Transcript Management Information Systems Decision Support

Chapter 10 Decision Support
Systems
James A. O'Brien, and George Marakas
Management Information Systems, 9th ed.
Boston, MA: McGraw-Hill, Inc., 2009
ISBN: 13 9780073376769
McGraw-Hill/Irwin
Copyright © 2009 by The McGraw-Hill Companies, Inc. All rights reserved.
Learning Objectives
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Identify the changes taking place in the form and use of decision
support in business
Identify the role and reporting alternatives of management
information systems
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
Explain how the following information systems can support the
information needs of executives, managers, and business
professionals: EIS, Enterprise information portals, and KMS
Identify how neural networks, fuzzy logic, genetic algorithms,
virtual reality, and intelligent agents can be used in business
Give examples of several ways expert systems can be used in
business decision-making situations
10-2
Decision Support in Business
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Companies are investing in data-driven
decision support application frameworks to
help them respond to
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Changing market conditions
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Customer needs
This is accomplished by several types of
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Management information
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Decision support
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Other information systems
10-3
Levels of Managerial Decision Making
10-4
Information Quality
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Information products made more valuable by
their attributes, characteristics, or qualities
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Information that is outdated, inaccurate, or
hard to understand has much less value
Information has three dimensions
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Time
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Content
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Form
10-5
Attributes of Information Quality
10-6
Decision Structure
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Structured (operational)
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Unstructured (strategic)
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The procedures to follow when decision
is needed can be specified in advance
It is not possible to specify in advance
most of the decision procedures to follow
Semi-structured (tactical)
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Decision procedures can be pre-specified,
but not enough to lead to the correct decision
10-7
Decision Support Systems
Management Information
Systems
Decision Support
Systems
Decision
support
provided
Provide information about
the performance of the
organization
Provide information and
techniques to analyze
specific problems
Information
form and
frequency
Periodic, exception,
demand, and push reports
and responses
Interactive inquiries and
responses
Information
format
Prespecified, fixed format
Ad hoc, flexible, and
adaptable format
Information produced by
extraction and manipulation
of business data
Information produced by
analytical modeling of
business data
Information
processing
methodology
10-8
Decision Support Trends
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The emerging class of applications focuses on
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Personalized decision support
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Modeling
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Information retrieval
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Data warehousing
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What-if scenarios
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Reporting
10-9
Business Intelligence Applications
10-10
Decision Support Systems
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Decision support systems use the following to
support the making of semi-structured business
decisions
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Analytical models
Specialized databases
A decision-maker’s own insights and judgments
An interactive, computer-based modeling process
DSS systems are designed to be ad hoc,
quick-response systems that are initiated and
controlled by decision makers
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DSS Model Base
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Model Base
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A software component that consists of
models used in computational and analytical
routines that mathematically express relations
among variables
Spreadsheet Examples
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Linear programming
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Multiple regression forecasting
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Capital budgeting present value
10-12
Applications of Statistics and Modeling
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Supply Chain: simulate and optimize supply
chain flows, reduce inventory, reduce stock-outs
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Pricing: identify the price that maximizes
yield or profit
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Product and Service Quality: detect quality
problems early in order to minimize them
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Research and Development: improve quality, efficacy,
and safety of products and services
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Management Information Systems
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The original type of information system
that supported managerial decision making
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Produces information products that support
many day-to-day decision-making needs
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Produces reports, display, and responses
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Satisfies needs of operational and tactical decision makers
who face structured decisions
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Management Reporting Alternatives
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Periodic Scheduled Reports
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Exception Reports
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Reports about exceptional conditions
May be produced regularly or when an
exception occurs
Demand Reports and Responses
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Prespecified format on a regular basis
Information is available on demand
Push Reporting
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Information is pushed to a networked computer
10-15
Online Analytical Processing (OLAP)
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Enables managers and analysts to examine
and manipulate large amounts of detailed and
consolidated data from many perspectives
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Done interactively, in real time, with rapid
response to queries
10-16
Online Analytical Operations
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Consolidation
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Drill-Down
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Aggregation of data
Example: data about sales offices rolled up
to the district level
Display underlying detail data
Example: sales figures by individual product
Slicing and Dicing
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Viewing database from different viewpoints
Often performed along a time axis
10-17
Geographic Information Systems (GIS)
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DSS uses geographic databases to construct and
display maps and other graphic displays
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Supports decisions affecting the geographic
distribution of people and other resources
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Often used with Global Positioning Systems (GPS)
devices
10-18
Data Visualization Systems (DVS)
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Represents complex data using interactive,
three-dimensional graphical forms (charts,
graphs, maps)
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Helps users interactively sort, subdivide,
combine, and organize data while it is in its
graphical form
10-19
Using Decision Support Systems
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Using a decision support system involves an
interactive analytical modeling process
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Decision makers are not demanding
pre-specified information
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They are exploring possible alternatives
What-If Analysis
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Observing how changes to selected variables affect
other variables
10-20
Using Decision Support Systems
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Sensitivity Analysis
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Goal-seeking Analysis
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Observing how repeated changes to a single variable
affect other variables
Making repeated changes to selected variables until a
chosen variable reaches a target value
Optimization Analysis
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Finding an optimum value for selected variables, given
certain constraints
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Data Mining
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Provides decision support through knowledge
discovery
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Analyzes vast stores of historical business data
Looks for patterns, trends, and correlations
Goal is to improve business performance
Types of analysis
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Regression
Decision tree
Neural network
Cluster detection
Market basket analysis
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Market Basket Analysis
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One of the most common uses for data mining
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Determines what products customers purchase
together with other products
Results affect how companies
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Market products
Place merchandise in the store
Lay out catalogs and order forms
Determine what new products to offer
Customize solicitation phone calls
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Executive Information Systems (EIS)
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Combines many features of MIS and DSS
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Provide top executives with immediate and
easy access to information
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Identify factors that are critical to accomplishing
strategic objectives (critical success factors)
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So popular that it has been expanded to managers,
analysis, and other knowledge workers
10-24
Features of an EIS
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Information presented in forms tailored to the
preferences of the executives using the system
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Customizable graphical user interfaces
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Exception reports
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Trend analysis
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Drill down capability
10-25
Enterprise Information Portals
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An EIP is a Web-based interface and integration of
MIS, DSS, EIS, and other technologies
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Available to all intranet users and select
extranet users
Provides access to a variety of internal and external business
applications and services
Typically tailored or personalized to the user
or groups of users
Often has a digital dashboard
Also called enterprise knowledge portals
10-26
Expert Systems
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An Expert System (ES)
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A knowledge-based information system
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Contain knowledge about a specific, complex application area
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Acts as an expert consultant to end users
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Components of an Expert System
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Knowledge Base
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Facts about a specific subject area
Heuristics that express the reasoning procedures of an
expert (rules of thumb)
Software Resources
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An inference engine processes the knowledge
and recommends a course of action
User interface programs communicate with
the end user
Explanation programs explain the reasoning process to
the end user
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Components of an Expert System
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Methods of Knowledge Representation
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Case-Based
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Knowledge organized in the form of cases
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Cases are examples of past performance, occurrences,
and experiences
Frame-Based
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Knowledge organized in a hierarchy or
network of frames
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A frame is a collection of knowledge about
an entity, consisting of a complex package
of data values describing its attributes
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Methods of Knowledge Representation
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Object-Based
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Knowledge represented as a network of objects
An object is a data element that includes both data
and the methods or processes that act on those data
Rule-Based
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Knowledge represented in the form of rules
and statements of fact
Rules are statements that typically take the
form of a premise and a conclusion (If, Then)
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Expert System Application
Categories
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Decision Management
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Diagnostic/Troubleshooting
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Loan portfolio analysis
Employee performance evaluation
Insurance underwriting
Equipment calibration
Help desk operations
Medical diagnosis
Software debugging
Design/Configuration
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Computer option installation
Manufacturability studies
Communications networks
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Expert System Application
Categories (cont’d)
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Selection/Classification
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Material selection
Delinquent account identification
Information classification
Suspect identification
Process Monitoring/Control
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Machine control (including robotics)
Inventory control
Production monitoring
Chemical testing
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Benefits of Expert Systems
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Captures the expertise of an expert or group of
experts in a computer-based information system
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Faster and more consistent than an expert
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Can contain knowledge of multiple experts
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Does not get tired or distracted
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Cannot be overworked or stressed
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Helps preserve and reproduce the knowledge of human
experts
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Limitations of Expert Systems
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Limited focus
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Inability to learn
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Maintenance problems
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Development cost
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Can only solve specific types of problems in a
limited domain of knowledge
10-35
Knowledge Engineering
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A knowledge engineer
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Works with experts to capture the knowledge (facts and
rules of thumb) they possess
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Builds the knowledge base, and if necessary,
the rest of the expert system
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Performs a role similar to that of systems
analysts in conventional information systems development
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Intelligent Agents
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A software surrogate for an end user or a
process that fulfills a stated need or activity
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Uses built-in and learned knowledge base
to make decisions and accomplish tasks in
a way that fulfills the intentions of a user
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Also call software robots or bots
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User Interface Agents
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Interface Tutors – observe user computer operations,
correct user mistakes, provide hints/advice on efficient
software use
Presentation Agents – show information in a variety of
forms/media based on user preferences
Network Navigation Agents – discover paths
to information, provide ways to view it based
on user preferences
Role-Playing – play what-if games and other roles to help
users understand information and make better decisions
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Information Management Agents
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Search Agents – help users find files and databases, search
for information, and suggest and find new types of
information products, media, resources
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Information Brokers – provide commercial services to
discover and develop information resources that fit business
or personal needs
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Information Filters – Receive, find, filter, discard, save,
forward, and notify users about products received or
desired, including e-mail, voice mail, and other information
media
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