Download Week Three - Temple Fox MIS

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.
Learning Objectives
2
Learning Objectives
3
Decision-Making Levels of an
Organization
4
Operational Level



Day-to-day business processes
Interactions with customers
Information systems used to:



Decisions:




5
Automate repetitive tasks
Improve efficiency
Structured
Recurring
Can often be automated using IS
Examples?
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?
6
Executive Level
The president, CEO, vice presidents,
board of directors
 Decisions

Long-term strategic issues
 Complex and nonroutine problems
 Unstructured decisions
 Long-term ramifications


7
Examples?
7-7
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)
8
Learning Objectives
9
General Types of Information
Systems

Input-process-output model
Basic systems model
 Payroll system example

10
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.
11
Architecture of a TPS
12
Architecture of a TPS: Inputs

Source Documents

13
Different data entry methods
Architecture of a TPS:
Processing

Online processing


Batch processing


14
Immediate results
Transactions collected and later processed
together
Used when immediate notification not
necessary
Architecture of a TPS:
Outputs
Counts, summary reports
 Inputs to other systems
 Feedback to systems operator

15
Summary of TPS
Characteristics
16
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.
17
Architecture of an MIS
18
Architecture of an MIS:
Processing
Aggregation
 Summary

19
Architecture of an MIS:
Outputs
20
Summary of MIS Characteristics
21
Executive Information
Systems



A.k.a. Executive support system
Executive level
Purpose



Examples



22
Aid in executive decision-making
Provide information in highly aggregated
form
Monitoring of internal and external events
and resources
Crisis management
Etc.
Architecture of an EIS
23
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
24
Architecture of an EIS:
Processing
Summarizing
 Graphical interpreting

25
Architecture of an EIS:
Outputs
Summary reports
 Trends
 Simulations

26
EIS Output: Digital Dashboards

Digital dashboard
 Presentation of
summary
information
 Information from
multiple sources
 Ability to drill
down if
necessary
27
Summary of EIS Characteristics
28
Summary
So what’s 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
29
Summary: Types of Information
Systems
Weaker
EIS
MIS
Controls
and
Security
TPS
Stronger
Operations Staff
Transaction
Processing
Source: Business Driven Technology, by Haag, Baltzan, Phillips, McGraw Hill, 2006 (with modifications)
30
Summary: Decision Levels
Decision Level
Description
Example
Type of
Information
Executive
Competitive advantage
Market leader
Long term
New products
that change
the industry
External events,
rivals, sales, costs
quality, trends.
Management
Improve operations
without restructuring
Operations
Day-to-day actions
keep company running
31
New tools to
Expenses,
cut costs or impschedules, sales
rove efficiency
models, forecast
Scheduling
employees,
placing orders.
Transactions,
accounting,
HRM, inventory
Learning Objectives
32
Information Systems Today: Managing in the Digital World
7-32
Seven Information Systems that
Span Organizational
Boundaries
33
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


34
Analyze results for hypothetical
changes
Architecture of a DSS
35
Common DSS Models
36
Information Systems Today: Managing in the Digital World
7-36
Using DSS to Buy a Car
Selling price – $22,500
 Down payment – $2,500
 Monthly payment – about $400
 Interest rate information from the bank

37
2. Intelligent Systems

Artificial intelligence
Simulation of human intelligence
 Reasoning, learning, sensing, hearing,
walking, talking, etc.

38
Intelligent Systems

Three types
Expert systems
 Neural networks
 Intelligent agents

39
Expert Systems




Use reasoning methods
Manipulate knowledge rather than
information
System asks series of questions
Inferencing/pattern matching


40
Matching user responses with predefined
rules
If-then format
Neural Network System
Approximation of human brain
functioning
 Training to establish common patterns


Past information
New data compared to patterns
 E.g., loan processing

41
Example: Neural Network
System
Loan
processing
system
relying on a
neural
network
42
-42
Intelligent Agent Systems



Program working in the background
Bot (software robot)
Provides service when a specific
event occurs
43
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
44
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
45
Visualization

Display of complex data relationships using
graphical methods
Visualization of a
weather system
46
Text Mining


Extraction of
information from
textual documents
Web crawlers used
to extract
information from
Internet
47
4. Office Automation
Systems
Developing documents, scheduling
resources, communicating
 Examples

Word processing
 Desktop publishing
 Electronic calendars
 E-mail

48
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


49
Need for new collaboration
technologies
Video Conferencing

Costs – few thousand dollars to $500,000

Dedicated videoconferencing systems
 Located within organizational conference rooms
 Highly realistic
50
Groupware

Enables more
effective team
work

Distinguished
along two
dimensions
51
Benefits of Groupware
52
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.
53
Benefits and Challenges of
Knowledge Based Systems
54
7. Functional Area Information
Systems
Cross-organizational-level IS
 Support specific functional area
 Focus on specific set of activities

55
Business Processes Supported
by Functional Area Information
Systems
56
Cases
57
Amazon.com
• 35 million customers worldwide
• Innovations leading to satisfaction




Fraud protection




Personalized greeting
Memory for recent purchases
Targeted “gold box” offers and
bargains
Shipping vs. billing address
comparison
Method of shipment checks
Credit card sources checks
“One-click” shopping
58
The Growing Blogosphere

One of the fastest growing phenomena in the digital
world
59
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
60