Transcript PPT Notes
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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