Enhancing Business Intelligence Using Information Systems - PowerPoint PPT Presentation

Loading...

PPT – Enhancing Business Intelligence Using Information Systems PowerPoint presentation | free to view - id: 2776a4-ZDc1Z



Loading


The Adobe Flash plugin is needed to view this content

Get the plugin now

View by Category
About This Presentation
Title:

Enhancing Business Intelligence Using Information Systems

Description:

Day-to-day business processes. Interactions with customers ... Human hair 70,000-80,000 nm thick. Nanotubes. Sequence of carbon 60 (C60) atoms. Extremely strong ... – PowerPoint PPT presentation

Number of Views:96
Avg rating:3.0/5.0
Slides: 88
Provided by: ITED7
Category:

less

Write a Comment
User Comments (0)
Transcript and Presenter's Notes

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Use of outdated information systems can be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
Operational Level Managerial Level Executive Level
Who Foreman or supervisor Midlevel managers and functional managers Executive-level managers
What Automate routine and repetitive activities Automate the monitoring and controlling of operational activities Aggregate summaries of past organizational data and projections of the future
Why Improve organizational efficiency Improve organizational effectiveness Improve organizational strategy and planning
IS Transaction Processing Systems (TPS) Management Information Systems (MIS) Executive Information Systems (EIS)
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
  1. Buyer agents (shopping bots) search for best
    price
  2. User agents perform a task for the user
  3. Monitoring and sensing agents keep track of key
    information
  4. Data-mining agents analyze large amounts of
    data
  5. Web crawlers (web spiders) browse the Web for
    specific information
  6. 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
About PowerShow.com