Week 9 - Problem Solving Through Information System

8/4/2019 Week 9 - Problem Solving Through Information System

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Problem solving

Through information system(Decision Support Systems)

Chapter

4.1.2 ( week 9)

McGraw-Hill/Irwin Copyright 2009 by The McGraw-Hill Companies, Inc. All rights reserved.


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Identify the changes taking place in the formand use of decision support in business

Identify the role and reporting alternatives

of management information systems Describe how online analytical processing

can meet key information needs of managers

Explain the decision support system concept

and how it differs from traditional managementinformation systems

Learning Objectives

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Learning Objectives

Explain how the following information systemscan support the information needs ofexecutives, managers, and businessprofessionals

Executive information systems

Enterprise information portals

Knowledge management systems

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

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Learning Objectives

Give examples of several waysexpert systems can be used inbusiness decision-making situations

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Decision Support in Business

Companies are investing in data-drivendecision support application frameworksto help them respond to

Changing market conditions

Customer needs

This is accomplished by several types of

Management information

Decision support

Other information systems

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Case 1: Hillman Group, Avnet, andQuaker Chemical

BI refers to a variety of software applications used toanalyze an organizations raw data (e.g., salestransactions) and extract useful insights from them.

BI projects can transform business processes. BI tools,coupled with changes to business processes, can have a

significant impact on the bottom line. Major impediment to using BI that transforms business

processes is that most companies dont understand their

business processes well enough to determine how to

improve them. Companies that use BI to uncover flawed business

processes are in a much better position to successfullycompete than those companies that use BI merely tomonitor whats happening.

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Case Questions

1. What are the business benefits of BI deployments such as

those implemented by Avnet and Quaker Chemical? Whatroles do data and business processes play in achievingthose benefits?

2. What are the main challenges to the change of mindsetrequired to extend BI tools beyond mere reporting? Whatcan companies do to overcome them? Use examples fromthe case to illustrate your answer.

3. Both Avnet and Quaker Chemical implemented systemsand processes that affect the practices of their

salespeople. In which ways did the latter benefit fromthese new implementations? How important was theirbuy-in to the success of these projects? Discussalternative strategies for companies to foster adoption ofnew systems like these.

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Levels of Managerial Decision Making

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Information Quality

Information products made morevaluable by their attributes,characteristics, or qualities

Information that is outdated, inaccurate, orhard to understand has much less value

Information has three dimensions

Time Content

Form

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Attributes of Information Quality

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Decision Structure

Structured (operational)

The procedures to follow when decisionis needed can be specified in advance

Unstructured (strategic) It is not possible to specify in advance

most of the decision procedures to follow

Semi-structured (tactical) Decision procedures can be pre-specified,

but not enough to lead to the correct decision

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Decision Support Systems

Management InformationSystems

Decision SupportSystems

Decisionsupport

provided

Provide information aboutthe performance of the

organization

Provide information andtechniques to analyze

specific problemsInformationform andfrequency

Periodic, exception,demand, and push reports

and responses

Interactive inquiries andresponses

Informationformat

Prespecified, fixed format Ad hoc, flexible, andadaptable format

Informationprocessingmethodology

Information produced byextraction and manipulation

of business data

Information produced byanalytical modeling of

business data

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Decision Support Trends

The emerging class of applicationsfocuses on

Personalized decision support

Modeling

Information retrieval

Data warehousing

What-if scenarios

Reporting

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Business Intelligence Applications

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Decision Support Systems

Decision support systems use thefollowing to support the making of semi-structured business decisions Analytical models

Specialized databases A decision-makers own insights and

judgments

An interactive, computer-based modeling

process DSS systems are designed to be ad hoc,

quick-response systems that are initiatedand controlled by decision makers

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DSS Components

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DSS Model Base

Model Base

A software component that consists ofmodels used in computational and analytical

routines that mathematically expressrelations among variables

Spreadsheet Examples

Linear programming

Multiple regression forecasting

Capital budgeting present value

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Applications of Statistics and Modeling

Supply Chain: simulate and optimize supplychain flows, reduce inventory, reduce stock-outs

Pricing: identify the price that maximizesyield or profit

Product and Service Quality: detect qualityproblems early in order to minimize them

Research and Development: improve quality,efficacy, and safety of products and services

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Management Information Systems

The original type of information systemthat supported managerial decisionmaking

Produces information products that supportmany day-to-day decision-making needs

Produces reports, display, and responses

Satisfies needs of operational and tacticaldecision makers who face structureddecisions

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Management Reporting Alternatives

Periodic Scheduled Reports Prespecified format on a regular basis

Exception Reports Reports about exceptional conditions

May be produced regularly or when anexception occurs

Demand Reports and Responses Information is available on demand

Push Reporting Information is pushed to a networked

computer

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Online Analytical Processing

OLAP

Enables managers and analysts toexamineand manipulate large amounts ofdetailed and consolidated data frommany perspectives

Done interactively, in real time, withrapid response to queries

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Online Analytical Operations

Consolidation Aggregation of data

Example: data about sales offices rolled upto the district level

Drill-Down Display underlying detail data

Example: sales figures by individual product

Slicing and Dicing Viewing database from different viewpoints

Often performed along a time axis

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Geographic Information Systems (GIS)

DSS uses geographic databases toconstruct and display maps andother graphic displays

Supports decisions affecting thegeographic distribution of people andother resources

Often used with Global PositioningSystems (GPS) devices

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Data Visualization Systems (DVS)

Represents complex data usinginteractive, three-dimensionalgraphical forms (charts, graphs,

maps)

Helps users interactively sort,subdivide, combine, and organizedata while it is in its graphical form

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Using Decision Support Systems

Using a decision support systeminvolves an interactive analyticalmodeling process

Decision makers are not demandingpre-specified information

They are exploring possible alternatives

What-If Analysis

Observing how changes to selectedvariables affect other variables

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Using Decision Support Systems

Sensitivity Analysis

Observing how repeated changes to a singlevariable affect other variables

Goal-seeking Analysis Making repeated changes to selected

variables until a chosen variable reaches atarget value

Optimization Analysis Finding an optimum value for selected

variables, given certain constraints

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Data Mining

Provides decision support throughknowledge discovery Analyzes vast stores of historical business

data

Looks for patterns, trends, and correlations Goal is to improve business performance

Types of analysis Regression

Decision tree Neural network Cluster detection Market basket analysis

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Analysis of Customer Demographics

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Market Basket Analysis

One of the most common uses for datamining

Determines what products customerspurchase together with other products

Results affect how companies

Market products

Place merchandise in the store

Lay out catalogs and order forms Determine what new products to offer

Customize solicitation phone calls

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Executive Information Systems (EIS)

Combines many features of MIS and DSS

Provide top executives with immediate andeasy access to information

Identify factors that are critical toaccomplishing strategic objectives (criticalsuccess factors)

So popular that it has been expanded to

managers, analysis, and other knowledgeworkers

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Features of an EIS

Information presented in formstailored to the preferences of theexecutives using the system

Customizable graphical userinterfaces

Exception reports

Trend analysis

Drill down capability

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Enterprise Information Portals

An EIP is a Web-based interface andintegration of MIS, DSS, EIS, and othertechnologies

Available to all intranet users and selectextranet users

Provides access to a variety of internal andexternal business applications and services

Typically tailored or personalized to the useror groups of users

Often has a digital dashboard

Also called enterprise knowledge portals

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Enterprise Information Portal Components

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Enterprise Knowledge Portal

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Case 2: Goodyear, JEA, OSUMC, andMonsanto

Advanced technologies such as AI, mathematicalsimulations, and robotics can have dramatic impacts on bothbusiness processes and financial results.

At Goodyear, designers can perform tests 10 times fasterusing simulation, reducing a new tires time to market from

two years to as little as nine months.

Public Utility Company JEA uses neural network technologyto automatically determine the optimal combinations of oiland natural gas the utilitys boilers need to produce electricity

cost effectively, given fuel prices and the amount ofelectricity required.

The Ohio State University Medical Center (OSUMC)replaced its overhead rail transport system with 46 self-guided robotic vehicles to move linens, meals, trash, andmedical supplies throughout the 1,000-bed hospital.

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Case Study Questions1. Consider the outcomes of the projects discussed in the case. In

all of them, the payoffs are both larger and achieved more rapidlythan in more traditional system implementations. Why do youthink this is the case? How are these projects different fromothers you have come across in the past? What are thosedifferences? Provide several examples.

2. How do these technologies create business value for theimplementing organizations? In which ways are theseimplementations similar in how they accomplish this, and how arethey different? Use examples from the case to support youranswer.

3. In all of these examples, companies had an urgent need thatprompted them to investigate these radical, new technologies. Doyou think the story would have been different had the companiesbeen performing well already? Why or why not? To what extentare these innovations dependent on the presence of a problem orcrisis?

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Artificial Intelligence (AI)

AI is a field of science and technologybased on Computer science Biology

Psychology Linguistics Mathematics Engineering

The goal is to develop computers thancan simulate the ability to think And see, hear, walk, talk, and feel as well

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Attributes of Intelligent Behavior

Some of the attributes of intelligentbehavior

Think and reason

Use reason to solve problems

Learn or understand from experience

Acquire and apply knowledge

Exhibit creativity and imagination

Deal with complex or perplexing situations

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Attributes of Intelligent Behavior

Attributes of intelligent behavior(continued)

Respond quickly and successfully tonew situations

Recognize the relative importance ofelements in a situation

Handle ambiguous, incomplete, orerroneous information

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Domains of Artificial Intelligence

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Cognitive Science

Applications in the cognitive science ofAI Expert systems

Knowledge-based systems

Adaptive learning systems Fuzzy logic systems

Neural networks

Genetic algorithm software

Intelligent agents

Focuses on how the human brain worksand how humans think and learn

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Robotics

AI, engineering, and physiology are the basicdisciplines of robotics Produces robot machines with computer intelligence

and humanlike physical capabilities

This area include applications designed togive robots the powers of Sight or visual perception

Touch

Dexterity

Locomotion Navigation

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Natural Interfaces

Major thrusts in the area of AI and thedevelopment of natural interfaces Natural languages

Speech recognition

Virtual reality

Involves research and development in Linguistics

Psychology Computer science

Other disciplines

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Latest Commercial Applications of AI

Decision Support

Helps capture the whyas well as thewhatof engineered design and

decision making

Information Retrieval

Distills tidal waves of information intosimple presentations

Natural language technology

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Latest Commercial Applications of AI

Virtual Reality

X-ray-like vision enabled by enhanced-realityvisualization helps surgeons

Automated animation and haptic interfacesallow users to interact with virtual objects

Robotics

Machine-vision inspections systems

Cutting-edge robotics systems

From micro robots and hands and legs, tocognitive and trainable modular vision systems

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Expert Systems

An Expert System (ES)

A knowledge-based informationsystem

Contain knowledge about a specific,complex application area

Acts as an expert consultant to endusers

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Components of an Expert System

Knowledge Base Facts about a specific subject area Heuristics that express the reasoning

procedures of an expert (rules of thumb)

Software Resources An inference engine processes the

knowledgeand recommends a course of action

User interface programs communicate withthe end user

Explanation programs explain thereasoning process to the end user

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Components of an Expert System

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Methods of Knowledge Representation

Case-Based

Knowledge organized in the form of cases

Cases are examples of past performance,

occurrences, and experiences

Frame-Based

Knowledge organized in a hierarchy ornetwork of frames

A frame is a collection of knowledge aboutan entity, consisting of a complex packageof data values describing its attributes

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Methods of Knowledge Representation

Object-Based Knowledge represented as a network of

objects

An object is a data element that includes

both data and the methods or processes thatact on those data

Rule-Based

Knowledge represented in the form of rules

and statements of fact Rules are statements that typically take the

form of a premise and a conclusion (If, Then)

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Expert System Application Categories

Decision Management

Loan portfolio analysis

Employee performance evaluation

Insurance underwriting

Diagnostic/Troubleshooting

Equipment calibration

Help desk operations

Medical diagnosis

Software debugging

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Design/Configuration Computer option installation

Manufacturability studies

Communications networks

Selection/Classification Material selection

Delinquent account identification

Information classification

Suspect identification

Process Monitoring/Control

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Process Monitoring/Control

Machine control (including robotics)

Inventory control

Production monitoring

Chemical testing

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Benefits of Expert Systems

Captures the expertise of an expert orgroup of experts in a computer-basedinformation system

Faster and more consistent than an expert

Can contain knowledge of multiple experts

Does not get tired or distracted

Cannot be overworked or stressed

Helps preserve and reproduce theknowledgeof human experts

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Limitations of Expert Systems

The major limitations of expertsystems

Limited focus

Inability to learn

Maintenance problems

Development cost Can only solve specific types of

problemsin a limited domain of knowledge

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Developing Expert Systems

Suitability Criteria for Expert Systems

Domain: the domain or subject area ofthe problem is small and well-defined

Expertise: a body of knowledge, techniques,and intuition is needed that only a fewpeople possess

Complexity: solving the problem is a

complex task that requires logical inferenceprocessing

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Developing Expert Systems

Suitability Criteria for Expert Systems

Structure: the solution process must be ableto cope with ill-structured, uncertain, missing,

and conflicting data and a changing problemsituation

Availability: an expert exists who isarticulate, cooperative, and supported by the

management and end users involved in thedevelopment process

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Development Tool

Expert System Shell

The easiest way to develop an expertsystem

A software package consisting of anexpert system without its knowledgebase

Has an inference engine and userinterface programs

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Knowledge Engineering

A knowledge engineer

Works with experts to capture the knowledge(facts and rules of thumb) they possess

Builds the knowledge base, and if necessary,the rest of the expert system

Performs a role similar to that of systemsanalysts in conventional information systems

development

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Neural Networks

Computing systems modeled afterthe brains mesh-like network ofinterconnected processing elements

(neurons)

Interconnected processors operate inparallel

and interact with each other Allows the network to learn from the

data it processes

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Fuzzy Logic

Fuzzy logic

Resembles human reasoning

Allows for approximate values andinferences and incomplete or ambiguousdata

Uses terms such as very high instead ofprecise measures

Used more often in Japan than in the U.S.

Used in fuzzy process controllers used insubway trains, elevators, and cars

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Example of Fuzzy Logic Rules and Query

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Genetic Algorithms

Genetic algorithm software

Uses Darwinian, randomizing, and othermathematical functions

Simulates an evolutionary process, yieldingincreasingly better solutions to a problem

Being uses to model a variety of scientific,technical, and business processes

Especially useful for situations in whichthousands of solutions are possible

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Virtual Reality (VR)

Virtual reality is a computer-simulatedreality

Fast-growing area of artificial intelligence

Originated from efforts to build natural,realistic, multi-sensory human-computerinterfaces

Relies on multi-sensory input/output devices

Creates a three-dimensional world throughsight, sound, and touch

Also called telepresence

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Typical VR Applications

Current applications of virtual reality

Computer-aided design

Medical diagnostics and treatment

Scientific experimentation

Flight simulation

Product demonstrations

Employee training

Entertainment

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Intelligent Agents

A software surrogate for an end user or aprocess that fulfills a stated need oractivity

Uses built-in and learned knowledge baseto make decisions and accomplish tasks ina way that fulfills the intentions of a user

Also call software robots or bots

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User Interface Agents

Interface Tutors observe user computeroperations, correct user mistakes, providehints/advice on efficient software use

Presentation Agents show information ina variety of forms/media based on userpreferences

Network Navigation Agents discoverpathsto information, provide ways to view it basedon user preferences

Role-Playing play what-if games and otherroles to help users understand informationand make better decisions

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Information Management Agents

Search Agents help users find files anddatabases, search for information, andsuggest and find new types of informationproducts, media, resources

Information Brokers provide commercialservices to discover and develop informationresources that fit business or personal needs

Information Filters Receive, find, filter,discard, save, forward, and notify usersabout products received or desired, includinge-mail, voice mail, and other informationmedia

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Case 3: Oracle Corporation and Others:Dashboards for Executives

Web-based dashboards Displays critical information in graphic form

Assembled from data pulled in real time fromcorporate software and databases

Managers see changes almostinstantaneously

Now available to smaller companies

Potential problems

Pressure on employees Divisions in the office

Tendency to hoard information

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Case Study Questions

1. What is the attraction of dashboardsto CEOs and other executives?What real business value do theyprovide to executives?

2. The case emphasizes that managersof small businesses and manybusiness professionals now rely ondashboards. What business benefits

do dashboards provide to thisbusiness audience?

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Case 4: Harrahs Entertainment


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Case 4: Harrah s Entertainment,LendingTree, DeepGreen Financial, andCisco Systems:

The promise of AI of automatingdecision making has been very slow tomaterialize.

The new generation AI applications areeasier to create and manage, do notrequire anyone to identify the problemsor to initiate the analysis, decision-

making capabilities are embedded intothe normal flow of work, and aretriggered without human intervention.

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Case 4: Harrahs Entertainment


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Case 4: Harrah s Entertainment,LendingTree, DeepGreen Financial, andCisco Systems:

They sense online data or conditions,apply codified knowledge or logic andmake decisions with minimal human

intervention. But they rely on experts and managers

to create and maintain rules andmonitor the results.

Also, managers in charge of automateddecision systems must developprocesses for managing exceptions.

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1. Why did some previous attempts to useartificial intelligence technologies fail?What key differences of the new AI-based applications versus the old causethe authors to declare that automateddecision making is finally coming of age?

2. What types of decisions are best suited

for automated decision making? Provideseveral examples of successfulapplications from the companies in thiscase to illustrate your answer.

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3. What role do humans play inautomated decision makingapplications? What are some of

the challenges faced by managerswhere automated decision-makingsystems are being used? What

solutions are needed to meet suchchallenges?

Documents

Week 9 - Problem Solving Through Information System