Top Banner
Information and Decision Support Systems
74
Welcome message from author
This document is posted to help you gain knowledge. Please leave a comment to let me know what you think about it! Share it to your friends and learn new things together.
Transcript
Page 1: DSS

Information and Decision Support Systems

Page 2: DSS

Principles and Learning Objectives

• Good decision-making and problem-solving skills are the key to developing effective information and decision support systems.

– Define the stages of decision making.– Discuss the importance of implementation and

monitoring in problem solving.

Page 3: DSS

Principles and Learning Objectives

• The management information system (MIS) must provide the right information to the right person in the right fashion at the right time.

– Define the term MIS and clearly distinguish the difference between a TPS and an MIS.

– Discuss information systems in the functional areas of business organizations.

Page 4: DSS

Principles and Learning Objectives

• Decision support systems (DSSs) are used when the problems are more unstructured.

– List and discuss important characteristics of DSSs that give them the potential to be effective management support tools.

– Identify and describe the basic components of a DSS.

Page 5: DSS

Principles and Learning Objectives

• Specialized support systems, such as group decision support systems (GDSSs) and executive support systems (ESSs), use the overall approach of a DSS in situations such as group and executive decision making.

– State the goals of a GDSS and identify the characteristics that distinguish it from a DSS.

– Identify the fundamental uses of an ESS and list the characteristics of such a system.

Page 6: DSS

Decision Making and Problem Solving

Page 7: DSS

Decision Making as a Component of Problem Solving

Page 8: DSS

Programmed versus Nonprogrammed Decisions

• Programmed decisions– Structured situations with well defined relationships– Quantifiable– Management information system– Easy to computerize

• Nonprogrammed decisions– Rules and relationships not defined– Problem is not routine– Not easily quantifiable

Page 9: DSS

Problem Solving Approaches

• Optimization: find the best solution• Satisficing: find a good solution• Heuristics: rules of thumb

Page 10: DSS

An Overview of Management Information Systems

Page 11: DSS

Developing Effective Reports

Page 12: DSS

Characteristics of an MIS

• Fixed format, standard reports• Hard-copy or soft-copy reports• Uses internal data• User-developed reports• Users must request formal reports from IS

department

Page 13: DSS

Functional Aspects of the MIS

Page 14: DSS

Functional Aspects of an MIS

Page 15: DSS

Financial MIS

Page 16: DSS

Manufacturing MIS

• Design engineering

• Process control– Computer-assisted manufacturing (CAM)– Computer-integrated manufacturing (CIM)– Flexible manufacturing system

• Quality control and testing

Page 17: DSS

Overview of a Manufacturing MIS

Page 18: DSS

Marketing MIS

Page 19: DSS

Human Resource MIS

Page 20: DSS

An Overview of Decision Support Systems

Page 21: DSS

Characteristics of Decision Support Systems

• Handle large amounts of data from various sources

• Provide report and presentation flexibility• Offer both textual and graphical orientation• Support drill down analysis

Page 22: DSS

Characteristics of a DSS

• Perform complex, sophisticated analysis

• Optimization, satisficing, heuristics– Simulation– What-if analysis– Goal-seeking analysis

Page 23: DSS

Capabilities of a DSS

• Support all problem-solving phases• Support different decision frequencies• Support different problem structures

• Support various decision-making levels

Page 24: DSS

Support for Various Decision-Making Levels

Page 25: DSS

Comparison of DSSs and MISs

Page 26: DSS

Comparison of DSSs and MISs

Page 27: DSS

Components of a DSS

Page 28: DSS

Components of a DSS

Page 29: DSS

Data-driven versus Model-driven DSS

• Data-driven DSS - primarily performs qualitative analysis based on the company’s databases

• Model-driven DSS - primarily performs mathematical or quantitative analysis

Page 30: DSS

Group Decision Support Systems

Page 31: DSS

Group Decision Support System

Page 32: DSS

Characteristics of a GDSS

• Special design• Ease of use• Flexibility• Decision-making support• Anonymous input• Reduction of negative group behavior• Parallel communication• Automated record keeping

Page 33: DSS

GDSS Alternatives

Page 34: DSS

The Decision Room

Page 35: DSS

Executive Support Systems

Page 36: DSS

Executive Support Systems

Page 37: DSS

Executive Support Systems (ESS) in Perspective

• Tailored to individual executives• Easy to use• Drill down capabilities• Support need for external data• Can help when uncertainty is high• Future-oriented• Linked to value-added processes

Page 38: DSS

Capabilities of an ESS

• Support for defining an overall vision• Support for strategic planning• Support for strategic organizing & staffing• Support for strategic control• Support for crisis management

Page 39: DSS

Summary

• Management information system - an integrated collection of people, procedures, databases, and devices that provide managers and decision-makers with information to help achieve organizational goals

• Decision-making phase: includes intelligence, design, and choice

• Problem solving: also includes implementation and monitoring

• Decision approaches: optimization, satisficing, and heuristic

Page 40: DSS

Summary

• Decision support system (DSS) - an organized collection of people, procedures, software, databases, and devices working to support managerial decision making

• Group decision support system (GDSS) - also called a computerized collaborative work system, consists of most of the elements in a DSS, plus software needed to provide effective support in group decision-making settings

• Executive support systems (ESSs) - specialized decision support systems designed to meet the needs of senior management

Page 41: DSS

Specialized Business Information Systems

Page 42: DSS

Principles and Learning Objectives

• Artificial intelligence systems form a broad and diverse set of systems that can replicate human decision making for certain types of well-defined problems.

– Define the term artificial intelligence and state the objective of developing artificial intelligence systems.

– List the characteristics of intelligent behavior and compare the performance of natural and artificial intelligence systems for each of these characteristics.

– Identify the major components of the artificial intelligence field and provide one example of each type of system.

Page 43: DSS

Principles and Learning Objectives

• Expert systems can enable a novice to perform at the level of an expert but must be developed and maintained very carefully.

– List the characteristics and basic components of expert systems.– Identify at least three factors to consider in evaluating the

development of an expert system.– Outline and briefly explain the steps for developing an expert

system.

– Identify the benefits associated with the use of expert systems.

Page 44: DSS

Principles and Learning Objectives

• Virtual reality systems have the potential to reshape the interface between people and information technology by offering new ways to communicate information creatively.

– Define the term virtual reality and provide three examples of

virtual reality applications.

• Special-purpose systems can help organizations and individuals achieve their goals.

– Discuss examples of special-purpose systems for organizational and individual use.

Page 45: DSS

An Overview of Artificial Intelligence

Page 46: DSS

The Nature of Intelligence

• Learn from experience & apply the knowledge• Handle complex situations• Solve problems when important information is

missing• Determine what is important

Page 47: DSS

The Nature of Intelligence

• React quickly & correctly to new situations • Understand visual images• Process & manipulate symbols• Be creative & imaginative• Use heuristics

Page 48: DSS

The Difference Between Natural and Artificial Intelligence

Page 49: DSS

The Major Branches of ArtificialIntelligence

Page 50: DSS

An Overview of Expert Systems

Page 51: DSS

Characteristics of an Expert System

• Can explain their reasoning or suggested decisions• Can display “intelligent” behavior • Can draw conclusions from complex relationships• Can provide portable knowledge• Can deal with uncertainty• Not widely used or tested

Page 52: DSS

Characteristics of an Expert System

• Limited to relatively narrow problems• Cannot readily deal with “mixed” knowledge• Possibility of error• Cannot refine its own knowledge• May have high development costs• Raise legal and ethical concerns

Page 53: DSS

Capabilities of an Expert Systems

• Strategic goal setting• Planning• Design• Decision-making• Quality control and monitoring• Diagnosis

Page 54: DSS

Capabilities of Expert Systems

Page 55: DSS

When to Use Expert Systems

• High payoff• Preserve scarce expertise• Distribute expertise• Provide more consistency than humans• Faster solutions than humans• Training expertise

Page 56: DSS

Components of an Expert System

Page 57: DSS

Knowledge Base

• Assembling human experts

• The use of fuzzy logic

• The use of rules

• The use of cases

Page 58: DSS

Knowledge Base

Page 59: DSS

The Use of Rules

Page 60: DSS

The Knowledge Acquisition Facility

Page 61: DSS

Components of an Expert System

• The explanation facility• The knowledge acquisition facility• The user interface

Page 62: DSS

Expert Systems Development

Page 63: DSS

Participants in Developing and Using Expert Systems

• Domain expert• Knowledge engineer• Knowledge user

Page 64: DSS

Participants in Developing and Using Expert Systems

Page 65: DSS

Domain Experts

• Recognize the real problem• Develop a general framework for problem solving• Formulate theories about the situation• Develop and use general rules to solve a problem• Know when to break the rules or general principles• Solve problems quickly and efficiently

Page 66: DSS

Expert Systems Development Tools and Techniques

Page 67: DSS

Expert Systems Development Tools and Techniques

Page 68: DSS

Expert Systems Development Alternatives

Page 69: DSS

Applications of Expert Systems and Artificial Intelligence

• Credit granting and loan analysis• Stock picking• Catching cheats and terrorists• Budgeting

Page 70: DSS

Virtual Reality

Page 71: DSS

Virtual Reality

• Enables one or more users to move and react in a computer-simulated environment

• Immersive virtual reality - user becomes fully immersed in an artificial, three-dimensional world that is completely generated by a computer

• Virtual reality system - enables one or more users to move and react in a computer-simulated environment

Page 72: DSS

Useful Applications

• Medicine – used to link stroke patients to physical therapists

• Education and training – used by military for aircraft maintenance

• Entertainment – Star Wars Episode II: Attack of the Clones

Page 73: DSS

Useful Applications

• Real Estate Marketing and Tourism– Used to increase real estate sales– Virtual reality tour of the White House

Page 74: DSS

Summary

• Artificial intelligence - used to describe computers with ability to mimic or duplicate functions of the human brain

• Intelligent behavior - includes the ability to learn from experience

• Expert systems - can explain their reasoning (or suggested decisions) and display intelligent behavior

• Virtual reality systems - enables one or more users to move and react in a computer-simulated environment

• Special-purpose systems - assist organizations and individuals in new and exciting ways. For example, Segway