Enhancing Business Intelligence Using Information Systems

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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Use of outdated information systems can be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
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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

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Summary of Characteristics Operational Level
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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

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Summary of Characteristics Operational Level
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Executive Level

• The president, CEO, vice presidents, board of
  directors
• Decisions
• Long-term strategic issues
• Complex and nonroutine problems
• Unstructured decisions
• Long-term ramifications

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Summary of Characteristics Operational Level
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Comparison of Decision-Making Levels
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Learning Objectives
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General Types of Information Systems

• Input-process-output model
• Basic systems model
• Payroll system example

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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.

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Architecture of a TPS
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Architecture of a TPS Inputs

• Source Documents
• Different data entry methods

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Architecture of a TPS Processing

• Online processing
• Immediate results
• Batch processing
• Transactions collected and later processed
  together
• Used when immediate notification not necessary

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Architecture of a TPS Outputs

• Counts, summary reports
• Inputs to other systems
• Feedback to systems operator

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Summary of TPS Characteristics
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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.

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Architecture of an MIS
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Architecture of an MIS Inputs

• TPS data
• Internal data
• Requests for reports

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Architecture of an MIS Processing

• Aggregation
• Summary

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Architecture of an MIS Outputs
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Summary of MIS Characteristics
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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.

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Architecture of an EIS
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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

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Use of Web-based Portals for Gathering Soft Data
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Architecture of an EIS Processing

• Summarizing
• Graphical interpreting

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Architecture of an EIS Outputs

• Summary reports
• Trends
• Simulations

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EIS Output Digital Dashboards

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

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EIS Output Digital Dashboard (II)

• Total employee absenteeism
• a) line chart b) drill-down numbers

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Summary of EIS Characteristics
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Learning Objectives
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7 Information Systems that Span Organizational
Boundaries
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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

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Architecture of a DSS
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Common DSS Models
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Summary of DSS Characteristics
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Using DSS to Buy a Car

• Selling price 22,500
• Down payment 2,500
• Monthly payment about 400
• Interest rate information from the bank

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Microsoft Excel Loan Analysis Template

• Calculate
• Monthly payment
• Total amount paid
• Total interest paid
• What-if analysis
• Change inputs
• See the results

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Loan Analysis Summary

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

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2. Intelligent Systems

• Artificial intelligence
• Simulation of human intelligence
• Reasoning, learning, sensing, hearing, walking,
  talking, etc.

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Example Artificial Intelligence
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Intelligent Systems

• Intelligent system
• Sensors, software and computers
• Emulate and enhance human capabilities
• Three types
• Expert systems
• Neural networks
• Intelligent agents

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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

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Example Expert System
Expert system to make a medical recommendation
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Architecture of an Expert System
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Summary of ES Characteristics
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Neural Network System

• Approximation of human brain functioning
• Training to establish common patterns
• Past information
• New data compared to patterns
• E.g., loan processing

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Example Neural Network System
Loan processing system relying on a neural
network
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Intelligent Agent Systems

• Program working in the background
• Bot (software robot)
• Provides service when a specific event occurs

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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

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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

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Visualization

• Display of complex data relationships using
  graphical methods

Visualization of a weather system
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Text Mining

• Extraction of information from textual documents
• Web crawlers used to extract information from
  Internet

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4. Office Automation Systems

• Developing documents, scheduling resources,
  communicating
• Examples
• Word processing
• Desktop publishing
• Electronic calendars
• E-mail

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Architecture of an Office Automation System
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Summary of OAS Characteristics
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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

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Video Conferencing

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

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Desktop Videoconferencing

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

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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

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Groupware

• Enables more effective team work
• Distinguished along two dimensions

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Benefits of Groupware
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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.

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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

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Example Electronic Meeting System
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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.

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Benefits and Challenges of Knowledge Based Systems
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How Organizations Utilize KMS

• Successful KMS facilitate the exchange of
  knowledge

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Web-Based Knowledge Portals

• Knowledge repository

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7. Functional Area Information Systems

• Cross-organizational-level IS
• Support specific functional area
• Focus on specific set of activities

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Business Processes Supported by Functional Area
Information Systems
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Organizational Functions and Representative
Information Systems
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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

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End of Chapter Content
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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

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The Growing Blogosphere

• One of the fastest growing phenomena in the
  digital world

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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.

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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

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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

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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

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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

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Internet Protocol Television

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

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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