Chapter 9: Information,
Decision Support, Artificial
Intelligence, and SpecialPurpose Systems
Succeeding with Technology:
Second Edition
Objectives
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Define the stages of decision making and problem
solving
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Discuss the use of management information
systems in providing reports to help solve structured
problems
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Describe how decision support systems are used to
solve nonprogrammed and unstructured problems
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Objectives (continued)
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Explain how a group decision support system can
help people and organizations collaborate on team
projects
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Discuss the uses of artificial intelligence and specialpurpose systems
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Decision Making and Problem
Solving
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Decision making
 Process that takes place in three stages
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Intelligence
Design
Choice
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Decision Making and Problem
Solving (continued)
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Intelligence stage
 Identify and define potential problems or
opportunities
Design stage
 Develop alternative solutions
Choice stage
 Select a course of action
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Decision Making and Problem
Solving (continued)
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Problem solving
 Includes and goes beyond decision making
 Implementation stage
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Action is taken to put the solution into effect
Monitoring stage
 Decision makers evaluate the implementation of the
solution
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Decision Making and Problem
Solving (continued)
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Reactive problem-solving approach
 Wait until problem surfaces before taking action
Proactive approach
 Seek out potential problems before they become
serious
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Programmed versus
Nonprogrammed Decisions
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Programmed decisions
 Made using a rule, procedure, or quantitative
method
Management information systems
 Often used to support programmed decisions
Nonprogrammed decisions
 Deal with unusual or exceptional situations
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Optimization and Heuristic
Approaches
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Optimization model
 Will find the best solution
 Utilizes problem constraints
Heuristics (“rules of thumb”)
 Commonly accepted guidelines
 Usually find a good solution, but not the optimal
solution
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Management Information System
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Often used to
 Support programmed decisions made in response to
structured problems
Primary purpose
 To help individuals and organizations achieve their
goals
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Inputs to a Management
Information System
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Input data can originate from internal or external
sources
TPS
 Most significant internal source of data for the MIS
 Major activity is to capture and store data resulting
from ongoing transactions
Databases
 Supply data to MIS
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Outputs of a Management
Information System
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Scheduled reports
 Produced periodically or on a schedule
Key-indicator report
 Special type of scheduled report
 Summarizes previous day’s critical activities
 Available at the beginning of each workday
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Outputs of a Management
Information System (continued)
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Demand reports
 Give certain information at a person’s request
Exception reports
 Automatically produced when a situation is unusual
or requires action
 Used to help fight terrorism
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Decision Support Systems
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Focus is on decision-making effectiveness
Should assist people and organizations with all
aspects of decision making
The approach realizes that people, not machines,
make decisions
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Characteristics of a Decision
Support System
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Handle a Range of Data
Obtain and Process Data from Different Sources
Provide Report and Presentation Flexibility
Perform complex, sophisticated analysis and
comparisons using advanced software packages
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Characteristics of a Decision
Support System (continued)
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Support Optimization and Heuristic Approaches
Perform What-if and Goal-seeking Analysis
 What-if analysis
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Process of making hypothetical changes to problem
data and observing the impact on the results
Goal-seeking analysis
 Process of determining what problem data is required
for a given result
Simulation
 DSS attempts to mimic an event that could happen in
the future
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The Group Decision Support System
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DSS approaches
 Many not suitable for a group decision-making
environment
Group decision support system (GDSS)
 Also called a computerized collaborative work
system
 Hardware, software, people, databases, and
procedures needed to provide effective support in
group decision-making settings
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Characteristics of a GDSS
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Special Design
Flexibility
Anonymous Input
Reduction of Negative Group Behavior
Support of positive group behavior
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GDSS Software or Groupware
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Helps with joint work group scheduling,
communication, and management
Lotus Notes
 Popular groupware package
 Can capture, store, manipulate, and distribute
memos and communications
Using groupware
 Gives every employee rapid access to a vast source
of information
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Artificial Intelligence and SpecialPurpose Systems
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Artificial intelligence (AI)
 Computers with ability to mimic or duplicate the
functions of the human brain
Advances in AI
 Have led to systems that work like the human brain
to recognize complex patterns
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Artificial Intelligence and SpecialPurpose Systems
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AI systems are helping to
 Make medical diagnoses
 Explore for natural resources
 Determine what is wrong with mechanical devices
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The Difference Between Natural and
Artificial Intelligence
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One driving force behind AI research
 An attempt to understand how human beings
actually reason and think
Turing Test
 Attempts to determine if the responses from a
computer with intelligent behavior are
indistinguishable from responses from a human
 No computer has passed
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Components of Artificial
Intelligence
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Robotics
Vision systems
Natural language processing
Learning systems
Neural networks
Genetic algorithms
Intelligent agents
Expert systems
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Robotics
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Developing mechanical or computer devices to
 Perform tasks that require a high degree of
precision
Contemporary robotics
 Combine high-precision machine capabilities and
sophisticated controlling software
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Vision Systems
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Include hardware and software that
 Permit computers to capture, store, and manipulate
visual images and pictures
Can be used to give robots “sight”
U.S. Justice Department
 Makes use of vision systems to perform fingerprint
analysis
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Natural Language Processing
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Referred to as speech recognition
Allows computers to
 Understand and react to commands made in a
“natural” language
Three major challenges of natural language
 Interpreting ambiguous words
 Sentence parsing
 Being able to interpret the unique ways in which
people pronounce words
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Learning Systems
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Combination of software and hardware
 Allows computer to change how it functions or
reacts to situations based on feedback
Learning systems software
 Requires feedback on the results of its actions or
decisions
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Neural Networks
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Act like or simulate the functioning of a human brain
Features of neural networks
 Ability to retrieve information
 Fast modification of stored data
 Ability to discover relationships and trends in large
databases
 Ability to solve complex problems for which all
information is not present
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Fuzzy Logic
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Deals in probabilities rather than absolutes
Example of fuzzy logic
 Unclear terms, like “tall” or “many”
Fuzzy logic theory
 Allows people to incorporate interpretations and
relationships that are not completely precise
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Genetic Algorithms
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An approach to solving large, complex problems
Based on the theory of evolution
First step in generating the algorithm
 Change or vary a number of competing solutions to
the problem
Second step
 Select only the best models or algorithms, which
continue to evolve
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Intelligent Agents
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Also called an intelligent robot or bot
Consist of
 Programs and a knowledge base used to perform a
specific task
Used by the U.S. Army to
 Route security clearance information for soldiers
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Expert Systems
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Act or behave like a human expert in a field or area
Computerized expert systems have been developed
to
 Diagnose diseases given a patient’s symptoms
 Suggest the cause of a mechanical failure of an
engine
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Specialized Systems
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Virtual Reality Systems
 Computer-simulated environment or event
Geographic Information Systems
 Capable of storing, manipulating, and displaying
geographic or special information
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Specialized Systems (continued)
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Game Theory Systems
 Develop strategies for people who are competing
against each other
Other Specialized Systems
 Informatics
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Combines traditional disciplines with computer
systems and technology
Bioinformatics: combines biology and computer
science
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Summary
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Three phases of decision making
 Intelligence, design, and choice
Problem solving
 Takes decision making a step further
 Implements the choice
 Monitors the effects of the decision
MIS
 Provide managers with insight into the regular
operations of the organization
 Output
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Scheduled reports, demand reports, and exception
reports
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Summary (continued)
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Decision support systems
 Can handle large amount of data
 Can obtain and process data from different sources
 Can provide report and presentation flexibility
Group decision support system (GDSS)
 A computerized collaborative work system
Artificial intelligence (AI) includes
 Robotics
 Learning systems
 Neural networks
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