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Use of outdated information systems can be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.
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Learning Objectives
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Learning Objectives
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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
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)
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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

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

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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