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MANAGING
INFORMATION
TECHNOLOGY
FIFTH EDITION
CHAPTER 7
MANAGERIAL SUPPORT SYSTEMS
E. Wainright Martin  Carol V. Brown  Daniel W. DeHayes
Jeffrey A. Hoffer  William C. Perkins
DECISION SUPPORT SYSTEMS
 Designed to assist decision
makers with unstructured
problems
 Usually interactive
 Incorporates data and
models
 Data often comes from
transaction processing
systems or data warehouse
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DECISION SUPPORT SYSTEMS
Three major components
© 2005 Pearson Prentice-Hall
Chapter 7 - 3
Figure 7.1 Decision Support Systems
Components
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DECISION SUPPORT SYSTEMS
 Specific DSSs – actual DSS applications that
directly assist in decision making
 DSS generator – a software package used to
build a specific DSS quickly and easily

Examples: Microsoft Excel or Lotus 1-2-3
DSS model 1
used to create
DSS generator
DSS model 2
DSS model 3
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DATA MINING
Data Mining – uses different technologies to
search for (mine) “nuggets” of information
from data stored in a data warehouse
 Data
mining software:
 Oracle 9i Data Mining and Oracle Data Mining Suite
 SAS Enterprise Miner
 IBM Intelligent Miner Modeling
 Angoss Software’s KnowledgeSEEKER, Knowledge Studio,
and KnowledgeExcelerator
 Datamation’s Data Mining and Business Intelligence Product
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DATA MINING
Data Mining – uses different technologies to
search for (mine) “nuggets” of information
from data stored in a data warehouse
 Decision
techniques used:
 Decision trees
 Linear and logistic regression
 Clustering for market segmentation
 Rule induction
 Nearest neighbor
 Genetic algorithms
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DATA MINING
 Uses:
 Cross-selling
 Customer
churn
 Customer retention
 Direct marketing
 Fraud detection
 Interactive marketing
 Market basket analysis
 Market segmentation
 Payment or default analysis
 Trend analysis
© 2005 Pearson Prentice-Hall
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see Table 7.1 Uses of Data Mining
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GROUP SUPPORT SYSTEMS
 Type of DSS to support a group rather than an
individual
 Specialized type of groupware
 Attempt to make group meetings more
productive
 Now focus on supporting team in all its
endeavors, including “different time, different
place” mode – virtual teams
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GROUP SUPPORT SYSTEMS
Traditional “same time, same place” meeting layout
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Figure 7.2 Group Support System Layout
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GEOGRAPHIC INFORMATION
SYSTEMS
GISs – systems based on manipulation of
relationships in space that use geographic
data
 Early
GIS users:
Natural resource management
Public administration
NASA and the military
Urban planning
Forestry
Map makers
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GEOGRAPHIC INFORMATION
SYSTEMS
Business Adopts Geographic Technologies
 Business
uses:
Determining site locations
Market analysis and planning
Logistics and routing
Environmental engineering
Geographic pattern analysis
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(Reprinted courtesy of Environmental Systems Research Institute, Inc. Copyright © 2003 Environmental Systems Research
Institute, Inc. All rights reserved.)
© 2005 Pearson Prentice-Hall
Chapter 7 - 12
Figure 7.3 Department Store Analysis
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GEOGRAPHIC INFORMATION
SYSTEMS
What’s Behind Geographic Technologies
 Approaches to representing spatial data:

Raster-based GISs – rely on dividing space into
small, uniform cells (rasters) in a grid

Vector-based GISs – associate features in the
landscape with a point, line, or polygon

Geodatabase model – uses object-oriented data
concepts
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GEOGRAPHIC INFORMATION
SYSTEMS
Coverage model uses
different layers to represent
similar types of geographic
features in the same area
© 2005 Pearson Prentice-Hall
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Figure 7.4 Map Layers in a GIS
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GEOGRAPHIC INFORMATION
SYSTEMS
What’s Behind Geographic Technologies
 Questions geographic analysis can answer:

What is adjacent to this feature?

Which site is the nearest one?

What is contained within this area?

Which features does this element cross?

How many features are within a certain distance
of a site?
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EXECUTIVE INFORMATION
SYSTEMS/BUSINESS INTELLIGENCE
SYSTEMS
EISs – a hands-on tool that focuses, filters, and organizes
an executive’s information so he or she can make more
effective use of it
Where does EIS data come from?
 Filtered and summarized transaction data (internal)
 Collected competitive information (internal and external)
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EXECUTIVE INFORMATION
SYSTEMS/BUSINESS INTELLIGENCE
SYSTEMS
 Executive information system (EIS):

Delivers online current information about
business conditions in aggregate form

Easily accessible to senior executives and
other managers

Designed to be used without intermediary
assistance

Uses state-of-the-art graphics,
communications and data storage methods
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(Courtesy of Geac Computer Corporation Limited. Copyright © 2003 Geac Computer Corporation Limited.)
© 2005 Pearson Prentice-Hall
Chapter 7 - 18
Figure 7.5 Example Geac Performance
Management Displays
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(Courtesy of Geac Computer Corporation Limited. Copyright © 2003 Geac Computer Corporation Limited.)
© 2005 Pearson Prentice-Hall
Chapter 7 - 19
Figure 7.5 Example Geac Performance
Management Displays
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KNOWLEDGE MANAGEMENT
SYSTEMS
 Knowledge management (KM):

Set of practical and action-oriented management
practices

Involves strategies and processes of identifying,
creating, capturing, organizing, transferring, and
leveraging knowledge to help compete

Relies on recognizing knowledge held by
individuals and the firm
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KNOWLEDGE MANAGEMENT
SYSTEMS
 Knowledge management system (KMS):

System for managing organizational knowledge

Technology or vehicle that facilitates the sharing
and transferring of knowledge so that valuable
knowledge can be reused

Enable people and organizations to enhance
learning, improve performance, and produce longterm competitive advantage
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ARTIFICIAL INTELLIGENCE
AI – the study of how to make computers
do things that are currently done better by
people
 Six areas:






© 2005 Pearson Prentice-Hall
Natural languages
Robotics
Perceptive systems
Genetic programming
Expert systems
Neural networks
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ARTIFICIAL INTELLIGENCE
AI – the study of how to make computers
do things that are currently done better by
people
 Six areas:






© 2005 Pearson Prentice-Hall
Natural languages
Robotics
Perceptive systems
Genetic programming
Expert systems
Neural networks
Chapter 7 - 23
Most relevant for
managerial support
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EXPERT SYSTEMS
Expert systems – attempt to capture the
expertise of humans in a computer program
 Knowledge engineer:

A specially trained systems analyst who works
closely with one or more experts in the area of
study

Tries to learn about how experts make decisions

Loads information (what learned) into module
called knowledge base
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EXPERT SYSTEMS
© 2005 Pearson Prentice-Hall
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Figure 7.6 Architecture of an Expert System
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EXPERT SYSTEMS
Obtaining an Expert System
 Approaches:
 Buy
a fully developed system created
for a specific application
 Develop
using a purchased expert
system shell (basic framework) and
user-friendly special language
 Have
knowledge engineers custom
build using special-purpose language
(such as Prolog or Lisp)
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EXPERT SYSTEMS
Examples of Expert Systems

Standford University’s MYCIN – to diagnose and
prescribe treatment for meningitis and blood diseases

General Electric’s CATS-1 to diagnose mechanical
problems in diesel locomotives

AT&T’s ACE to locate faults in telephone cables

Market Surveillance software – to detect insider trading

FAST software – for credit analysis, used by banking
industry

Nestle Food’s developed system to provide employees
information on pension fund status
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NEURAL NETWORKS
Neural networks – attempt to tease out meaningful patterns
from vast amounts of data
 Process:
1.
2.
3.
4.
5.
6.
Program given set of data
Program analyzed data, works out correlations, selects
variables to create patterns
Pattern used to predict outcomes, then results
compared to known results
Program changes pattern by adjusting variable weights
or variables themselves
Repeats process over and over to adjust pattern
When no further adjustment possible, ready to be used
to make predictions for future cases
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NEURAL NETWORKS
© 2005 Pearson Prentice-Hall
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Table 7.2 Uses of Neural Networks
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VIRTUAL REALITY
Virtual reality – use of a computer-based system to create
an environment that seems real to one or more senses of
users
 Non-entertainment categories:



Training
Design
Marketing
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VIRTUAL REALITY
Training
U.S. Army to train tank crews
Amoco for training its drivers
Duracell for training factory workers on using new
equipment
Design
Design of automobiles
Walk-throughs of air conditioning/ furnace units
Marketing
Interactive 3-D images of products (used on the Web)
Virtual tours used by real estate companies or resort hotels
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VIRTUAL REALITY
Training
U.S. Army to train tank crews
Amoco for training its drivers
Duracell for training factory workers on using new
equipment
Design
Design of automobiles
Walk-throughs of air conditioning/ furnace units
Marketing
Interactive 3-D images of products (used on the Web)
Virtual tours used by real estate companies or resort hotels
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VIRTUAL REALITY
(Courtesy of Homestore, Inc. Copyright © 2004 Homestore, Inc.)
© 2005 Pearson Prentice-Hall
Chapter 7 - 33
Figure 7.7 Hometour 360o Virtual Tour
of Living Room
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