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Enhancing Business Intelligence Using Information Systems

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Web crawlers (web spiders) browse the Web for specific information ... Web crawlers used to extract information from Internet ... – PowerPoint PPT presentation

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Title: Enhancing Business Intelligence Using Information Systems


1
7
Chapter
Enhancing Business Intelligence Using Information
Systems
Use of outdated information systems can be
costly. A software glitch at the Tokyo Stock
Exchange cost Misuho Securities Co. U.S.350
million.
2
Learning Objectives
3
Learning Objectives
4
Decision-Making Levels of an Organization
5
Operational Level
  • Day-to-day business processes
  • Interactions with customers
  • Information systems used to
  • Automate repetitive tasks
  • Improve efficiency
  • Decisions
  • Structured
  • Recurring
  • Can often be automated using IS

6
Summary of Characteristics Operational Level
7
Managerial Level
  • Functional managers
  • Monitoring and controlling operational-level
    activities
  • Providing information to executive level
  • Midlevel managers
  • Focus on effectively utilizing and deploying
    resources
  • Goal of achieving strategic objectives
  • Managers decisions
  • Semistructured
  • Contained within business function
  • Moderately complex
  • Time horizon of few days to few months

8
Summary of Characteristics Operational Level
9
Executive Level
  • The president, CEO, vice presidents, board of
    directors
  • Decisions
  • Long-term strategic issues
  • Complex and nonroutine problems
  • Unstructured decisions
  • Long-term ramifications

10
Summary of Characteristics Operational Level
11
Comparison of Decision-Making Levels
12
Learning Objectives
13
General Types of Information Systems
  • Input-process-output model
  • Basic systems model
  • Payroll system example

14
Transaction Processing System
  • Operational level
  • Purpose
  • Processing of business events and transactions
  • Increase efficiency
  • Automation
  • Lower costs
  • Increased speed and accuracy
  • Examples
  • Payroll processing
  • Sales and order processing
  • Inventory management
  • Etc.

15
Architecture of a TPS
16
Architecture of a TPS Inputs
  • Source Documents
  • Different data entry methods

17
Architecture of a TPS Processing
  • Online processing
  • Immediate results
  • Batch processing
  • Transactions collected and later processed
    together
  • Used when immediate notification not necessary

18
Architecture of a TPS Outputs
  • Counts, summary reports
  • Inputs to other systems
  • Feedback to systems operator

19
Summary of TPS Characteristics
20
Management Information Systems
  • Managerial level
  • Purpose
  • Produce reports
  • Support of midlevel managers decisions
  • Examples
  • Sales forecasting
  • Financial management and forecasting
  • Manufacturing, planning and scheduling
  • Inventory management and planning
  • Etc.

21
Architecture of an MIS
22
Architecture of an MIS Inputs
  • TPS data
  • Internal data
  • Requests for reports

23
Architecture of an MIS Processing
  • Aggregation
  • Summary

24
Architecture of an MIS Outputs
25
Summary of MIS Characteristics
26
Executive Information Systems
  • A.k.a. Executive support system
  • Executive level
  • Purpose
  • Aid in executive decision-making
  • Provide information in highly aggregated form
  • Examples
  • Monitoring of internal and external events and
    resources
  • Crisis management
  • Etc.

27
Architecture of an EIS
28
Architecture of an EIS Inputs
  • Hard data
  • Facts and numbers
  • Generated by TPS MIS
  • Soft data
  • Nonanalytical information
  • Web-based news portals
  • Customizable
  • Delivery to different media

29
Use of Web-based Portals for Gathering Soft Data
30
Architecture of an EIS Processing
  • Summarizing
  • Graphical interpreting

31
Architecture of an EIS Outputs
  • Summary reports
  • Trends
  • Simulations

32
EIS Output Digital Dashboards
  • Digital dashboard
  • Presentation of summary information
  • Information from multiple sources
  • Ability to drill down if necessary

33
EIS Output Digital Dashboard (II)
  • Total employee absenteeism
  • a) line chart b) drill-down numbers

34
Summary of EIS Characteristics
35
Learning Objectives
36
7 Information Systems that Span Organizational
Boundaries
37
1. Decision Support Systems
  • Decision making support for recurring problems
  • Used mostly by managerial level employees (can be
    used at any level)
  • Interactive decision aid
  • What-if analyses
  • Analyze results for hypothetical changes
  • E.g., Microsoft Excel

38
Architecture of a DSS
39
Common DSS Models
40
Summary of DSS Characteristics
41
Using DSS to Buy a Car
  • Selling price 22,500
  • Down payment 2,500
  • Monthly payment about 400
  • Interest rate information from the bank

42
Microsoft Excel Loan Analysis Template
  • Calculate
  • Monthly payment
  • Total amount paid
  • Total interest paid
  • What-if analysis
  • Change inputs
  • See the results

43
Loan Analysis Summary
  • Examine results
  • Choose best solution for given situation
  • E.g., based on monthly payment or total interest

44
2. Intelligent Systems
  • Artificial intelligence
  • Simulation of human intelligence
  • Reasoning, learning, sensing, hearing, walking,
    talking, etc.

45
Example Artificial Intelligence
46
Intelligent Systems
  • Intelligent system
  • Sensors, software and computers
  • Emulate and enhance human capabilities
  • Three types
  • Expert systems
  • Neural networks
  • Intelligent agents

47
Expert Systems
  • Use reasoning methods
  • Manipulate knowledge rather than information
  • System asks series of questions
  • Inferencing/pattern matching
  • Matching user responses with predefined rules
  • If-then format
  • Fuzzy logic
  • Represent rules using approximations

48
Example Expert System
Expert system to make a medical recommendation
49
Architecture of an Expert System
50
Summary of ES Characteristics
51
Neural Network System
  • Approximation of human brain functioning
  • Training to establish common patterns
  • Past information
  • New data compared to patterns
  • E.g., loan processing

52
Example Neural Network System
Loan processing system relying on a neural
network
53
Intelligent Agent Systems
  • Program working in the background
  • Bot (software robot)
  • Provides service when a specific event occurs

54
Intelligent Agent Types
  • Buyer agents (shopping bots) search for best
    price
  • User agents perform a task for the user
  • Monitoring and sensing agents keep track of key
    information
  • Data-mining agents analyze large amounts of
    data
  • Web crawlers (web spiders) browse the Web for
    specific information
  • Destructive agents malicious agents designed by
    spammers

55
3. Data Mining and Visualization Systems
  • Application of sophisticated statistical
    techniques
  • What-if analyses to support decision making
  • Capabilities can be embedded into a large range
    of systems

56
Visualization
  • Display of complex data relationships using
    graphical methods

Visualization of a weather system
57
Text Mining
  • Extraction of information from textual documents
  • Web crawlers used to extract information from
    Internet

58
4. Office Automation Systems
  • Developing documents, scheduling resources,
    communicating
  • Examples
  • Word processing
  • Desktop publishing
  • Electronic calendars
  • E-mail

59
Architecture of an Office Automation System
60
Summary of OAS Characteristics
61
5. Collaboration Technologies
  • Increased need for flexible teams
  • Virtual teams dynamic task forces
  • Forming and disbanding as needed
  • Fluctuating team size
  • Easy, flexible access to other team members
  • Need for new collaboration technologies

62
Video Conferencing
  • Costs few thousand dollars to 500,000
  • Dedicated videoconferencing systems
  • Located within organizational conference rooms
  • Highly realistic

63
Desktop Videoconferencing
  • Low-cost alternative to dedicated
    videoconferencing
  • Enablers
  • Increase in processing power
  • Internet connection speed

64
Future of Desktop Videoconferencing
  • Notebook computers with built in video cameras
  • Microsoft Office RoundTable 2007
  • 360-degree camera
  • Unified communications software
  • Built in microphone
  • Meeting content can be recorded, indexed and
    stored

65
Groupware
  • Enables more effective team work
  • Distinguished along two dimensions

66
Benefits of Groupware
67
Asynchronous Groupware
  • 1989 Lotus Development released Notes
  • Lotus Notes still an industry leader
  • Other tools
  • E-mail, newsgroups, mailing lists, group
    calendars, collaborative writing tools, etc.

68
Synchronous Groupware
  • Electronic meeting systems
  • Help groups have better meetings
  • Uses of EMS
  • Strategic planning sessions
  • Marketing focus groups
  • Brainstorming sessions
  • Business process management
  • Quality improvement
  • Web-based implementations

69
Example Electronic Meeting System
70
6. Knowledge Management Systems
  • Generating value from knowledge assets
  • Collection of technology-based systems
  • Knowledge assets
  • Skills, routines, practices, principles,
    formulas, methods, heuristics and intuition
  • Used to improve efficiency, effectiveness and
    profitability
  • Documents storing both facts and procedures
  • Examples
  • Databases, manuals, diagrams, books, etc.

71
Benefits and Challenges of Knowledge Based Systems
72
How Organizations Utilize KMS
  • Successful KMS facilitate the exchange of
    knowledge

73
Web-Based Knowledge Portals
  • Knowledge repository

74
7. Functional Area Information Systems
  • Cross-organizational-level IS
  • Support specific functional area
  • Focus on specific set of activities

75
Business Processes Supported by Functional Area
Information Systems
76
Organizational Functions and Representative
Information Systems
77
Geographic Information System
  • Use of geographically referenced information
  • Finding optimal location for a new store
  • Identification of areas too wet to fertilize (see
    figure)
  • Locating target customers
  • Infrastructure design

78
End of Chapter Content
79
Opening Case Amazon.com
  • 35 million customers worldwide
  • Innovations leading to satisfaction
  • Personalized greeting
  • Memory for recent purchases
  • Targeted gold box offers and bargains
  • Fraud protection
  • Shipping vs. billing address comparison
  • Method of shipment checks
  • Credit card sources checks
  • One-click shopping

80
The Growing Blogosphere
  • One of the fastest growing phenomena in the
    digital world

81
Information Systems Problems at the Tokyo Stock
Exchange
  • Outdated information system causing problems
  • December 2005
  • Order to sell 610,000 shares for 1 yen/share
    (U.S.0.009)
  • The actual price of the stock 610,000 yen
    (U.S.5,310)
  • Error was irreversible
  • Misuho Securities Co. lost billions of yen
    (U.S.350 million)
  • January 2006
  • TSE shut down because software reached trading
    capacity
  • Designed to handle 4.5 million
  • Reached the capacity at 200 p.m.

82
Ministry of Sound
  • Started as a small dance club in London
  • 1990 expansion started when new group of fans
    joined
  • Data management problem
  • Key to success IS consultants
  • Integration of databases across business units
  • Central data warehouse
  • Today global dance franchise
  • Record label, licensed products, tours, clubs,
    events and cell phones

83
Nanotubes
  • Nano something microscopic
  • Nanoscale
  • Nanometer 8-10 atoms
  • Human hair 70,000-80,000 nm thick
  • Nanotubes
  • Sequence of carbon 60 (C60) atoms
  • Extremely strong
  • Pure conductors of electricity
  • Used in resistors, capacitors, inductors, diodes,
    transistors

84
Too Much Intelligence? RFID and Privacy
  • RFID tags
  • Latest in technological tracking devices
  • Information imprinted on a tag
  • Tag generates signature signal
  • Special RFID reader interprets signal
  • Use of RFID tags
  • Pharmaceutical industry
  • Tracking of medication from factory to pharmacy
  • Retail businesses

85
Jeff Bezos, Founder and CEO, Amazon.com
  • Jeff Bezos
  • Example of how to succeed in e-commerce
  • 1986 graduated from Princeton
  • 1990 Bankers Trust Company youngest vice
    president
  • 1990-1994 D.E. Shaw Co.
  • Amazon.com
  • 1994 founded
  • 2003 first time profitable
  • Today worth 17 billion

86
Internet Protocol Television
  • HDTV (high-definition television)
  • Digital TV service through cable subscription
  • Full duplex connection
  • Services
  • Video-on-demand, Web access, voice access

87
Internet Protocol Television (II)
  • IPTV (Internet protocol television)
  • Programming control in consumers hands
  • Will be available in more areas than HDTV
  • Europe and Asia lead the world in IPTV revenue
  • By 2009 US-based revenue expected to reach 44
    billion
  • Services
  • Access to extensive video and film libraries
  • Phone calls, Internet connection, video games
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