEURAL NETWORKS • VIRTUAL REALITY *

  3. DECISION SUPPORT SYSTEMS • COMPUTER-BASED SYSTEM, USUALLY INTERACTIVE, DESIGNED TO ASSIST MANAGERS IN MAKING DECISIONS • INCORPORATES BOTH DATA AND MODELS, INTENDED TO ASSIST IN THE SOLUTION OF SEMI- OR UNSTRUCTURED PROBLEMS *

  4. DSS COMPONENTS • MODEL MANAGEMENT: Helps user determine appropriate analytic tools • DATA MANAGEMENT: Provides access to select, handle data • USER INTERFACE: Allows user to interact with system *

  5. TYPICAL DSS APPLICATIONS • PROFIT & LOSS MODEL • MACHINE LOADING OF MACHINES IN A JOB SHOP • COST/BENEFIT ANALYSIS • PRO FORMA FINANCIAL STATEMENT • “WHAT-IF” ANALYSIS *

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

  7. DATA MINING TECHNIQUES • ONLINE ANALYTICAL PROCESSING: Human-driven analysis querying a database with specific criteria • DECISION TREES • NEURAL NETWORKS • MATHEMATICAL PROGRAMMING • STATISTICAL ANALYSIS *

  8. USES OF DATAMINING

  9. USES OF DATAMINING

  10. GROUP SUPPORT SYSTEMS (GPS) • SYSTEM DESIGNED TO MAKE GROUP SESSIONS MORE PRODUCTIVE: Brainstorming, issue structuring, voting, conflict resolution • A VARIANT OF DSS IN WHICH THE SYSTEM IS DESIGNED TO SUPPORT A GROUP • A SPECIALIZED TYPE OF GROUPWARE *

  11. GSS CHARACTERISTICS • PARALLEL HUMAN PROCESSING • EQUAL OPPORTUNITY FOR PARTICIPATION • ANONYMITY • COMPLETE RECORD OF MEETING • OUTPUT OF ONE PHASE LEADS TO NEXT • CAN MORE EASILY APPLY STRUCTURE *

  12. GEOGRAPHIC INFORMATION SYSTEMS (GIS) • A COMPUTER-BASED SYSTEM DESIGNED TO COLLECT, STORE, RETRIEVE, MANIPULATE, AND DISPLAY SPATIAL DATA • A SPATIALLY BASED DSS • TYPICALLY A DIGITIZED MAP WITH OTHER DATA LINKED TO THE MAP COORDINATES *

  13. TWO TYPES OF GIS • RASTER • Grids of equal-sized cells groupedor linked to make lines and shapes • Values of cells vary • Example: Satellite images, pixels on screen • VECTOR • Points, Lines, and Polygons • Approximates curves, can link into networks • Example: Property boundaries, sales territories *

  14. GIS COVERAGE MODEL • WHAT IS ADJACENT TO FEATURE? • WHICH IS NEAREST SITE? • WHAT DOES AREA CONTAIN? • WHICH FEATURES DOES THIS ELEMENT CROSS? • HOW MANY FEATURES ARE A CERTAIN DISTANCE FROM SITE? *

  15. NEW DIRECTIONS FOR GIS • 3-D, DYNAMIC SIMULATION • MAP-ENABLED INTERNET SITES • GIS EMBEDDED IN APPLICATIONS • REAL-TIME TRACKING OF ASSETS-IN-MOTION *

  16. EXECUTIVE INFORMATION SYSTEMS (EIS) COMPUTER APPLICATION USED DIRECTLY BY TOP MANAGERS, WITHOUT THE ASSISTANCE OF INTERMEDIARIES, TO PROVIDE THEM ON-LINE ACCESS TO CURRENT INFORMATION ABOUT STATUS OF ORGANIZATION AND ITS ENVIRONMENT *

  17. CHARACTERISTICS OF EIS • PRIMARILY USED FOR TRACKING AND CONTROL • CUSTOMIZED TO THE INDIVIDUAL EXECUTIVE • GRAPHICAL • EASY TO USE • INCORPORATES BOTH HARD AND SOFT DATA *

  18. ARTIFICIAL INTELLIGENCE (AI) USING THE COMPUTER TO PERFORM TASKS DONE BY HUMANS IN SELECTED AREAS: • NATURAL LANGUAGES • ROBOTICS • PERCEPTIVE SYSTEMS • EXPERT SYSTEMS • NEURAL NETWORKS *

  19. EXPERT SYSTEMS • ONE BRANCH OF ARTIFICIAL INTELLIGENCE (AI) • CONCERNED WITH BUILDING SYSTEMS THAT INCORPORATE DECISION-MAKING LOGIC OF A HUMAN EXPERT IN A SPECIFIC SKILL *

  20. EXPERT SYSTEMS • KNOWLEDGE BASE: Model of Human Knowledge • RULE - BASED EXPERT SYSTEM: AI system based on IF - THEN statements (Bifurcation); Rule Base: Collection of IF - THEN knowledge • KNOWLEDGE FRAMES: Knowledge organizes in chunks based on shared relationships *

  21. EXPERT SYSTEMS • AI SHELL: Programming environment of expert system • INFERENCE ENGINE: Search through rule base • FORWARD CHAINING:Uses input, searches rules for answer • BACKWARD CHAINING:Begins with hypothesis, seeks information until hypothesis accepted or rejected *

  22. EXAMPLES OF EXPERT SYSTEMS • MYCIN:Diagnose, treat blood diseases • CATS-1:Diagnose locomotive problems • MARKET SURVEILLANCE: Detects insider trading on stock market • FINANCIAL ANALYSIS SUPPORT TECHNIQUE: Credit analysis in banks • INDIVIDUAL DEVELOPMENT PLAN GOAL ADVISOR: Helps set career goals *

  23. NEURAL NETWORKS • BASED ON HOW HUMAN NERVOUS SYSTEM WORKS • USE STATISTICAL ANALYSIS TO RECOGNIZE PATTERNS FROM VAST AMOUNTS OF DATA BY A PROCESS OF ADAPTIVE LEARNING • CONSIST OF SOFTWARE THAT ATTEMPTS TO EMULATE PROCESSING PATTERNS OF BIOLOGICAL BRAIN *

  24. EXAMPLES OF NEURAL NETWORKS • BANKAMERICA: Neural network evaluates commercial loan applications • AMERICAN EXPRESS: System reads handwriting on credit card slips • STATE OF WYOMING: System reads hand-printed numbers on tax forms • ARCO AND TEXACO: Neural network helps pinpoint oil and gas deposits *

  25. EXAMPLES OF NEURAL NETWORKS • SPIEGEL: Prune mailing list to eliminate those unlikely to order again • DEERE & COMPANY: Pension fund management *

  26. VIRTUAL REALITY (VR) • USE OF COMPUTER-BASED SYSTEMS TO CREATE AN ENVIRONMENT THAT SEEMS REAL TO ONE OR MORE SENSE (USUALLY INCLUDING SIGHT) • USED IN VIDEO GAMES, TRAINING & EDUCATION, PROVIDING SERVICE AT A DISTANCE, PRODUCT DESIGN, INTERACTIVE WORLD WIDE WEB APPLICATIONS *

  27. CHAPTER 6 Managerial Support Systems

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