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© 2009 Pearson Education, Inc. Publishing as Prentice Hall
Supporting Information-Centric Decision
Making
Chapter 12Information Systems
Management in Practice
8th Edition
12-2
© 2009 Pearson Education, Inc. Publishing as Prentice Hall
Part IV: Systems for Supporting Knowledge-Based Work
This part consists of three chapters that discuss supporting three kinds of work—decision making, collaboration, and knowledge work
Procedure-based versus knowledge-based information-handling activities Part III dealt with procedural-based work Part IV focuses on knowledge-based work
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© 2009 Pearson Education, Inc. Publishing as Prentice Hall
Chapter 12
Introduction Technologies-supported decision making
Building timely business intelligence Decision support systems Data mining Executive information systems Expert systems Agent-based modeling
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© 2009 Pearson Education, Inc. Publishing as Prentice Hall
Chapter 12 cont’d
Toward the real-time enterprise Enterprise nervous systems Straight-through processing Real-time CRM Communicating objects Vigilant information systems Requisites for successful real-time management
Conclusion
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© 2009 Pearson Education, Inc. Publishing as Prentice Hall
Introduction
Decision making is a process that involves a variety of activities, most of which handle information
Most computer systems support decision making by automating decision processes
A wide variety of computer-based tools and approaches can be used to solve problems.
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A Problem-Solving Scenario
Case Example: Supporting decision making1. Use of executive information systems (EIS) to
compare budget to actual sales2. Discovery of a sale shortfall in one region3. Analysis of possible cause(s) of the shortfall
Economic conditions, competitive analysis, data mining, sales reports
Sales pattern via marketing DSS Brainstorming session via GDSS
4. No discernable singular cause5. Solution: Multimedia sales campaign
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Technologies-Supported Decision Making
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© 2009 Pearson Education, Inc. Publishing as Prentice Hall
Building Timely Business Intelligence
Business intelligence (BI) is a broad set of concepts, methods and technologies to improve context-sensitive business decisions Gather, filter and analyze large quantities of data from
various sources
Sense-making is central to BI Ability to be aware and assess situations that seem
important to the organization Awareness: Inductive process (data-driven) Assessment: Fitting observed data into a pre-determined
model
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© 2009 Pearson Education, Inc. Publishing as Prentice Hall
Decision Support Systems
Computer-based systems that help decision makers confront ill-structured problems through direct interaction with data and analysis models.
Architecture for DSS Dialog-Data Model (DDM)
Ad hoc information requests Specific data query
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Components of a Decision Support System
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© 2009 Pearson Education, Inc. Publishing as Prentice Hall
ORE-IDA Foods
Case Example: Institutional DSS Frozen food division of H.J. Heinz Marketing DSS must support three main tasks in
decision making process:1. Data retrieval
• “What has happened?”2. Marketing analysis (70% of DSS function)
• “Why did it happen?”3. Modeling
• “What will happen if…?” Modeling for projection purposes offers greatest
potential value of marketing management
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© 2009 Pearson Education, Inc. Publishing as Prentice Hall
A Major Services Company
Case Example: ‘Quick Hit’ DSS - short analysis programs
Employee stock ownership plan (ESOP) Determine possible impact of the ESOP on the company
and answer questions including How many company shares needed in 10-30 years? Level of growth needed to meet stock requirements?
IS manager wrote a program to perform calculations Program produced impact projections of ESOP over 30-
year period (surprising results) DSS program subsequently expanded to other employee
benefit programs
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© 2009 Pearson Education, Inc. Publishing as Prentice Hall
Data Mining
Use of computers to uncover unknown correlations from a large data set Classes Clusters Associations Sequential patterns
Data mining gives people insights into data Customer data
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© 2009 Pearson Education, Inc. Publishing as Prentice Hall
Harrah’s Entertainment
Case Example: Data Mining (Customer) Total Rewards Program
Mined customer data to create 90 demographic clusters for different direct mail offers Calculates the ROI on each customer Found that 80% of profits from slot machine and
electronic game machine players rather than ‘high rollers’
Within first two years of program, revenue from repeat customers increased by $100 million
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© 2009 Pearson Education, Inc. Publishing as Prentice Hall
Executive Information Systems
EIS an “executive summary” form of DSS Used to gauge company performance, address a
critical business need and scan the environment1. Provides access to summary performance data
2. Uses graphics to display and visualize the data in a user-friendly fashion
3. Has a minimum of analysis for modeling capability beyond that for examining summary data
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© 2009 Pearson Education, Inc. Publishing as Prentice Hall
Xerox Corporation
Case Example: Executive Information Systems Objective for EIS at Xerox was to improve
communications and strategic planning Quick access to related information at the right time
Executive meetings More efficient and better planning, especially across
divisions Explore relationships between plans and activities at
several divisions Xerox corporate chief of staff was executive sponsor
of EIS development
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© 2009 Pearson Education, Inc. Publishing as Prentice Hall
Executive Information Systems cont’d
Pitfalls for EIS development1. Lack of executive support
2. Undefined system objectives
3. Poorly defined information requirements
4. Inadequate support staff
5. Poorly planned evolution (expansion of EIS)
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© 2009 Pearson Education, Inc. Publishing as Prentice Hall
General Electric
Case Example: Executive Information Systems Most senior GE executives have a real-time view of
their portion of GE via “dashboard” GE’s goal is to gain visibility into all its operations in
real time and give managers a way to monitor operations quickly and easily EIS based on complex enterprise software that interlinks
existing systems
GE’s actions are also moving its partners and business ecosystem closer to real-time operations
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© 2009 Pearson Education, Inc. Publishing as Prentice Hall
Expert Systems
Expert systems are a real-world use of artificial intelligence (AI) AI mimics human cognition and communication to
analyze a situation or solve a problem e.g. MIT’s Commonsense Computing project
Expert system components User interface Inference engine
Reasoning methods Knowledge base
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© 2009 Pearson Education, Inc. Publishing as Prentice Hall
Expert Systems cont’d
Knowledge representation Cases
Knowledge from hundreds or thousands of cases to draw inferences from
Neural networks Knowledge stored as nodes in a network (adaptive
learning) Rules
Knowledge obtained from human experts drawing on own expertise, experience, common sense, regulations, laws and regulations
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© 2009 Pearson Education, Inc. Publishing as Prentice Hall
American Express
Case Example: Expert System Authorizer’s Assistant one of most successful
commercial uses of expert system Approves all AmEx credit card transactions and assesses
for fraud based on over 2600 rules Credit worth of card holders Bill payment Purchases within normal spending pattern
Rules derived from authorizers with various levels of expertise Customer sensitive (to avoid customer embarrassment) Can be changed to meet changing business demands
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© 2009 Pearson Education, Inc. Publishing as Prentice Hall
Agent-Based Modeling
A simulation technology for studying emergent behavior (from large number of individuals) Simulation contains “software agents” making decisions to
understand behavior of markets and other complex systems
Nasdaq Example Performed simulation to investigate effect of switch in tick
size from fixed eighths (.125) to decimals Found increase in buy-ask price spread instead of initially
predicted decrease because of the reduction in market’s ability to do price discovery
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© 2009 Pearson Education, Inc. Publishing as Prentice Hall
Toward Real-Time Enterprise
This section builds on the five different types of decision support technologies and demonstrates how they can be mixed and matched to form the foundation for the real-time enterprise
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© 2009 Pearson Education, Inc. Publishing as Prentice Hall
Toward the Real-Time Enterprise
IT, especially the Internet, is giving companies a way to know how they are doing “at the moment” and disseminate the closer-to-real-time information about events
Occurring on a whole host of fronts including Enterprise nervous systems
Coordinate company operations Straight-through processing
Reduce distortion in supply chains Communicating objects
Gain real-time data about the physical world
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© 2009 Pearson Education, Inc. Publishing as Prentice Hall
Enterprise Nervous Systems
A kind of network that connects people, applications and devices (buzz phrase?) Message-based
Messages are efficient and effective for dispersing information
Event driven Events are recorded and made available
Publish and subscribe approach Events are published to electronic address, which can be
subscribed to as an information feed Common data formats
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© 2009 Pearson Education, Inc. Publishing as Prentice Hall
Delta Airlines
Case Example: Enterprise Nervous Systems Delta integrated existing disparate systems to
build an enterprise nervous system to manage gate operations Information about each flight is managed in real-
time by the system System uses a publish-and-subscribe approach
using messaging middleware Delta is now expanding system out to their
partners who serve their passengers
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© 2009 Pearson Education, Inc. Publishing as Prentice Hall
Straight-Through Processing
Real-time information Zero latency
Quick reaction to new information
Straight-through processing means transaction data are entered just once in a process, especially a supply chain
Goal is to reduce bullwhip effect from process lags and latency
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Real-Time CRM
Another view of real-time response might occur between a company and a potential customer (touch points) Customer call Web site
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A Real-Time Interaction On a Web Site
An illustration of how real-time CRM works A potential guest visits the Web site of a hotel
chain The real-time CRM system initiates requests to create
profile of customer Past interactions with the customer Past billing information Past purchasing history
Using this information, it makes real-time offers to the visitor, and visitor’s responses are recorded and taken into account for Web site visits
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A Real-Time Interaction On a Web Site cont’d
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© 2009 Pearson Education, Inc. Publishing as Prentice Hall
Communicating Objects
These are “smart” sensors and tags that provide information about the physical world via real-time data radio frequency identification device (RFID)
pet micro-chips (satellite GPS), product tags
A tag can be passive (read-only) or active (send out signals)
Carries far more information than bar codes Item code, price and history
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© 2009 Pearson Education, Inc. Publishing as Prentice Hall
Communicating Objects cont’d
Example: Real-time electronic road pricing (ERP) system in Singapore to control traffic congestion Cars have smart card devices attached to their
windscreens Smart cards are debited (wirelessly) when cars
pass through gantries in certain areas of the city Variable pricing dependent on when and where
you drive
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© 2009 Pearson Education, Inc. Publishing as Prentice Hall
Vigilant Information Systems
The premise of a real-time enterprise is not only having the ability to capture data in real time, but also acting on that data quickly
US Air Force pilot’s OODA framework Never lost a dog-fight even to superior aircraft!
Observe where his challenger’s plane is Orient himself and size up his own vulnerabilities and
opportunities Decide which maneuver to take Act to perform before the challenger through the same four
steps
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© 2009 Pearson Education, Inc. Publishing as Prentice Hall
Western Digital
Case Example: Vigilant Information Systems PC disk manufacturer used OODA type of
thinking to move itself closer to operating in real-time with a sense-and-respond culture for competitive advantage
Built “alertly watchful” vigilant information system (VIS) Complex and builds on the firm’s legacy systems Essentially four layers
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Western Digital’s Vigilant Information Systems
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© 2009 Pearson Education, Inc. Publishing as Prentice Hall
Western Digital cont’d
Changed business processes to complement VIS to give Western Digital a way to operate inside competitors’ OODA loops Established new company policies
Translate strategic goals to time-based objectives Capture real-time key performance indicators (KPIs) Collaborate decision making and coordinate actions
Three levels of OODA loops to maximize VIS “alerts” Shop-floor, Factory, Corporate
Benefits of VIS Quickened all OODA loops and helped link decisions across
them, which ultimately led to significant increase in firm performance
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© 2009 Pearson Education, Inc. Publishing as Prentice Hall
Requisites for Successful Real-Time Management
Real-time data and real-time performance metrics Focus on high value-added data
Identify key activities and performance indicators that are needed in real time
Technology readiness Substantial computing resources
Integrated and seamless system that is capable of selecting, filtering and compiling data to send them in real time to designated users on demand.
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© 2009 Pearson Education, Inc. Publishing as Prentice Hall
Conclusion
Use of IT to support decision making covers a variety of functions including Alert, recommendation or decision making itself
Computer-supported decision making needs to be monitored
IS managers must comprehend the potentials and limitations of these technologies
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© 2009 Pearson Education, Inc. Publishing as Prentice Hall
All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic,
mechanical, photocopying, recording, or otherwise, without the prior written permission of the publisher. Printed in the United States of America.
Copyright © 2009 Pearson Education, Inc. Copyright © 2009 Pearson Education, Inc. Publishing as Prentice HallPublishing as Prentice Hall