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Chapter 8 Decision Support Systems

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Chapter

8

Decision Support Systems

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Learning Objectives

Identify the changes taking place in the form and use of decision support in e-business enterprises.

Identify the role and reporting alternatives of management information systems.

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Learning Objectives (continued)

Describe how online analytical processing can meet key information needs of managers.

Explain the decision support system concept and how it differs from traditional management information systems.

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Learning Objectives (continued)

Explain how the following information systems can support the information needs of executives, managers, and business professionals:Executive information systemsEnterprise information portalsEnterprise knowledge portals

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Learning Objectives (continued)

Identify how neural networks, fuzzy logic, genetic algorithms, virtual reality, and intelligent agents can be used in business.

How can expert systems be used in business decision-making situations?

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Section I

Decision Support in Business

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Business and Decision Support

To succeed, companies need information systems that can support the diverse information and decision-making needs of their managers and business professionals.

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Business and Decision Support (continued)

Information, Decisions, & Management

The type of information required by decision makers is directly related to the level of management and the amount of structure in the decision situations.

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Business and Decision Support (continued)

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Business and Decision Support (continued)

Information QualityTimeliness

Provided WHEN it is neededUp-to-date when it is providedProvided as often as neededProvided about past, present, and future

time periods as necessary

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Business and Decision Support (continued)

Information Quality (continued)Content

Free from errorsShould be related to the information needs of a

specific recipient for a specific situationProvide all the information that is neededOnly the information that is needed should be

providedCan have a broad or narrow scope, or an internal

or external focusCan reveal performance

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Business and Decision Support (continued)

Information Quality (continued)Form

Provided in a form that is easy to understandCan be provided in detail or summary formCan be arranged in a predetermined sequenceCan be presented in narrative, numeric, graphic,

or other formsCan be provided in hard copy, video, or other

media.

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Business and Decision Support (continued)

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Business and Decision Support (continued)

Decision StructureStructured decisions

Involve situations where the procedures to be followed can be specified in advance

Unstructured decisionsInvolve situations where it is not possible

to specify most of the decision procedures in advance

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Business and Decision Support (continued)

Decision structure (continued)

Semistructured decisions Some decision procedures can be specified

in advance, but not enough to lead to a definite recommended decision

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Business and Decision Support (continued)

Amount of structure is typically tied to management levelOperational – more structuredTactical – more semistructuredStrategic – more unstructured

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Decision Support Trends

The growth of corporate intranets, extranets and the Web has accelerated the development and use of “executive class” information delivery & decision support software tools to virtually every level of the organization.

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Management Information Systems

The original type of information systemProduces many of the products that support

day-to-day decision-makingThese information products typically take the

following forms:Periodic scheduled reportsException reportsDemand reports and responsesPush reports

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Management Information Systems (continued)

Management reporting alternativesPeriodic scheduled reports

Prespecified formatProvided on a scheduled basis

Exception reportsProduced only when exceptional

conditions occurReduces information overload

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Management Information Systems (continued)

Management reporting alternatives (continued)Demand reports and responses

Available when demanded.Ad hoc

Push reportsInformation is sent to a networked PC

over the corporate intranet.Not specifically requested by the recipient

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Online Analytical Processing

Enables managers and analysts to interactively examine & manipulate large amounts of detailed and consolidated data from many perspectivesAnalyze complex relationships to discover

patterns, trends, and exception conditionsReal-time

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Online Analytical Processing (continued)

Involves..Consolidation

The aggregation of data.From simple roll-ups to complex

groupings of interrelated dataDrill-Down

Display detail data that comprise consolidated data

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Online Analytical Processing (continued)

Slicing and DicingThe ability to look at the database from

different viewpoints.When performed along a time axis, helps

analyze trends and find patterns

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Decision Support Systems

Computer-based information systems that provide interactive information support during the decision-making process

DSS’s useAnalytical modelsSpecialized databasesThe decision maker’s insights & judgmentsAn interactive, computer-based modeling

process to support making semistructured and unstructured business decisions

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Decision Support Systems (continued)

Designed to be ad hoc, quick-response systems that are initiated and controlled by the decision maker

DSS Models and SoftwareRely on model bases as well as databasesMight include models and analytical

techniques used to express complex relationships

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Decision Support Systems (continued)

DSS models and software (continued)Can combine model components to create

integrated models in support of specific types of business decisions

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Decision Support Systems (continued)

Geographic Information & Data Visualization SystemsSpecial categories of DSS that integrate

computer graphics with other DSS featuresGIS

A DSS that uses geographic databases to construct and display maps and other graphics displays

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Decision Support Systems (continued)

Geographic information and data visualization systems (continued)

Data visualization systemsRepresent complex data using interactive

three-dimensional graphic formsHelps discover patterns, links, and

anomalies

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Using Decision Support Systems

An interactive modeling processFour types of analytical modeling

What-if analysisSensitivity analysisGoal-seeking analysisOptimization analysis

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Using Decision Support Systems (continued)

What-If AnalysisEnd user makes changes to variables, or

relationships among variables, and observes the resulting changes in the values of other variables

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Using Decision Support Systems (continued)

Sensitivity AnalysisA special case of what-if analysisThe value of only one variable is changed

repeatedly, and the resulting changes on other variables are observed

Typically used when there is uncertainty about the assumptions made in estimating the value of certain key variables

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Using Decision Support Systems (continued)

Goal-Seeking AnalysisInstead of observing how changes in a

variable affect other variables, goal-seeking sets a target value (a goal) for a variable, then repeatedly changes other variables until the target value is achieved

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Using Decision Support Systems (continued)

Optimization AnalysisA more complex extension of goal-seekingThe goal is to find the optimum value for

one or more target variables, given certain constraints

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Using Decision Support Systems (continued)

Data Mining for Decision SupportSoftware analyzes vast amounts of dataAttempts to discover patterns, trends, &

correlationsMay perform regression, decision tree,

neural network, cluster detection, or market basket analysis

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Executive Information Systems

EIS’s combine many of the features of MIS and DSS

Originally intended to provide top executives with immediate, easy access to information about the firm’s “critical success factors”

Alternative namesEnterprise information systemsExecutive support systems

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Executive Information Systems (continued)

Features of an EISInformation presented in forms tailored to

the preferences of the usersMost stress use of graphical user interface

and graphics displaysMay also include exception reporting and

trend analysis

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Enterprise Portals and Decision Support

A Web-based interface and integration of intranet and other technologies that gives all intranet users and selected extranet users access to a variety of internal & external business applications and services

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Enterprise Portals and Decision Support (continued)

Business benefitsMore specific and selective informationEasy access to key corporate intranet

website resourcesIndustry and business newsAccess to company data for stakeholdersLess time spent on unproductive surfing

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Knowledge Management Systems

IT that helps gather, organize, and share business knowledge within an organization

Hypermedia databases that store and disseminate business knowledge. May also be called knowledge bases

Best practices, policies, business solutionsEntered through the enterprise knowledge

portal

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Section II

Artificial Intelligence Technologies in Business

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Business and AI

“Designed to leverage the capabilities of humans rather than replace them,…AI technology enables an extraordinary array of applications that forge new connections among people, computers, knowledge, and the physical world.”

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Artificial Intelligence

A field of science and technology based on disciplines such as computer science, biology, psychology, linguistics, mathematics, & engineering

Goal is to develop computers that can think, see, hear, walk, talk, and feel

Major thrust – development of computer functions normally associated with human intelligence – reasoning, learning, problem solving

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Artificial Intelligence (continued)

Domains of AIThree major areas

Cognitive scienceRoboticsNatural interfaces

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Artificial Intelligence (continued)

Cognitive scienceFocuses on researching how the human

brain works & how humans think and learnApplications

Expert systemsAdaptive learning systemsFuzzy logic systemsNeural networksIntelligent agents

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Artificial Intelligence (continued)

RoboticsProduces robot machines with computer

intelligence and computer controlled, humanlike physical capabilities

Natural interfacesNatural language and speech recognitionTalking to a computer and having it

understandVirtual reality

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Neural Networks

Computing systems modeled after the brain’s meshlike network of interconnected processing elements, called neurons

Goal – the neural network learns from data it processes

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Fuzzy Logic Systems

A method of reasoning that resembles human reasoning

Allows for approximate values and inferencesAllows for incomplete or ambiguous dataAllows “fuzzy” systems to process incomplete

data and provide approximate, but acceptable, solutions to problems

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Genetic Algorithms

Uses Darwinian, randomizing, & other mathematical functions to simulate an evolutionary process that can yield increasingly better solutions

Especially useful for situations in which thousands of solutions are possible & must be evaluated

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Virtual Reality

Computer-simulated realityRelies on multisensory input/output devicesAllows interaction with computer-simulated

objects, entities, and environments in three dimensions

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Intelligent Agents

A “software surrogate” for an end user or a process that fulfills a stated need or activity

Uses built-in and learned knowledge base about a person or process to make decisions and accomplish tasks

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Expert Systems

A knowledge-based information system that uses its knowledge about a specific, complex application area to act as an expert consultant

Provides answers to questions in a very specific problem area

Must be able to explain reasoning process and conclusions to the user

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Expert Systems (continued)

ComponentsKnowledge baseSoftware resources

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Expert Systems (continued)

Knowledge baseContains

Facts about a specific subject areaHeuristics that express the reasoning

procedures of an expert on the subject

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Expert Systems (continued)

Software ResourcesContains an inference engine and other

programs for refining knowledge and communicatingInference engine processes the

knowledge, and makes associations and inferences

User interface programs, including an explanation program, allows communication with user

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Developing Expert Systems

Begin with an expert system shellAdd the knowledge base

Built by a “knowledge engineer”Works with experts to capture their

knowledgeWorks with domain experts to build the

expert system

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The Value of Expert Systems

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The Value of Expert Systems (continued)

BenefitsCan outperform a single human expert in

many problem situationsHelps preserve and reproduce knowledge of

experts

LimitationsLimited focus, inability to learn,

maintenance problems, developmental costs

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Discussion Questions

Is the form and use of information and decision support in e-business changing and expanding?

Has the growth of self-directed teams to manage work in organizations changed the need for strategic, tactical, and operational decision making in business?

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Discussion Questions (continued)

What is the difference between the ability of a manager to retrieve information instantly on demand using an MIS and the capabilities provided by a DSS?

In what ways does using an electronic spreadsheet package provide you with the capabilities of a decision support system?

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Discussion Questions (continued)

Are enterprise information portals making executive information systems unnecessary?

Can computers think? Will they EVER be able to?

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Discussion Questions (continued)

What are some of the most important applications of AI in business?

What are some of the limitations or dangers you see in the use of AI technologies such as expert systems, virtual reality, and intelligent agents? What could be done to minimize such effects?

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Real World Case 1 – AmeriKing & Others

AmeriKing’s old systemRelied on an antiquated corporate information

system.Involved mailing or faxing paper reports to

managers.AmeriKing’s new system

An intranet-based enterprise information portalEnables employees to use Web browsers to

instantly access financial, marketing, human resource, and other reports.

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Real World Case 1 (continued)

What is the business value to a company of an enterprise portal like AmeriKing’s?

What are several ways AmeriKing could improve the business value of its portal?

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Real World Case 1 (continued)

How might an enterprise portal help you as a business professional or manager in your work activities?

Is it becoming necessary for all companies to provide an enterprise information portal to their employees?

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Real World Case 2 – BAE Systems

ProblemsWasted time trying to find information to do

the job.Duplication of effortInformation overloadInadequate search capability

SolutionAn intranet-based knowledge management

system

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Real World Case 2 (continued)

What problems was BAE having in knowledge sharing? Are such problems common to many companies?

How does BAE’s knowledge management system help solve such problems?

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Real World Case 2 (continued)

What are some of the business benefits and potential limitations of BAE’s knowledge management system?

What is the difference between a corporate intranet and a knowledge management system? What is the difference in their business value?

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Real World Case 3 – Cisco Systems, NetFlix, & Office Depot

What are the business benefits and limitations of Cisco’s Web-based system for its channel managers?

Do you agree that NetFlix’s real-time personalization system is critical to their success?

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Real World Case 3 (continued)

Do you think salespeople will appreciate and benefit from the real-time alert system envisioned for Office Depot?

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Real World Case 4 – Producers Assistance, Kinko’s, & Champion Printing

Using Spatial Information Systems to…Find workersFind servicesFind customers

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Real World Case 4 (continued)

What is the business value of spatial information systems?

How else could spatial information systems be used in business?

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Real World Case 4 (continued)

How helpful is Kinko’s location finder service? What else can they do to improve this spatial information management application?

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Real World Case 5 – Schneider National

The business value of business intelligence (BI)

“We were drowning in data but starving for information.”

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Real World Case 5 (continued)

What problem was Schneider National having with their business data?

How did business intelligence solve the problem?

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Real World Case 5 (continued)

What are the benefits and limitations of business intelligence software as demonstrated by Schneider National?

What is the business value of business intelligence as defined by Cognos?