Transcript Learning Objectives - Eastern Michigan University

Chapter 10
Supporting Management
& Decision Making
1
Learning Objectives
 Describe the concepts of management, decision
making, and computerized support for decision
making.
 Justify the role of models in decision making.
 Describe the framework for computerized decision
support & classify problems & support according
to the framework.
 Describe decision support systems and their
benefits, and analyze their role in management
support.
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Learning Objectives
 Compare regular (personal) decision support
systems with group and organizational decision
support systems and analyze the major
differences.
 Describe enterprise and executive information
systems, and analyze their role in management
support.
 Explain how networks and the Web can enhance
managerial decision making.
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Case: Web-based Data Analysis at Shopko
Problem:
 The information systems that supported ShopKo’s business in the past
were highly fragmented, ineffective, and inflexible.
 Forecasts were inaccurate, and wrong decisions were frequently made.
Solution:
 The company installed comprehensive decision support system (DSS)
software (DSS Agent, from MicroStrategy).
 This system includes a data warehouse and online analytical processing.
Results:
 ShopKo’s investment into sophisticated web-based data analysis
enabled stores to carry the right merchandise at the right place & time.
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Lessons from the Case
 A solution to complex decisions can be enhanced with the use
of computer programs called a decision support system (DSS).
 Decisions are supported both in the sales and inventory areas.
 Much of the support is based around the concepts of data
warehousing and online analytical processing.

 The Web is playing an increasing role in facilitating purchasing.
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Managers & Decision Making
 Management is a process by which organizational goals are
achieved through the use of resources (people, money,
energy, materials, space, time).
 These resources are considered to be inputs, and the
attainment of the goals is viewed as the output of the
process.
 Managers oversee this process in an attempt to optimize it.
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The Manager’s Job
3 Categories
(Mintzberg ,1973)
1. Interpersonal roles: figurehead,
leader, liaison.
2. Informational roles: monitor,
disseminator, spokesperson.
3. Decisional roles: entrepreneur,
disturbance handler, resource
allocator, negotiator.
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The Manager’s Decision Role
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Decision Complexity
Decision making ranges from simple to very complex decisions that fall along a
continuum that ranges from structured to unstructured. Structured processes refer to
routine & repetitive problems with standard solutions. While Unstructured are "fuzzy,"
complex problems with no clear-cut solutions.
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Managerial Decisions & Computerized Support
 The success of management depends on the skillful execution of
managerial functions such as planning, organizing, directing, and
controlling.
 To carry out these functions, managers engage in the continuous
process of making decisions.
 Managers must learn how to use the new tools and techniques
that can help them make decisions.
 Computerized techniques support qualitative and quantitative decision
making.
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The Decision Making Process
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Modeling & Models
 A model (in decision making) is a simplified representation or
abstraction of reality.
 With modeling, one can perform virtual experiments and an
analysis on a model of reality, rather than on reality itself.
 Some Benefits of Modelling:
 The cost of virtual experimentation is much lower than the
cost of experimentation conducted with a real system.
 Models allow for the simulated compression of time.
 Manipulating the model (by changing variables) is much
easier than manipulating the real system.
 The cost of making mistakes during a real trial-and-error
experiment is much lower.
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4 Types of Models
 Iconic (Scale) Models. An
iconic model—the least abstract
model—is a physical replica of a
system, usually based on a
different scale from the original.
 Analog Models. An analog
model, in contrast to an iconic
model, does not look like the real
system but behaves like it.
 Mathematical (Quantitative)
Models. The complexity of
relationships in many systems
cannot conveniently be
represented. A more abstract
model is possible with the aid of
mathematics.
 Mental models provide a
subjective description of how a
person thinks about a situation.
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Why do Managers Need the Support of IT?
Making decisions while processing information manually is growing
increasingly difficult due to the following trends:
1. The number of alternatives to be considered is ever
increasing.
2. Many decisions must be made under time pressure.
3. Due to increased fluctuations & uncertainty in the
decision environment, it is frequently necessary to
conduct a sophisticated analysis to make a good
decision.
4. It is often necessary to access remote information,
consult with experts, or have a group decision-making
session, all quickly & in expensively.
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Determining the Information Needs of Managers
 Wetherbe approach (1991): Two-phase process.
 Phase I: a structured interview is conducted to determine managers’
perceived information needs.
 Phase I: a prototype of the information system is quickly constructed.
 Critical success factor (CSF) approach
 Watson and Frolick approach (1992): is based on the following
strategies:





determining information requirements
asking (the interview approach)
deriving the needs from an existing information system
synthesizing from characteristics of the systems
and discovering via evolving systems (prototyping)
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Management Support Systems (MSS]
 Four major information technologies have been successfully
used to support managers.
 DSSs: provide support primarily to analytical, quantitative
types of decisions.
 Executive (enterprise) support systems: support the
informational roles of executives.
 Group decision support systems: support managers
working in groups.
 Intelligent systems: provide mulitfunctional support.
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Framework for Computerized Decisions
 Managerial problems fall under 3 categories (Source:
Simon,1977):
 Structured problems: all phases—intelligence, design,
and choice—are structured & the procedures for
obtaining the best solution are known.
 Unstructured problems: none of the three phases—
intelligence, design, or choice—is structured, and human
intuition is frequently the basis for decision making.
 Semistructured problems: requires a combination of
standard solution procedures and individual judgment.
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Framework for Computerized Decisions (cont.)
 There are 3 broad categories that encompass all
managerial activities (Part ii Source: Anthony,1965):
 Strategic planning — the long-range goals & policies
for resource allocation;
 Management control — the acquisition & efficient
utilization of resources in the accomplishment of
organizational goals
 Operational control — the efficient & effective
execution of specific tasks.
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Management Science
 he Management Science approach maintains that managers
can follow a fairly systematic process for solving problems.
 Defining the problem (a decision situation that may deal with a
setback or with an opportunity).
 Classifying the problem into a standard category.
 Constructing a standard mathematical model that describes the
real-life problem.
 Finding potential solutions to the modeled problem and evaluating
them.
 Choosing & recommending a solution to the problem.
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Decision Support Systems [DSS]
 Decision Support System (DSS) = a computer-based
information system that combines models and data in an
attempt to solve semistructure problems with extensive
user involvement.
 The term decision support systems (DSS), like the terms
MIS and MSS, means different things to different people.
 DSS can be viewed as an approach or a philosophy rather
than a precise methodology.
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Case: Using DSS to Determine Risk
Problem:
 Houston Oil & Minerals Corporation was interested in a
proposed joint venture but requried a risk analysis.
Solution:
 Houston Oil built a DSS by means of a specialized planning
language. The results suggested that the project be accepted.
Results:
 The executive vice president, using his experience, judgment,
and intuition, decided to reverse the decision and rejected the
project.
 The DSS was flexible and responsive enough to allow managerial
intuition and judgment to be incorporated into the analysis.
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Characteristics of DSSs
 Provides support for decision makers at all management levels,
whether individuals or groups, by. bringing together human judgment
and objective information.
 Supports several interdependent and/or sequential decisions.
 Supports all phases of the decision-making process— intelligence,
design, choice, and implementation—as well as a variety of decisionmaking processes and styles.
 Is adaptable by the user over time to deal with changing conditions.
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Characteristics of DSSs (cont.)
 Is easy to construct and use in many cases.
 Promotes learning, which leads to new demands & refinement of the
application, which leads to additional learning, and so forth.
 Utilizes quantitative models (standard and/or custom made).
 Advanced DSSs are equipped with a knowledge management
component that allows the efficient and effective solution of very complex
problems.
 Can be disseminated for use via the Web.
 Allows the easy execution of sensitivity analyses.
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Components of a DSS System
 Data Management Subsystem contains all the necessary data
that flow from several sources and are extracted prior to their
entry to a DSS database.
 Model Management Subsystem contains completed models &
models’ building blocks necessary to develop DSS applications.
 This includes standard software with financial, statistical, management
science, or other quantitative models.
 Model Base Management System (MBMS) creates DSS
models easily and quickly, either from scratch, existing models,
or building blocks.
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DSS Users
 Staff Assistant. This person has
specialized knowledge about
management problems and some
experience with decision support
technology.
 Expert Tool User. This person is
skilled in the application of one or
more types of specialized
problem-solving tools. This user
performs tasks for which the
manager does not have the
necessary skills or training.
 Business (System) Analyst. This
person has a general knowledge
of the application area, formal
business administration education,
and considerable skill in DSS
construction tools.
 Group Facilitator. When group
decisions are supported by IT, it is
frequently beneficial to use a
process facilitator.
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The DSS Model
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Group Decision Support Systems
 Group decision support system (GDSS) = an interactive computerbased system that facilitates the solution of semistructured and
unstructured problems by a group of decision makers.
 The goal of GDSS is to improve the productivity of decision-making
meetings, either by speeding up the decision-making process or by
improving the quality of the resulting decisions, or both.
 The first generation of GDSS was designed to support face-to-face
meetings in what is called a decision room.
 Such a GDSS is composed of hardware, software, people and procedures.
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GDSS Components
Hardware. A group can use two types
of hardware configurations.
 a GDSS facility designed for
electronic meetings.
 a collection of PCs, equipped
with keypads for voting and
other groupware activities.
Software. Typical GDSS software is a
collection of about a dozen tools or
packages, which are integrated
into a comprehensive system.
People. The group members and
a facilitator.
Procedures. The procedures that
allow for ease of operation and
effective use of the technology
by group members.
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Case: The World Economic Forum (WEF)
Problem:
 WEF is a consortium of top business, government, academic, and
media leaders from virtually every country in the world.
 Until 1998 the members conferred privately or debated global issues at
meetings. Follow-up was difficult.
Solution:
 WEF developed a collaborative computing system called the World
Electronic Community (WELCOM).
 Provides members with a secure channel to send e-mail, read reports &
communicate in videoconferences.
Results:
 By 2001 the system was completely on the Web.
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Enterprise Decision Support
There are two main types of enterprise decision support system:
 Organizational decision support systems (ODSS) which focus
on an organizational task or activity involving a sequence of
operations and decision makers
 Computer-based systems can be developed to provide decision support
at the individual group or organization levels (Hackathorn and Keen,
1981).
 Executive information system (EIS), also known as an
Executive support system (ESS), is a technology designed in
response to managers’ specific needs.
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Characteristics of EISs
 The drill down capability enables
users to get details, and details of
details, of any given information.
 Trend analysis can be done using
forecasting models, which are
included in many ESSs
 Critical success factors (CSFs) &
Key Performance Indicators are
identified.
 Executive support systems provide
for ad hoc analysis capabilities, in
which executives can make
specific requests for data analysis
as needed.
 In a status access mode, the
latest data or reports on the status
of key indicators or other factors
can be accessed at any time.
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Characteristics of EISs (cont.)
 Exception reporting is based on
the concept of management by
exception, in which an executive
gives attention to significant
deviations from standards.
 Integration with DSS. Executive
information systems are useful in
identifying problems and
opportunities.
 In order to save the executive’s
time in conducting a drill down,
finding exceptions, or identifying
trends, an intelligent EIS has been
developed.
 With the introduction of the Intranet
& corporate portals, the traditional
EIS has become a part of an
enterprise information system, and
it now often appears under the
name of business intelligence.
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Benefits of DSS for the User
 Users can access DSS from anywhere.
 Many DSSs are now deployed on the corporate Intranet, making them
accessible to all employees.
 The Web supports interactive DSS-related queries and ad hoc report
generation.
 Users can select a list of variables from a pull-down menu when executing
a predefined query or report.
 Web-based application servers can download Java applets that
execute functions on desktop DSS programs.
 This gives users the capabilities of advanced DSS applications without
requiring client software to be loaded.
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Benefits of DSS for the Builder
 A DSS developer (builder) can access Web pages with data related to the
project, the software used, the users etc., thus cutting development time.
 A DSS developer can collaborate with end-users for quicker prototyping
of DSS applications.
 A DSS developer can collaborate with vendors over the Web.
 DSS software and applications are available from ASPs over the
Web. In such a case there is no need to program the DSS, but the
developer must work with the vendor.
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Benefits Web-Based DSSs
 Able to reach rich
resources of data with
simple data entry &
analysis procedure.
 Can easily retrieve data
in sophisticated ways.
 Is easy to use.
 Contributes to better
decision making.
 Enables easier use of
ready-made DSS.
 Cuts development costs.
 Reduces paperwork
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Requirements for Web-Based DSS
 A study by Business Objects Corporation
(businessobjects.com) identified five key requirements for the
successful delivery of Web-based DSS.
 Self-service data access
 High availability & performance
 Zero-administration clients
 Security
 Unified meta data
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Simulation for Decision Makers
 In DSS, simulation refers to a technique for conducting
experiments with a computer on a model of a management
system.
 Characteristics of Simulation;
 While models in general represent reality, simulation usually
imitates it closely.
 It is a technique for conducting experiments.
 It can describe and/or predict the characteristics of a given system
under different circumstances.
 It can be used for complex decision making
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Case: Simulation Saves Siemens Millions
Problem:
 Siemens Solar Industries (SSI), the world’s largest maker of solar
electric products, suffered continuous problems in poor material flow,
unbalanced resource use, bottlenecks in throughput & schedule delays.
Solution:
 SSI built a cleanroom contamination-control technology.
 The simulation provided a virtual laboratory for engineers to
experiment with various configurations before the physical systems
were constructed.
Results:
 SSI improved their manufacturing process significantly.
 The cleanroom facility saved SSI over $75 million/ year.
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Advantages of Simulation
1.
Allows for inclusion of the
real-life complexities of
problems.
2.
Is descriptive, enabling
managers to ask what-if
type questions.
3.
Can handle an extremely
wide variation in problem
types, such as inventory &
staffing, as well as higher
managerial-level tasks like
long-range planning.
4.
Can show the effect of
compressing time, giving the
manager in a matter of minutes
the long-term effects of various
policies.
5.
Can be conducted from
anywhere using Web tools on
the corporate portal or extranet.
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Examples of DSSs
 PriceWaterhouseCoopers (pcwglobal.com) offers online DSSs in
retailing, financial services, etc. Of special interest are the risk
management and self insurance decisions.
 Microsoft’s Office Small Business edition (microsoft.com) contains
“what-if”wizards that can be used to view the financial impacts of
decisions, such as price and inventory decisions.
 IBM (software.ibm.com) offers many tools ranging from market-basket
analysis to financial & manufacturing decision support
 Brio’s (brio.com) “revenue optimization application” helps companies to
identify & capture the full potential of revenue across product lines &
market segments.
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Frontline Decision Making
 Frontline decision making is the process by which
companies automate decision processes and push them
down into the organization & sometimes out to partners.
 Frontline decision making serves business users such as
line managers, sales executives, and call-center
representatives by incorporating decision making into their
daily work.
 Frontline software that started to appear on the market in
late 1999 can solve standard problems
 According to Forrester Research Inc., such systems are essential for the
survival of many companies, but it is expected to take five years for the
technology to mature.
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DSS Failures
 Over the years there have been many cases of failures of all types of
decision support systems. Here are some examples;
 The ill-fated Challeger Shuttle mission was partially attributed to a
flawed GDSS. NASA used a mismanaged GDSS session in which
anonymity was not allowed and other procedures were violated.
 In an international congress on airports, failures in Denver, Hong
Kong, and Malaysia airports have been attributed to failed DSSs.
 Brezillon and Pomerol (1997) describe some failures in intelligent
DSSs.
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Managerial Issues
 Intangible benefits. Management  Security. Decision support
systems may contain extremely
support systems are difficult to justify
important information for the
because they generate mostly
livelihood of organizations.
intangible benefits, such as the ability
to solve problems faster.
 Documenting personal DSS. Many
employees develop their own DSS to
increase their productivity. It is
advisable to have an inventory of these
DSSs so that if the employee leaves
the organization, the productivity tool
remains.
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Managerial Issues (cont.)
 Ready-made commercial DSS. With
the increased use of Web-based
system and ASPs, it is possible to
find more and more DSS
applications sold off the shelf,
frequently online.
 Organizational culture. The more
people recognize the benefits of
DSS and the more support is given
to it by top management, the more
DSS will be used.
 Intelligent DSS. Introducing
intelligent agents into a DSS
application can greatly increase its
functionality.
 Ethical issues. Corporations with
management support systems may
need to address some serious
ethical issues such as privacy &
accountability. Human judgment is
another important issue DSS.
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