Transcript Week10-BUAD283-Chp04

Management Information Systems
for the Information Age
Chapter 4:
Decision Support Systems
and Artificial Intelligence
Brainpower for Your Business
What Makes a Good Businessperson?
Your ability to…
Work with, motivate, and lead people
Identify and capitalize on opportunities
Recognize problems and devise solutions
Innovate, be creative, and think on the fringe
Make DECISIONS, DECISIONS, DECISIONS
Success is based on making good decisions:
IT can supplement human decision-making
IT can replace some human decision-making
Chapter 4: Decision Support and AI
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How Do You Make Good Decisions?
Understand the Question!
I seek not to know the answers, but to
understand the questions. Kwai Chang Caine.
Gather Good Information!
When you are educated, you'll believe only half
of what you hear. When you are intelligent,
you’ll know which half. Jerome Perryman.
Learn from Experience!
Experience teaches you to recognize a mistake
when you've made it again. Woodrow Wilson.
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Where Does IT Fit In?
The Role of IT in Decision-Making:
To increase an organization’s knowledgebase and
their capability for using this knowledge via
intelligent tools such as decision support systems
and artificial intelligence software
Primary Categories of Computer-Aided
Decision Support:
Decision Support
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Decision Support Systems
Performance Support Systems
Collaboration Systems
Geographic Information Systems
Artificial Intelligence
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Expert Systems
Neural Networks
Genetics Algorithms
Intelligent Agents
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Four Phases of Decision-Making
Understand the
similarity to other
structured process
models, such as:
Analysis
Design
Develop
Implement
Evaluate
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Types of Decisions: Difficulty Level
Structured Decision
Set of steps that if followed in a particular way
will always yield the correct answer
Doesn’t involve any feel or intuition
Easily programmed – inputs, processing, outputs
Non-Structured Decision
One for which there are no rules or criteria that
will guarantee a good solution
Usually have several “right” answers
Both controllable and uncontrollable variables
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Types of Decisions: Frequency
Recurring Decisions
One that happens repeatedly and, often,
periodically (daily, monthly, annually)
Usually based on the same set of rules each time
Non-Recurring Decisions
Ad-hoc or one that you make infrequently
Usually based on different criteria for determining the
best solution each time
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Types of IT Brainpower
Decision Support Systems (DSS)
Group Decision Support Systems (GDSS)
Geographic Information Systems (GIS)
Artificial Intelligence Systems (AI)
Expert Systems
Neural Networks
Genetic Algorithms
Intelligent Agents
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Chapter 4: Decision Support and AI
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Decision Support Systems (DSS) 1/3
A highly flexible and interactive IT system
that is designed to support decision-making
when the problem is not structured.
A DSS assists you in making a decision, as
opposed to making the decision for you.
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Decision Support Systems (DSS) 2/3
Objective is to improve your effectiveness as a
decision maker by providing useful and relevant
information when and where you need it.
But you must know the right questions to ask!
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Decision Support Systems (DSS) 3/3
A DSS can help you…
Decide where to spend advertising dollars
Forecast market and sales trends
Analyze consumer behavior
Analyze drug interactions
Develop airline schedules
Price products
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Components of a DSS
Data Management
allows you to store and access information
i.e., data warehouse or relational database
Model Management
allows you to store and access models
i.e., ANOVA or regression analysis
User Interface Management
allows you to easily manipulate, ask questions,
and interpret responses of models
i.e., Microsoft Excel, SPSS, STORM, in-house
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DSS Components Working Together
You tell the DSS which model
to use on what information
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Choosing the Right DSS Model
A model is a representation of some event,
fact or situation to represent variables and
their relationships
The model you use in DSS depends on the
decision you are making and, consequently,
the kind of analysis you require
What-If Analysis
Optimization
Goal-Seeking
Statistical Analysis
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Developing Your Own DSS
1.INTELLIGENCE
Do you need a DSS?
What should it do?
What information and models does it need?
2.DESIGN
What can you buy/build?
3.CHOICE
What will you buy/build?
4.IMPLEMENTATION
Build or install DSS
Learn, test, and evaluate the DSS
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Group Decision Support Systems (GDSS)
Called “Collaboration Systems” in Haag and
emphasizes sharing and flow of information
A type of decision support system that
facilitates the formulation of and solution to
problems by a team
A GDSS helps a team to generate ideas,
identify strengths and weaknesses, choose
an alternative, and reach a consensus
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Why Use a GDSS?
A GDSS can help you…
Determine new product designs
Evaluate the impact of new competition
Analyze geographical differences
Formulate a strategic plan
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Steps in Group Decision-Making
Brainstorming
Generate ideas
Issue Categorization and Analysis
Classify and organize the ideas
Ranking and Voting
Prioritize alternatives and reach consensus
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People in Group Decision-Making
GDSS Team:
People united by a common goal and connected
through information technology
GDSS Facilitator:
Non-technical role: run the meeting
Technical role: manage IT components
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IT in Group Decision-Making
Groupware
Software than enables teams to share
information and work collaboratively
DSS Capabilities
Software that enables team decision making,
including voting and ranking
Telecommunications
Hardware and software that connects computers
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Meetings Whenever and Wherever
Same-Time (Synchronous) Meetings
In the same room
In the same city
On the same planet
Different-Time (Asynchronous) Meetings
In the same city
On the same planet
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Examples of Collaboration Systems
Enterprise-wide collaboration
Lotus Notes Groupware
Microsoft Exchange
Supply chain collaboration
Extranets and Internet Portals
Web-based collaboration
Websites, VPNs, virtual workspaces, intranets
Peer-to-peer collaboration
Groove Networks
MSN Messenger
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Geographic Information Systems (GIS)
A type of decision support system that
works with spatial information
Spatial information is any information that can be shown in
map form, such as roads, the distribution of populations,
and the layout of electrical or telecommunications lines
A GIS represents information thematically in
overlapping layers, each of which shows a
different aspect of the total picture
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Examples of a GIS
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Why Use a GIS?
Today GISs are helping businesses:
Identify the best site to locate a branch office
Target pockets of potential customers
Reposition promotions and advertising
Determine the optimal location of a new
distribution outlet
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Artificial Intelligence (AI)
Whereas DSS systems augment business
brain power, Artificial Intelligence mimics or
imitates human thinking and behavior
Robots are a form of AI:
Mechanical devices equipped with simulated
human senses and the capability of taking action
on its own
i.e., a robot lawn mower, called the LawnNibbler,
cuts your lawn intelligently – avoiding dogs, kids,
fences, and other obstacles
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Is AI Really Being Used?
By financial analysts:
For managing assets and investing in stocks
By hospitals:
For scheduling staff and diagnosing illnesses
By credit card companies:
For detecting credit card fraud
By police and security organizations:
For predicting criminal behavior patterns
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Types of AI Systems for Business
Expert Systems
Neural Networks
Genetic Algorithms
Intelligent Agents
70% of Top 500 Companies use
AI as part of their Decision
Support
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Expert Systems
Also called “knowledge-based systems” or
“performance support systems”
Captures human expertise and then applies
reasoning capabilities to problems and offers
advice in the form of a conclusion
Useful for:
Diagnostic or “what’s wrong” problems
Prescriptive or “what should we do” problems
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Expert System vs. DSS
A DSS augments or assist you in making the
decision, but you must know how to reason
through the problem and proceed
An Expert System only requires that you
input the facts and symptoms of the
problem – it contains the know-how for
solving the problem (based on human
expertise)
Visit Whale Watcher
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People in an Expert System
Domain Expert
The person who knows how to solve the problem
without the aid of IT
Sometimes called SMEs (subject matter experts)
Knowledge Engineer
The person who builds the expert system
Knowledge Worker
The person who uses the expert system to solve
a problem
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IT in an Expert System
Knowledgebase
Stores the rules of the expert system
Knowedge acquisition
Used to capture and enter the rules
Inference engine
Takes the problem facts and searches the
knowledgebase for rules that fit
User interface
Used to run the consultation
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What Expert Systems Can Do
Handle massive amounts of information
Reduce errors
Reduce costs
Improve customer service
Provide consistency in decision making
Maintain an organization’s knowledge asset
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What Expert Systems Can’t Do
Handle all types of domain expertise
Solve problems other than those for which
they are designed
Apply common sense or judgment to a
problem
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Neural Networks
A type of artificial intelligence system which
is capable of learning because it’s patterned
after the human brain
A neural network simulates the human
ability to classify things based on the
experience of seeing many examples;
capable of differentiating patterns
Visit 20 Questions
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Examples of Neural Networks
PDA and Tablet PC handwriting recognition
Voice recognition systems like IBM ViaVoice
and Dragon Naturally Speaking
In business, they are used in:
Securities trading
Credit-card fraud detection
Real estate appraisal
Evaluating loan applications
Target marketing
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What Neural Networks Can Do
Neural networks can:
Learn by example
Adapt to new concepts and knowledge
Cope with huge volumes of information
Work without complete or structured information
Analyze nonlinear relationships in information
Recognize textual, visual, and auditory patterns
Most useful for identification, classification,
and prediction when a vast amount of
information is available
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Types of Neural Networks
Self-organizing neural network
Finds patterns and relationships in vast amounts
of data by itself (form of data mining)
i.e., credit-card fraud detection
Back-propagation neural network
A neural network that is trained by someone
i.e., voice recognition
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Genetic Algorithms
An artificial intelligence system that mimics
the evolutionary, survival-of-the-fittest
process to generate increasingly better
solutions to a problem
Systems that follow trial-and-error processes
that optimize systems in such a way that
they find the combination of inputs that give
the best outputs
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Applying Genetic Algorithms
They are used by business executives to help them
decide which combination of projects a firm should
invest in.
They are used by investment firms to help them in
trading choices and associated decisions.
Used in the garment industry to help solve the
problem of laying out pieces of the garment and
cutting fabric to ensure as little waste as possible.
Used to determine the optimal configuration of fiber
optic cable in a network that may include as many
as 100,000 connection points
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Concepts of Evolution in Genetic Algorithms
Selection
Survival of the fittest
Crossover
Combining portions of good outcomes in the
hope of creating an even better outcome
Mutation
Randomly trying combinations and evaluating
the success and/or failure of the outcome
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Intelligent Agents
An artificial intelligence system that can
move around your computer or network
performing repetitive tasks independently,
adapting itself to your preferences
An intelligent agent is like a travel agent in
that it performs tasks that you stipulate
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Types of Intelligent Agents
Four types of intelligent agents:
Buyer agents or shopping bots
User or personal agents
Monitoring-and-surveillance or predictive agents
Data-mining agents
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In Summary (1/3)
Information Technology (IT) can help you be
an effective decision maker by assisting you
in decision-making tasks with:
Decision support systems (DSS)
Group decision support systems (GDSS)
Geographic information systems (GIS)
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In Summary (2/3)
Information Technology (IT) can help you be
an effective decision maker by performing
tasks for you with AI using:
Expert systems
Neural networks
Genetic algorithms
Intelligent agents
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In Summary (3/3)
To benefit from the decision support
capabilities of Information Technology (IT)
you must know:
The nature of the problem
What questions you want to ask
What type of decision support tools can help
How to apply the decision support tools to the
problem
How to interpret the results
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