Decision Support Systems

Decision SupportMIS and DSS

Artificial IntelligenceExpert Systems

Chapter

9

McGraw-Hill/Irwin Copyright © 2007 by The McGraw-Hill Companies, Inc. All rights reserved.

9-2

Levels of Management Decision Making

Strategic managementExecutives develop organizational goals,

strategies, policies, and objectives Tactical management

Develop short- and medium-range plans, schedules and budgets for their subunits

Operational managementDevelop short-range plans such as

weekly production schedules

9-3

Decision Structure

Unstructured – decision situations where it is not possible to specify in advance

Semistructured - decision procedures that can be prespecified, but not enough to lead to a definite recommended decision

Structured – situations where the procedures to follow when a decision is needed can be specified in advance

Page 318 Fig 9.4

9-4

Information Quality

Information has 3 dimensions:Time: currency, frequencyContent: accuracy, completenessForm: clarity, order

9-5

Business Intelligence Applications

9-6

Decision Support Systems

Provide interactive information support to business professionals during the decision-making process

To support semistructured business decisions

9-7

Using DSS

4 Analytical modelsWhat-if Analysis Sensitivity AnalysisGoal-SeekingOptimization

9-8

Management Information Systems

MISProduces information products that support

many of the day-to-day decision-making needs of managers and business professionals

Prespecified reports, displays and responsesSupport more structured decisions

9-9

MIS Reporting Alternatives

Periodic Scheduled ReportsPrespecified format on a regular basis

Exception ReportsReports about exceptional conditionsMay be produced regularly or when exception

occursDemand Reports and Responses

Information available when demandedPush Reporting

Information pushed to manager

9-10

Online Analytical Processing

OLAP Analytical Operations in real timeConsolidation

Aggregation of dataDrill-down

Display detail data that comprise consolidated data

Slicing and DicingAbility to look at the database from different

viewpoints

9-11

Data Mining

Main purpose is to provide decision support to business professionals through knowledge discovery

Market Basket AnalysisThe purpose is to determine what products

customers purchase together with other products

9-12

Executive Information Systems

Combine many features of MIS, DSS & OLAPCustomizable graphical user interfacesException reportingTrend analysisDrill down capability

9-13

Case 2 Artificial IntelligenceThe Dawn of the Digital Brain

Numenta will translate the way the brain works into an algorithm that can run on a new type of computer

The human brain does not work like a computer

Intelligence, according to Hawkins, is pattern recognition

9-14

Case Study Questions

1. What is the business value of AI technologies in business today? What value might exist if Jeff Hawkins can build a machine to think like humans?

2. Why has artificial intelligence become so important to business?

3. Why do you think banks and other financial institutions are leading users of AI technologies? What are the benefits and limitations of this technology?

9-15

Section II: Artificial Intelligence (AI)

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

Goal is to develop computers that can simulate the ability to think, as well as see, hear, walk, talk, and feel

9-16

Attributes of Intelligent Behavior

Think and reasonUse reason to solve problemsLearn or understand from experienceAcquire and apply knowledgeExhibit creativity and imaginationDeal with complex or perplexing situationsRespond quickly and successfully to new

situationsRecognize the relative importance of elements

in a situationHandle ambiguous, incomplete, or erroneous

information

9-17

Domains of Artificial Intelligence

9-18

Cognitive Science

Based in biology, neurology, psychology, etc.Focuses on researching how the human brain

works and how humans think and learn

9-19

Robotics

Based in AI, engineering and physiologyRobot machines with computer intelligence

and computer controlled, humanlike physical capabilities

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Natural Interfaces

Based in linguistics, psychology, computer science, etc.

Includes natural language and speech recognitionDevelopment of multisensory devices that use a

variety of body movements to operate computersVirtual reality

Using multisensory human-computer interfaces that enable human users to experience computer-simulated objects, spaces and “worlds” as if they actually exist

9-21

Expert Systems

ESA knowledge-based information system (KBIS)

that uses its knowledge about a specific, complex application to act as an expert consultant to end users

KBIS is a system that adds a knowledge base to the other components on an IS

9-22

Expert System Components

Knowledge BaseFacts about specific subject areaHeuristics that express the reasoning procedures

of an expert (rules of thumb)Software Resources

Inference engine processes the knowledge and makes inferences to make recommend course of action

User interface programs to communicate with end user

Explanation programs to explain the reasoning process to end user

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Methods of Knowledge Representation

Case-Based – knowledge organized in form of casesCases: examples of past performance,

occurrences and experiencesFrame-Based – knowledge organized in a

hierarchy or network of framesFrames: entities consisting of a complex

package of data values

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Methods of Knowledge Representation

Object-Based – knowledge organized in network of objectsObjects: data elements and the methods or

processes that act on those dataRule-Based – knowledge represented in rules

and statements of factRules: statements that typically take the form of

a premise and a conclusionSuch as, If (condition) then (conclusion)

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Expert System Benefits

Faster and more consistent than an expertCan have the knowledge of several expertsDoes not get tired or distracted by overwork or

stressHelps preserve and reproduce the knowledge

of experts

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Expert System Limitations

Limited focusInability to learnMaintenance problemsDevelopmental costsCan only solve specific types of problems in a

limited domain of knowledge

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Suitability Criteria for Expert Systems

Domain: subject area relatively small and limited to well-defined area

Expertise: solutions require the efforts of an expert

Complexity: solution of the problem is a complex task that requires logical inference processing (not possible in conventional information processing)

Structure: solution process must be able to cope with ill-structured, uncertain, missing and conflicting data

Availability: an expert exists who is articulate and cooperative