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CHAPTER 11
Managerial Support Systems
CHAPTER OUTLINE
 Managers and Decision Making
 Business Intelligence Systems
 Data Visualization Technologies
 Intelligent Systems
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How Managers Make Decisions
Herbert Simon’s
three-phase
process
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How Managers Make Decisions (cont.)
 Rational Managers follow Objective
Rationality
must know all the alternatives
 must know all the outcomes
 must optimize

 Administrative Decision-Makers follow
Bounded Rationality
Satisfice
 Adaptive decision-making

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Why Managers Need IT Support
 Large number of alternatives to be
considered
 Decisions under time pressure and
high degree of uncertainty
 Decisions are more complex
 Decision makers can be in different
locations and so is the information
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Business Intelligence (BI) Systems
 Applications that allow managers to
access, consolidate, and analyze vast
amounts of data for decision support

Multidimensional data analysis

Data mining

Decision support systems (DSS)

Digital Dashboards
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How Business Intelligence Works
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Data Mining
 Searching for valuable business
information in a large data warehouse.
 Two basic operations:

Predicting trends and behaviors

Identifying previously unknown patterns
and relationships

Example: targeted marketing in CRM
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Decision Support Systems (DSSs)
 Using analytical models to understand
relationships between decision variables
and outcomes

Mathematical models – e.g., Linear
Programming

Statistical models – e.g., Regression Analysis
 Emphasizing interactive problem-solving
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Common Analyses in DSS
 Used to examine alternative scenarios
 Sensitivity Analysis – understand how output
variables respond to changes in an input
variable
 What-if Analysis – understand how changes
in assumptions affect outcome
 Goal-Seeking Analysis – understand what it
takes to achieve a preset outcome
A Goal-Seeking example
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Digital Dashboards
 Previously called Executive Information
Systems, now no longer limited to executive
uses


Provide rapid access to summarized as well
as detailed information
Emphasize graphical support to allow easy
interpretation of patterns/trends
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Sample Performance Dashboard
(Figure 11.4)
An Executive
Dashboard
Demo
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Data Visualization Systems
 Making data easier to understand and use
Data Visualization in Action: Visa Operation Center East
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Virtual Reality: Flight or Driving
Simulator
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Geographic Information System
Example of data
visualization:
Hans Rosling at
the TED Talks
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Intelligent Systems
 Based on Advances in Artificial
Intelligence (AI)
 Uses sensors, software and computers
 Emulates / enhances human capabilities:
reasoning, learning, sensing, talking, etc.
Expert systems
 Natural Language Processing
 Neural networks

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Expert Systems (ESs)
 Codifies human expert knowledge to
analyze specific problems within a very
narrow domain
 System asks a series of questions
 Reasoning based on pattern matching
Matching user responses with predefined
rules
 If-then format

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Examples of ES Applications
 Medical Diagnosis
 Credit Card Fraud Detection
 Unusually large transaction amounts
 Unusual usage patterns
 Device Troubleshooting
 Quality Control in Auditing
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Natural Language Processing
 Speech (voice) recognition
 Natural language generation/voice
synthesis
 Natural language understanding
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Neural Networks
 A system of programs and data
structures that approximates the
operation of the human brain
 Particularly good at recognizing subtle,
hidden and newly emerging patterns
within complex data
 Requires extensive training with past
information (learning)
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Neural Network
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