Weeks 4-5: Internal Information Systems

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Weeks 4-5 Internal Information Systems
MIS 2101 Management Information Systems
Based on material from Information Systems Today
Managing in the Digital World, Leonard Jessup
and Joseph Valacich, Pearson Prentice Hall, 2007
Also includes material by David Schuff, Paul
Weinberg, and Cindy Joy Marselis.
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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
• Examples?

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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
• Semi-structured
• Contained within business function
• Moderately complex
• Time horizon of few days to few months
• Examples?

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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
• Examples?

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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 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
• Purchased data
• Soft data
• Nonanalytical information
• Web-based news portals
• Customizable
• Delivery to different media

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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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Summary of EIS Characteristics
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Summary
So whats the trend as you go down the list/up
the pyramid?

• Executive Information Systems
• Highest level summary of information
• Management Information Systems
• Aggregate and collect data
• Transaction Processing Systems
• Collect data

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Summary Types of Information Systems

Weaker
EIS MIS TPS
Controls and Security
Operations Staff
Transaction Processing
Stronger
Source Business Driven Technology, by Haag,
Baltzan, Phillips, McGraw Hill, 2006 (with
modifications)
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Summary Decision Levels
Decision Level
Description
Example
Type of Information
Competitive advantage Market leader Long term
New products that change the industry
External events, rivals, sales, costs quality,
trends.
Executive
Improve operations without restructuring
Management
New tools to cut costs or imp- rove efficiency
Expenses, schedules, sales models, forecast
Day-to-day actions keep company running
Operations
Scheduling employees, placing orders.
Transactions, accounting, HRM, inventory
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Learning Objectives
Information Systems Today Managing in the
Digital World
7-32
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Seven 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

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Architecture of a DSS
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Common DSS Models
Information Systems Today Managing in the
Digital World
7-36
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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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2. Intelligent Systems

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

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Intelligent Systems

• 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

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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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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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Groupware

• Enables more effective team work
• Distinguished along two dimensions

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Benefits of Groupware
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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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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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Cases
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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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Too Much Technology? 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