Transcript McNurlin - 7th Edition

Supporting
Decision Making
Chapter 11
Information Systems Management In
Practice 7E
McNurlin & Sprague
PowerPoints prepared by Michael Matthew
Visiting Lecturer, GACC, Macquarie University – Sydney Australia
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
• As shown in the book’s framework figure, we distinguish
between procedure-based and knowledge-based
information-handling activities
• The two previous chapters, in Part III, dealt mainly with
building systems for procedure-based work
• This part focuses on supporting knowledge-based
activities: the systems that support people in performing
information-handling activities to solve problems, work
together, and share expertise
©2006 Barbara C. McNurlin. Published by Pearson Education.
11-2
©2006 Barbara C. McNurlin. Published by Pearson Education.
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Part IV: Systems for Supporting
Knowledge-Based Work cont.
• Chapter 11 discusses supporting decision making by first
presenting five underlying technologies and some
examples of their use:
–
–
–
–
–
Decision Support Systems (DSS)
Data Mining
Executive Information Systems (EIS), and
Expert Systems (ES)
Agent-based Modelling
• The chapter then discusses the fascinating subject of the
real-time enterprise, which has a goal of gaining
competitive edge by learning of an event as soon as
possible and then responding to that event quickly, if
©2006
Barbara C. McNurlin. Published by Pearson Education.
11-4
necessary
Part IV: Systems for Supporting
Knowledge-Based Work cont.
• Chapter 12 deals with supporting collaboration by
– First describing various kinds of groups
– Different systems that support their collaboration, and
– Finally how executives might think about managing
virtual organizations – an increasing phenomenon these
days
• Chapter 13 discusses supporting knowledge work
by presenting a model for thinking about how to
manage knowledge
– It ends with a discussion of computer ethics and
intellectual capital issues in this Internet era
©2006 Barbara C. McNurlin. Published by Pearson Education.
11-5
Chapter 11
• This lecture / chapter discusses technologies for
supporting decision making:
–
–
–
–
–
Decision Support Systems (DSS)
Data Mining
Executive Information Systems (EIS), and
Expert Systems
Agent-based Modelling
• It then discusses IT issues related to creating the realtime enterprise
• Case examples include: a problem-solving scenario, OreIda Foods, a major services company, Harrah’s
Entertainment, Xerox Corporation, General Electric,
American Express, Delta Air Lines, a real-time interaction
on a website, and Western Digital
©2006 Barbara C. McNurlin. Published by Pearson Education.
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Introduction
• Most computer systems support decision
making because all software programs
involve automating decision steps that people
would take
• Decision making is a process that involves a
variety of activities, most of which handle
information
• A wide variety of computer-based tools and
approaches can be used to confront the
problem at hand and work through its solution
©2006 Barbara C. McNurlin. Published by Pearson Education.
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A PROBLEM-SOLVING SCENARIO
Case Example – Supporting Decision Making
• Using an executive information system, (EIS)
to compare budget to actual sales
• Discover a sale shortfall in one region
• Searches for the cause of the shortfall
• But couldn’t find an answer
©2006 Barbara C. McNurlin. Published by Pearson Education.
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A PROBLEM-SOLVING SCENARIO
Case Example – Supporting Decision Making cont.
Investigate – several possible causes
• Economic Conditions – through the EIS & the Web
accesses:
– Wire services
– Bank economic newsletters
– Current business and economic publications
• Competitive Analysis – through the same sources
investigates whether competitors:
– Have introduced a new product
– Have launched an effective ad campaign
• Written Sales Report – browses the reports
– “Concept based” text retrieval system makes this easier
• A Data Mining Analysis
– Looking for any previously unknown relationships
©2006 Barbara C. McNurlin. Published by Pearson Education.
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A PROBLEM-SOLVING SCENARIO
Case Example – Supporting Decision Making cont.
• Then accesses a marketing DSS – includes a set of
models to analyze sales patterns by:
– Product
– Sales representative
– Major customer
Result – no clear problems revealed.
Action – hold a meeting, in an electronic meeting room
supported by group DSS (GDSS) software
• This scenario illustrates:
– The wide variety of activities involved in problem solving,
and
– The wide variety of technologies that can be used to assist
decision makers and problem solvers
©2006 Barbara C. McNurlin. Published by Pearson Education.
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Technologies that Support
Decision Making
• The purpose of tractors, engines,
machines etc. = to enhance humans’
physical capabilities
• The purpose of computers has been to
enhance our mental capabilities
• Hence, a major use of IT is to relieve
humans of some decision making or
help us make more informed decisions
©2006 Barbara C. McNurlin. Published by Pearson Education.
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Technologies that Support Decision Making
Decision Support Systems
• Systems that support, not replace, managers in their
decision-making activities
• Decision modeling, decision theory, and decision
analysis, attempt to make models from which the ‘best
decision’ can be derived, by computation
• DSS are defined as: Computer-based systems
– That help decision makers
– Confront ill-structured problems
– Through direct interaction
– With data and analysis models
• Wide range of technologies can be used to assist
decision makers and problem solvers
©2006 Barbara C. McNurlin. Published by Pearson Education.
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Decision Support Systems
The Architecture for DSSs
• Figure 11-1 shows the relationship between
the three components of the DDM model
• Software system in the middle of the figure
consists of:
– The database management system (DBMS)
– The model base management system (MBMS)
– The dialog generation and management system
(DGMS)
©2006 Barbara C. McNurlin. Published by Pearson Education.
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©2006 Barbara C. McNurlin. Published by Pearson Education.
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Decision Support Systems
The Architecture for DSSs cont.
The Dialog Component
• The DSS contains a dialog component to link the user to the system
• Was ‘mouse’ (Mac) now = browser interface
The Data Component
• Data sources – as the importance of DSS has grown, it has become
increasingly critical for the DSS to use all the important data sources
within and outside the organization
• Data warehousing
• Data mining
– Much of the work on the data component of DSS has taken the form of
activities in this area
The Model Component
•
Models provide the analysis capabilities for a DSS
– Using a mathematical representation of the problem, algorithmic processes
are employed to generate information to support decision making
©2006 Barbara C. McNurlin. Published by Pearson Education.
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Decision Support Systems
Types of DSS
•
The size and complexity of DSS range from large
complex systems that have many of the attributes of
major applications down to simple ad hoc analyses that
might be called end user computing tasks
•
Institutional DSSs tend to be fairly well defined
–
They are based on pre=defined data sources
•
–
•
Heavily internal with perhaps some external data
Use well established models in a prescheduled way
Quick-hit DSSs are developed quickly to help a manager
make either a one-time decision or a recurring one
–
–
Can be every bit as useful for a small or large company
Most today = Excel spreadsheets (and not ‘called’ DSS)
©2006 Barbara C. McNurlin. Published by Pearson Education.
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ORE-IDA FOODS
Case Example – Institutional DSS
•
•
Frozen food division of H.J. Heinz
Marketing DSS must support 3 main tasks in the
decision making process:
1.
2.
3.
•
•
Data retrieval – helps managers find answers to the question,
“what has happened?”
Market analysis – addresses the question, “Why did it
happen?”
Modeling – helps managers get answers to, “What will
happen if…?”
Modeling for projection purposes, offers the greatest
potential value of marketing management
For successful use – line managers must take over
the ownership of the models and be responsible for
keeping them up-to-date
©2006 Barbara C. McNurlin. Published by Pearson Education.
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A MAJOR SERVICES COMPANY
Case Example – “Quick Hit” DSS – Short Analysis Programs
• Considering – new employee benefit program: an
employee stock ownership plan (ESOP).
• Wanted a study made to determine the possible impact
of the ESOP on the company and to answer such
questions as:
– How many shares of company stock will be needed in 10,20
and 30yrs to support the ESOP?
– What level of growth will be needed to meet these stock
requirements?
• The information systems manager wrote a program to
perform the calculations & printed the results
• Results = showed the impact of the ESOP over a 30yr
period
– Surprising results
©2006 Barbara C. McNurlin. Published by Pearson Education.
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Technologies that Support Decision Making
Data Mining
• A promising use of data warehouses is to let the
computer uncover unknown correlations by
searching for interesting patterns, anomalies, or
clusters of data that people are unaware exist
• Called data mining, its purpose is to give people
new insights into data
• Also covered in Chapter 7
• Most frequent type of data mined = customer
data
©2006 Barbara C. McNurlin. Published by Pearson Education.
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HARRAH’S ENTERTAINMENT
Case Example – Data Mining (Customer)
• To better know its customers, Harrah’s encourages
them to sign up for its frequent-gambler card, Total
Rewards
• Harrah’s mined its Total Rewards database to
uncover patterns and clusters of customers
• It has created 90 demographic clusters, each of
which is sent different direct mail offers –
encouraging them to visit other Harrah’s casinos
– Profit and loss for each customer calculating the likely
‘return’ for every ‘investment’ it makes in that customer
©2006 Barbara C. McNurlin. Published by Pearson Education.
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HARRAH’S ENTERTAINMENT
Case Example – Data Mining (Customer) cont.
• Much of its $3.7B in revenues (and 80% of its
profits) comes from its slot machines and
electronic gaming-machine players
– Found = locals who played often
• It was not the ‘high rollers’ who were the most
profitable
• Within the first two years of operation of Total
Rewards, revenue from customers who
visited more than one Harrah’s casino
increased by $100 million
©2006 Barbara C. McNurlin. Published by Pearson Education.
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Technologies that Support Decision Making
Executive Information Systems (EIS)
•
As the name implies EISs are for use by executives
•
They have been used for the following purposes:
1. Gauge company performance: sales, production,
earnings, budgets, and forecasts
2. Scan the environmental: for news on government
regulations, competition, financial and economics
developments, and scientific subjects
©2006 Barbara C. McNurlin. Published by Pearson Education.
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Technologies that Support Decision Making
Executive Information Systems (EIS) cont.
•
EIS can be viewed as a DSS that:
1. Provides access to summary performance data
2. Uses graphics to display and visualize the data in an
easy-to-use fashion, and
3. Has a minimum of analysis for modeling beyond the
capability to “drill down” in summary data to
examine components
•
In many companies, the EIS is called a
dashboard and may look like a dashboard of a
car
©2006 Barbara C. McNurlin. Published by Pearson Education.
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XEROX CORPORATION
Case Example – Executive Information System
• The EIS at Xerox began small and
evolved to the point where even skeptical
users became avid supporters
• Its objective was to improve
communications and planning, such as
giving executives pre-meeting documents
• It was also used in strategic planning and
resulted in better plans, especially across
divisions
©2006 Barbara C. McNurlin. Published by Pearson Education.
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Executive Information Systems (EIS)
Pitfalls in EIS Development
1. Lack of executive support: executives must provide
the funding, but are the principal users and supply the
needed continuity
2. Undefined system objectives: the technology, the
convenience, and the power of EIS are impressive,
but the underlying objectives and business values of
an EIS must be carefully thought through
3. Poorly defined information requirements: EIS typically
need non - traditional information sources judgments, opinion, external text-based documents in addition to traditional financial and operating data
©2006 Barbara C. McNurlin. Published by Pearson Education.
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Executive Information Systems (EIS)
Pitfalls in EIS Development cont.
4.
Inadequate support staff: support staff must:
–
–
–
Have technical competence
Understand the business, and
Have the ability to relate to the varied responsibilities and work patterns
of executives
5.
Poorly planned evolution: highly competent system professionals
using the wrong development process will fail with EIS
•
EIS are not developed, delivered, and then maintained
–
They should evolve over a period of time under the leadership of a team
that includes:
•
•
•
•
•
The executive sponsor
The operating sponsor
Executive users
The EIS support staff manager, and
The IS technical staff
©2006 Barbara C. McNurlin. Published by Pearson Education.
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Executive Information Systems (EIS)
Why Install an EIS?
• Attack a critical business need: EIS can be viewed as an
aid to dealing with important needs that involve the future
health of the organization
• A strong personal desire by the executive: The executive
sponsoring the project may
– Want to get information faster than he/she is now getting it, or
– Have a quicker access to a broader range of information, or
– Have the ability to select and display only desired information and
to probe for supporting detail, or
– To see information in graphical form
©2006 Barbara C. McNurlin. Published by Pearson Education.
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Executive Information Systems (EIS)
A Weak Reason to Install an EIS
• “The thing to do”: An EIS is seen as something
that modern management must have, in order
to be current in management practices
• The rationale given is that the EIS will increase
executive performance and reduce time that is
wasted looking for information and by such
things as telephone tag
©2006 Barbara C. McNurlin. Published by Pearson Education.
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Executive Information Systems (EIS)
What Should the EIS Do?
• A Status Access System: Filter, extract,
and compress a broad range of up-todate internal and external information
–
–
–
It should call attention to variances from plan.
It should also monitor and highlight the critical
success factors of the individual executive user
EIS is a structured reporting system for executive
management, providing the executive with the data
and information of choice and desired form
©2006 Barbara C. McNurlin. Published by Pearson Education.
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GENERAL ELECTRIC
Case Example – Executive Information System
• Most senior GE executives have a real-time view of
their portion of GE via an executive dashboard
– Each dashboard compares expected goals (sales, response
times, etc) with actual, alerting the executive when gaps of a
certain magnitude appear
• GE’s goal is to gain better visibility into all its operations
in real time and give employees a way to monitor
corporate operations quickly and easily
• The system is based on complex enterprise software
that interlinks existing systems
• GE’s actions are also moving its partners and business
ecosystem closer to real-time operation
©2006 Barbara C. McNurlin. Published by Pearson Education.
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Technologies that Support Decision Making
Expert Systems
•
A real-world use of artificial intelligence (AI)
–
–
•
AI is a group of technologies that attempts to mimic our senses
and emulate certain aspects of human behavior such as
reasoning and communication
Promising for 40 years +. Now = finally living up to promise
An expert system is an automated type of analysis or
problem-solving model that deals with a problem the way
an “expert” does
–
Note: Expert Systems are not new


LISP
Prolog
– Languages in the ’70s
©2006 Barbara C. McNurlin. Published by Pearson Education.
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Technologies that Support Decision Making
Expert Systems
•
•
cont.
The process involves consulting a base of
knowledge or expertise to reason out an answer
based on the characteristics of the problem
Like DSSs, they have:
– A user interface
– An inference engine, and
– Stored expertise (in the form of a knowledge base)
•
The inference engine is that portion of the
software that contains the reasoning methods
used to search the knowledge base and solve
the problem
©2006 Barbara C. McNurlin. Published by Pearson Education.
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Expert Systems
Knowledge Representation
•
Knowledge can be represented in a number of ways:
1. One is as cases; case-based reasoning expert systems
using this approach draw inferences by comparing a current
problem (or case) to hundreds or thousands of similar past
cases
2. A second form is neural networks, which store knowledge
as nodes in a network and are more intelligent than the
other forms of knowledge representation because they can
learn
3. Third, knowledge can be stored as rules (the most common
form of knowledge representation), which are obtained from
experts drawing on their own expertise, experience,
common sense, ways of doing business, regulations, and
laws
©2006 Barbara C. McNurlin. Published by Pearson Education.
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©2006 Barbara C. McNurlin. Published by Pearson Education.
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AMERICAN EXPRESS
Case Example – Expert System
• One of the first commercially successful ESs and a
fundamental part of the company’s everyday credit card
operation
• Authorizer’s Assistant is an expert system that
approves credit at the point of sale
• It has over 2,600 rules and supports all AmEx card
products around the world
• Authorizes credit by looking at:
– Whether cardholders are creditworthy
– Whether they have been paying their bills
– Whether a purchase is within their normal spending patterns
• It also assesses whether the request for credit could be
a potential fraud
©2006 Barbara C. McNurlin. Published by Pearson Education.
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AMERICAN EXPRESS
Case Example – Expert System
cont.
• The most difficult credit-authorization decisions
are still referred to people
• Avoids ‘sensitive’ transactions
– Restaurants
– Airline queues
• The rules were generated by interviewing
authorizers with various levels of expertise –
comparing good decisions to poor decisions
• The system can be adapted quickly to meet
changing business requirements
©2006 Barbara C. McNurlin. Published by Pearson Education.
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Expert Systems
Degree of Expertise
1. As an assistant, the lowest level of expertise, the
expert system can help a person perform routine
analysis and point out those portions of the work
where the expertise of the human is required
2. As a colleague, the second level of expertise, the
system and the human can “talk over” the problem
until a “joint decision” has been reached
3. As an expert, the highest level of expertise, the
system gives answers that the user accepts,
perhaps without question
©2006 Barbara C. McNurlin. Published by Pearson Education.
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Agent –Based Modelling
• A simulation technology for studying emergent
behaviour (e.g. traffic jam) that emerges from the
decisions of a large number of distinct individuals
(drivers)
– Simulation contains computer generated agents, each
making decisions typical of the decisions an individual
would make in the real world
• Trying to understand the mysteries of why businesses, markets,
consumers, and other complex systems behave as they do
• Some examples:
–
–
–
–
Nasdaq; Change its tick size
Retailer = redesign its incentive program
Southwest Airlines = revamp its cargo operations
Company changing its recruiting practices
©2006 Barbara C. McNurlin. Published by Pearson Education.
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Technologies that Support Decision Making
Conclusion
•
•
•
This section has discussed five seemingly
competing technologies that support decision
making
In reality they often overlap and combine
The next section demonstrates how these
decision support technologies and other
technologies are being mixed and matched to
form the foundation for the real-time enterprise
©2006 Barbara C. McNurlin. Published by Pearson Education.
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Toward the Real-Time Enterprise
• Through IT, organizations have been able to see the
status of operations more and more toward real time
• The Internet is giving companies a way to
disseminate closer-to-real-time information about
events
• The essence of the phrase real-time enterprise is that
organizations can know how they are doing at the
moment, rather than have to wait days, weeks, or
months for analysis results
©2006 Barbara C. McNurlin. Published by Pearson Education.
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Toward the Real-Time Enterprise cont.
• It is occurring on a whole host of fronts,
including:
– Enterprise nervous systems
• To coordinate company operations
– Straight-through processing
• To reduce distortion in supply chains
– Real-time CRM
• To automate decision making relating to
customers, and
– Communicating objects
• To gain real-time data about the physical world
©2006 Barbara C. McNurlin. Published by Pearson Education.
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Toward the Real-Time Enterprise
Enterprise Nervous Systems
 These are the technical means to a real-time
enterprise
 They are:
– Message based - because sending messages is efficient
and effective in dispersing information among parties
simultaneously
– Event driven - when an event occurs, it is recorded and
made available
– Use a publish and subscribe approach - the event is
“published” to an electronic address and any system,
person, or device authorized to see that information can
“subscribe” to that address’s information feed, and
– Use common data formats - data formats from disparate
systems are reduced to common denominators that can be
understood by other systems and hence shared
©2006 Barbara C. McNurlin. Published by Pearson Education.
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DELTA AIRLINES
Case Example – Enterprise Nervous Systems
• Delta has built an enterprise nervous system to manage its gate
operations by incorporating the disparate systems the airline had in
the late 1990s
• Information about each flight is managed by the system, in real
time, and everyone who needs to know about a change can get
the data
• The system uses a publish-and-subscribe approach using
enterprise application integration (EAI) products, whereby the
messaging middleware allows disparate applications to share data
• When an event occurs, it ripples to everyone
• Delta is now expanding those ripples out to their partners who
serve their passengers, such as caterers and security companies
©2006 Barbara C. McNurlin. Published by Pearson Education.
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Toward the Real-Time Enterprise
Straight-Through Processing
• The notion of a real-time enterprise has
generated two “buzzwords”
• One is zero latency, which means reacting
quickly to new information (with no wait time)
• The second is straight-through processing,
which means that transaction data are entered
just once in a process or a supply chain (like at
Delta)
• The goal is to reduce lags and latency in supply
chains
©2006 Barbara C. McNurlin. Published by Pearson Education.
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Toward the Real-Time Enterprise
Real-Time CRM
 Another view of a real-time response
might occur between a company and a
potential customer
- Perhaps via a customer call center or a
Website
©2006 Barbara C. McNurlin. Published by Pearson Education.
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A REAL-TIME INTERACTION ON A WEB SITE
Case Example – Real-Time CRM
• E.piphany CRM software example
• A potential guest visits the Website of a hotel
chain, checking for a hotel in Orlando
– The real-time CRM system initiates requests to
create a profile of the customer
• All past interactions with that customer
• Past billing information
• Past purchasing history
• Using this information, it makes real-time offers
to the Website visitor, and the visitor’s
responses are recorded and taken into account
for future Website visitors
©2006 Barbara C. McNurlin. Published by Pearson Education.
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©2006 Barbara C. McNurlin. Published by Pearson Education.
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Toward the Real-Time Enterprise
Communicating Objects
 These are sensors and tags that provide
information about the physical world via realtime data
 A communicating object can tell you:
–
–
–
–
What it is attached to
Where it is located
Where it belongs, and
A lot more information about itself
• It is a radio frequency identification device
(RFID), also called “smart tags”
– Based on WW2 technology
©2006 Barbara C. McNurlin. Published by Pearson Education.
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Toward the Real-Time Enterprise
Communicating Objects cont.
 In Singapore, cars carry smart tags, and drivers
are charged variable prices for where they drive
in the city and when
– The prices are set to encourage or discourage
driving at different places at different times
– Also proposed for Sydney’s new toll ways
• It’s an example of real-time traffic control
• Smart tags will transform industries because
they will talk to one another (object-to-object
communication), changing how work is handled
©2006 Barbara C. McNurlin. Published by Pearson Education.
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Toward the Real-Time Enterprise
Vigilant Information Systems
• The premise of the real-time enterprise is not
only that it can capture data in real time, but
that it has the means to act on that data
quickly
• US Air Force pilot = bet he could win any
dogfight
– Never lost a bet, even to superior aircraft
– Called his theory OODA
• Observe where his challenger’s plane is
• Orient himself and size up his own vulnerabilities and
opportunities
• Decide which manoeuvre to take
• Act to perform it before the challenger could go through
the same four steps
©2006 Barbara C. McNurlin. Published by Pearson Education.
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WESTERN DIGITAL
Case Example: Vigilant Information Systems (OODA)
• PC disk manufacturer used OODA type of
thinking to move itself closer to operating in
real time with a sense-and-respond culture
that aims to operate faster than its
competitors
• Built what they call a Vigilant Information
System (VIS) which they define as a system
that is “alertly watchful”
– Complex and builds on the firm’s legacy systems
– Essentially has four layers – Figure 11-5
©2006 Barbara C. McNurlin. Published by Pearson Education.
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©2006 Barbara C. McNurlin. Published by Pearson Education.
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WESTERN DIGITAL
Case Example: Vigilant Information Systems (OODA) cont.
•
VIS had to be complemented by appropriate business
processes
–
–
To operate inside it competitors OODA loops
Three new company policies were drafted
1.
2.
3.
–
–
–
•
Company’s strategic goals must be translated into time based
objectives and aligned across the company
KPIs must be captured in real time and be comparable
Collaborative decision making to co-ordinate actions company-wide
Shop-Floor OODA loop
Factory OODA loop
Corporate OODA loop
Benefits of the VIS
–
Quickened all 3 OODA loops and helped to link decisions across
them
Corporate performance improved measurably
–
•
–
Margins doubled since introduction 3 years ago
Sense and response culture where Western digital learns and
adapts quickly in a coordinated fashion
©2006 Barbara C. McNurlin. Published by Pearson Education.
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Toward the Real-Time Enterprise
The Dark Side of Real Time
• What are the drawbacks of real-time activities?
– Object-to-object communication could compromise
privacy, since knowing the exact location of a company
truck every minute of the day and night can be
construed as invading the driver’s privacy
 That’s a political issue, not a technical issue, and many CEOs
are going to face this question in the future
– Also, in the era of speed, a situation can become very
bad very fast, so people must be constantly watching
for signals that something negative is likely to happen
• Need for circuit breakers? e.g. NYSE
©2006 Barbara C. McNurlin. Published by Pearson Education.
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Conclusion
• Use of IT to support decision making covers a
broad swath of territory
• Some technologies aim to alert people to
anomalies, discontinuities, and shortfalls
• Others aim to make decisions, either as
recommendations to people or to act on
behalf of people
• Handing over decisions to systems has its
pros and cons, thus their actions need to be
monitored
©2006 Barbara C. McNurlin. Published by Pearson Education.
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Conclusion cont.
• CIOs need to alert their management team of
potential social and economic effects of
computer-based decision making because
errant computer-based decisions have
devastated corporate reputations and cost a
lot of money
• With vendors pushing toward the real-time
enterprise, this is a use of computers that
should give pause to explore the ramifications
©2006 Barbara C. McNurlin. Published by Pearson Education.
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