Download O`Brien MIS, 6th ed.

8
Management Information System
Decision Support System
Judi Prajetno Sugiono
[email protected]
(2008)
Learning Objectives
Identify the changes taking place in the
form and use of decision support in ebusiness enterprises.
Identify the role and reporting alternatives
of management information systems.
2
Learning Objectives (continued)
Describe how online analytical processing
can meet key information needs of
managers.
Explain the decision support system
concept and how it differs from traditional
management information systems.
3
Learning Objectives (continued)
Explain how the following information
systems can support the information
needs of executives, managers, and
business professionals:



Executive information systems
Enterprise information portals
Enterprise knowledge portals
4
Learning Objectives (continued)
Identify how neural networks, fuzzy logic,
genetic algorithms, virtual reality, and
intelligent agents can be used in business.
How can expert systems be used in
business decision-making situations?
5
Section I
Decision Support in Business
6
Business and Decision Support
To succeed, companies need information
systems that can support the diverse
information and decision-making needs of
their managers and business
professionals.
7
Business and Decision Support
(continued)
Information, Decisions, & Management

The type of information required by decision
makers is directly related to the level of
management and the amount of structure in
the decision situations.
8
Business and Decision Support
(continued)
9
Business and Decision Support
(continued)
Information Quality

Timeliness
 Provided WHEN it is needed
 Up-to-date when it is provided
 Provided as often as needed
 Provided about past, present, and future time
periods as necessary
10
Business and Decision Support
(continued)
Information Quality (continued)

Content
 Free from errors
 Should be related to the information needs of a specific
recipient for a specific situation
 Provide all the information that is needed
 Only the information that is needed should be provided
 Can have a broad or narrow scope, or an internal or external
focus
 Can reveal performance
11
Business and Decision Support
(continued)
Information Quality (continued)

Form




Provided in a form that is easy to understand
Can be provided in detail or summary form
Can be arranged in a predetermined sequence
Can be presented in narrative, numeric, graphic, or other
forms
 Can be provided in hard copy, video, or other media.
12
Business and Decision Support
(continued)
13
Business and Decision Support
(continued)
Decision Structure

Structured decisions
 Involve situations where the procedures to be
followed can be specified in advance

Unstructured decisions
 Involve situations where it is not possible to specify
most of the decision procedures in advance
14
Business and Decision Support
(continued)
Decision structure (continued)

Semistructured decisions
 Some decision procedures can be specified in
advance, but not enough to lead to a definite
recommended decision
15
Business and Decision Support
(continued)

Amount of structure is typically tied to
management level
 Operational – more structured
 Tactical – more semistructured
 Strategic – more unstructured
16
Decision Support Trends
The growth of corporate intranets,
extranets and the Web has accelerated
the development and use of “executive
class” information delivery & decision
support software tools to virtually every
level of the organization.
17
Management Information Systems
The original type of information system
Produces many of the products that support dayto-day decision-making
These information products typically take the
following forms:




Periodic scheduled reports
Exception reports
Demand reports and responses
Push reports
18
Management Information Systems
(continued)
Management reporting alternatives

Periodic scheduled reports
 Prespecified format
 Provided on a scheduled basis

Exception reports
 Produced only when exceptional conditions occur
 Reduces information overload
19
Management Information Systems
(continued)
Management reporting alternatives
(continued)

Demand reports and responses
 Available when demanded.
 Ad hoc

Push reports
 Information is sent to a networked PC over the
corporate intranet.
 Not specifically requested by the recipient
20
Online Analytical Processing
Enables managers and analysts to
interactively examine & manipulate large
amounts of detailed and consolidated data
from many perspectives


Analyze complex relationships to discover
patterns, trends, and exception conditions
Real-time
21
Online Analytical Processing
(continued)
Involves..

Consolidation
 The aggregation of data.
 From simple roll-ups to complex groupings of
interrelated data

Drill-Down
 Display detail data that comprise consolidated data
22
Online Analytical Processing
(continued)

Slicing and Dicing
 The ability to look at the database from different
viewpoints.
 When performed along a time axis, helps analyze
trends and find patterns
23
Decision Support Systems
Computer-based information systems that
provide interactive information support during
the decision-making process
DSS’s use




Analytical models
Specialized databases
The decision maker’s insights & judgments
An interactive, computer-based modeling process to
support making semistructured and unstructured
business decisions
24
Decision Support Systems
(continued)
Designed to be ad hoc, quick-response systems
that are initiated and controlled by the decision
maker
DSS Models and Software


Rely on model bases as well as databases
Might include models and analytical techniques used
to express complex relationships
25
Decision Support Systems
(continued)
DSS models and software (continued)

Can combine model components to create
integrated models in support of specific types
of business decisions
26
Decision Support Systems
(continued)
Geographic Information & Data
Visualization Systems


Special categories of DSS that integrate
computer graphics with other DSS features
GIS
 A DSS that uses geographic databases to
construct and display maps and other graphics
displays
27
Decision Support Systems
(continued)
Geographic information and data
visualization systems (continued)

Data visualization systems
 Represent complex data using interactive threedimensional graphic forms
 Helps discover patterns, links, and anomalies
28
Using Decision Support Systems
An interactive modeling process
Four types of analytical modeling




What-if analysis
Sensitivity analysis
Goal-seeking analysis
Optimization analysis
29
Using Decision Support Systems
(continued)
What-If Analysis

End user makes changes to variables, or
relationships among variables, and observes
the resulting changes in the values of other
variables
30
Using Decision Support Systems
(continued)
Sensitivity Analysis



A special case of what-if analysis
The value of only one variable is changed repeatedly,
and the resulting changes on other variables are
observed
Typically used when there is uncertainty about the
assumptions made in estimating the value of certain
key variables
31
Using Decision Support Systems
(continued)
Goal-Seeking Analysis

Instead of observing how changes in a
variable affect other variables, goal-seeking
sets a target value (a goal) for a variable, then
repeatedly changes other variables until the
target value is achieved
32
Using Decision Support Systems
(continued)
Optimization Analysis


A more complex extension of goal-seeking
The goal is to find the optimum value for one
or more target variables, given certain
constraints
33
Using Decision Support Systems
(continued)
Data Mining for Decision Support



Software analyzes vast amounts of data
Attempts to discover patterns, trends, &
correlations
May perform regression, decision tree, neural
network, cluster detection, or market basket
analysis
34
Executive Information Systems
EIS’s combine many of the features of MIS and
DSS
Originally intended to provide top executives
with immediate, easy access to information
about the firm’s “critical success factors”
Alternative names


Enterprise information systems
Executive support systems
35
Executive Information Systems
(continued)
Features of an EIS



Information presented in forms tailored to the
preferences of the users
Most stress use of graphical user interface
and graphics displays
May also include exception reporting and
trend analysis
36
Enterprise Portals and Decision
Support
A Web-based interface and integration of
intranet and other technologies that gives
all intranet users and selected extranet
users access to a variety of internal &
external business applications and
services
37
Enterprise Portals and Decision
Support (continued)
Business benefits





More specific and selective information
Easy access to key corporate intranet website
resources
Industry and business news
Access to company data for stakeholders
Less time spent on unproductive surfing
38
Knowledge Management
Systems
IT that helps gather, organize, and share
business knowledge within an organization
Hypermedia databases that store and
disseminate business knowledge. May also be
called knowledge bases
Best practices, policies, business solutions
Entered through the enterprise knowledge portal
39
Section II
Artificial Intelligence Technologies in
Business
40
Business and AI
“Designed to leverage the capabilities of
humans rather than replace them,…AI
technology enables an extraordinary array
of applications that forge new connections
among people, computers, knowledge,
and the physical world.”
41
Artificial Intelligence
A field of science and technology based on
disciplines such as computer science, biology,
psychology, linguistics, mathematics, &
engineering
Goal is to develop computers that can think, see,
hear, walk, talk, and feel
Major thrust – development of computer
functions normally associated with human
intelligence – reasoning, learning, problem
solving
42
Artificial Intelligence (continued)
Domains of AI

Three major areas
 Cognitive science
 Robotics
 Natural interfaces
43
Artificial Intelligence (continued)
Cognitive science


Focuses on researching how the human brain works
& how humans think and learn
Applications





Expert systems
Adaptive learning systems
Fuzzy logic systems
Neural networks
Intelligent agents
44
Artificial Intelligence (continued)
Robotics

Produces robot machines with computer intelligence
and computer controlled, humanlike physical
capabilities
Natural interfaces



Natural language and speech recognition
Talking to a computer and having it understand
Virtual reality
45
Neural Networks
Computing systems modeled after the
brain’s meshlike network of interconnected
processing elements, called neurons
Goal – the neural network learns from
data it processes
46
Fuzzy Logic Systems
A method of reasoning that resembles human
reasoning
Allows for approximate values and inferences
Allows for incomplete or ambiguous data
Allows “fuzzy” systems to process incomplete
data and provide approximate, but acceptable,
solutions to problems
47
Genetic Algorithms
Uses Darwinian, randomizing, & other
mathematical functions to simulate an
evolutionary process that can yield
increasingly better solutions
Especially useful for situations in which
thousands of solutions are possible &
must be evaluated
48
Virtual Reality
Computer-simulated reality
Relies on multisensory input/output
devices
Allows interaction with computer-simulated
objects, entities, and environments in
three dimensions
49
Intelligent Agents
A “software surrogate” for an end user or a
process that fulfills a stated need or
activity
Uses built-in and learned knowledge base
about a person or process to make
decisions and accomplish tasks
50
Expert Systems
A knowledge-based information system that
uses its knowledge about a specific, complex
application area to act as an expert consultant
Provides answers to questions in a very specific
problem area
Must be able to explain reasoning process and
conclusions to the user
51
Expert Systems (continued)
Components


Knowledge base
Software resources
52
Expert Systems (continued)
 Knowledge base

Contains
 Facts about a specific subject area
 Heuristics that express the reasoning procedures of
an expert on the subject
53
Expert Systems (continued)
 Software Resources

Contains an inference engine and other programs for
refining knowledge and communicating
 Inference engine processes the knowledge, and
makes associations and inferences
 User interface programs, including an explanation
program, allows communication with user
54
Developing Expert Systems
Begin with an expert system shell
Add the knowledge base
Built by a “knowledge engineer”


Works with experts to capture their knowledge
Works with domain experts to build the expert
system
55
The Value of Expert Systems
56
The Value of Expert Systems
(continued)
Benefits


Can outperform a single human expert in many
problem situations
Helps preserve and reproduce knowledge of experts
Limitations

Limited focus, inability to learn, maintenance
problems, developmental costs
57
Discussion Questions
Is the form and use of information and
decision support in e-business changing
and expanding?
Has the growth of self-directed teams to
manage work in organizations changed
the need for strategic, tactical, and
operational decision making in business?
58
Discussion Questions (continued)
What is the difference between the ability of a
manager to retrieve information instantly on
demand using an MIS and the capabilities
provided by a DSS?
In what ways does using an electronic
spreadsheet package provide you with the
capabilities of a decision support system?
59
Discussion Questions (continued)
Are enterprise information portals making
executive information systems
unnecessary?
Can computers think? Will they EVER be
able to?
60
Discussion Questions (continued)
What are some of the most important
applications of AI in business?
What are some of the limitations or
dangers you see in the use of AI
technologies such as expert systems,
virtual reality, and intelligent agents?
What could be done to minimize such
effects?
61
Real World Case 1 – AmeriKing
& Others
AmeriKing’s old system


Relied on an antiquated corporate information
system.
Involved mailing or faxing paper reports to managers.
AmeriKing’s new system


An intranet-based enterprise information portal
Enables employees to use Web browsers to instantly
access financial, marketing, human resource, and
other reports.
62
Real World Case 1 (continued)
What is the business value to a company
of an enterprise portal like AmeriKing’s?
What are several ways AmeriKing could
improve the business value of its portal?
63
Real World Case 1 (continued)
How might an enterprise portal help you
as a business professional or manager in
your work activities?
Is it becoming necessary for all companies
to provide an enterprise information portal
to their employees?
64
Real World Case 2 – BAE
Systems
Problems




Wasted time trying to find information to do the job.
Duplication of effort
Information overload
Inadequate search capability
Solution
An intranet-based knowledge management
system
65
Real World Case 2 (continued)
What problems was BAE having in
knowledge sharing? Are such problems
common to many companies?
How does BAE’s knowledge management
system help solve such problems?
66
Real World Case 2 (continued)
What are some of the business benefits
and potential limitations of BAE’s
knowledge management system?
What is the difference between a
corporate intranet and a knowledge
management system? What is the
difference in their business value?
67
Real World Case 3 – Cisco Systems,
NetFlix, & Office Depot
What are the business benefits and
limitations of Cisco’s Web-based system
for its channel managers?
Do you agree that NetFlix’s real-time
personalization system is critical to their
success?
68
Real World Case 3 (continued)
Do you think salespeople will appreciate
and benefit from the real-time alert system
envisioned for Office Depot?
69
Real World Case 4 –
Producers Assistance, Kinko’s, & Champion Printing
Using Spatial Information Systems to…



Find workers
Find services
Find customers
70
Real World Case 4 (continued)
What is the business value of spatial
information systems?
How else could spatial information
systems be used in business?
71
Real World Case 4 (continued)
How helpful is Kinko’s location finder
service? What else can they do to
improve this spatial information
management application?
72
Real World Case 5 – Schneider
National
The business value of business
intelligence (BI)
“We were drowning in data but starving for
information.”
73
Real World Case 5 (continued)
What problem was Schneider National
having with their business data?
How did business intelligence solve the
problem?
74
Real World Case 5 (continued)
What are the benefits and limitations of
business intelligence software as
demonstrated by Schneider National?
What is the business value of business
intelligence as defined by Cognos?
75