1. Decision Support System
Module 6 :
Decision Support System
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2. TKF 2263 Komputer Aplikasi II
Learning Objectives
Identify the changes taking place in the form and 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 management information systems. 2
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Learning Objectives
Explain how the following information systems can support the information needs of executives, managers, and business professionals:
Executive information systems
Enterprise information portals
Knowledge management systems 3
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Learning Objectives
Identify how neural networks, fuzzy logic, genetic algorithms, virtual reality, and intelligent agents can be used in business.
Give examples of several ways expert systems can be used in business decision-making situations. 4
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5. Information required at different management levels
Information required at different management levels 5
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6. Levels of Management Decision Making
Levels of Management Decision Making
Strategic management
Executives develop organizational goals, strategies, policies, and objectives
As part of a strategic planning process
Tactical management
Managers and business professionals in self-directed teams
Develop short- and medium-range plans, schedules and budgets
Specify the policies, procedures and business objectives for their subunits 6
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7. Levels of Management Decision Making
Levels of Management Decision Making
Operational management
Managers or members of self-directed teams
Develop short-range plans such as weekly production schedules 7
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Information Quality
Information products whose characteristics, attributes, or qualities make the information more value
Information has 3 dimensions:
Time
Content
Form 8
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9. Attributes of Information Quality
Attributes of Information Quality 9
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Decision Structure
Structured – situations where the procedures to follow when a decision is needed can be specified in advance
Unstructured – decision situations where it is not possible to specify in advance most of the decision procedures to follow
Semistructured - decision procedures that can be prespecified, but not enough to lead to a definite recommended decision
Need information systems to support decisions of all types.
Decision support systems support the unstructured with unscheduled ad hoc reports
Management information systems support the more structured with prespecified reports 10
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11. Information Systems to support decisions
Information Systems to support decisions
Management Information Systems
Decision Support Systems
Decision support provided
Provide information about the performance of the organization
Provide information and techniques to analyze specific problems
Information form and frequency
Periodic, exception, demand, and push reports and responses
Interactive inquiries and responses
Information format
Prespecified, fixed format
Ad hoc, flexible, and adaptable format
Information processing methodology
Information produced by extraction and manipulation of business data
Information produced by analytical modeling of business data 11
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12. Decision Support Trends
Decision Support Trends
Personalized proactive decision analytics
Web-Based applications
Decisions at lower levels of management and by teams and individuals
Business intelligence applications 12
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13. Business Intelligence Applications
Business Intelligence Applications 13
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14. Decision Support Systems (DSS)
Decision Support Systems (DSS)
Provide interactive information support to managers and business professionals during the decision-making process
Use:
Analytical models
Specialized databases
A decision maker’s own insights and judgments
Interactive computer-based modeling
To support semistructured business decisions 14
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DSS components
Example is a Web-enabled marketing DSS. Note the hardware, software, model, data and network resources involved. 15
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DSS Model base
Model base
A software component that consists of models used in computational and analytical routines that mathematically express relations among variables
Examples:
Linear programming models,
Multiple regression forecasting models
Capital budgeting present value models
Unlike an MIS, DSS contains a model base as well as a database 16
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Using DSS
What-if Analysis
End user makes changes to variables, or relationships among variables, and observes the resulting changes in the values of other variables
Sensitivity Analysis
Value of only one variable is changed repeatedly and the resulting changes in other variables are observed 17
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18. Management Information Systems (MIS)
Management Information Systems (MIS)
Produces information products that support many of the day-to-day decision-making needs of managers and business professionals
Prespecified reports, displays and responses
Support more structured decisions 18
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19. MIS Reporting Alternatives
MIS Reporting Alternatives
Periodic Scheduled Reports
Prespecified format on a regular basis
Exception Reports
Reports about exceptional conditions
May be produced regularly or when exception occurs
Demand Reports and Responses
Information available when demanded
Push Reporting
Information pushed to manager 19
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20. Online Analytical Processing (OLAP)
Online Analytical Processing (OLAP)
Enables mangers and analysts to examine and manipulate large amounts of detailed and consolidated data from many perspectives
Done interactively in real time with rapid response 20
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21. OLAP Analytical Operations
OLAP Analytical Operations
Consolidation
Aggregation of data
Drill-down
Display detail data that comprise consolidated data
Slicing and Dicing
Ability to look at the database from different viewpoints 21
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OLAP Technology 22
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23. Geographic Information Systems(GIS)
Geographic Information Systems(GIS)
That uses geographic databases to construct and display maps and other graphics displays
That support decisions affecting the geographic distribution of people and other resources
Often used with Global Position Systems (GPS) devices 23
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24. Data Visualization Systems (DVS)
Data Visualization Systems (DVS)
Represents complex data using interactive three-dimensional graphical forms such as charts, graphs, and maps
DVS tools help users to interactively sort, subdivide, combine, and organize data while it is in its graphical form. 24
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Data Mining
Main purpose is to provide decision support to managers and business professionals through knowledge discovery
Analyzes vast store of historical business data
Tries to discover patterns, trends, and correlations hidden in the data that can help a company improve its business performance
Use regression, decision tree, neural network, cluster analysis, or market basket analysis 25
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26. Market Basket Analysis
Market Basket Analysis
One of most common data mining for marketing
The purpose is to determine what products customers purchase together with other products 26
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27. Executive Information Systems
Executive Information Systems
EIS
Combine many features of MIS and DSS
Provide top executives with immediate and easy access to information
About the factors that are critical to accomplishing an organization’s strategic objectives (Critical success factors)
So popular, expanded to managers, analysts and other knowledge workers 27
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Features of an EIS
Information presented in forms tailored to the preferences of the executives using the system
Customizable graphical user interfaces
Exception reporting
Trend analysis
Drill down capability 28
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29. Enterprise Interface Portals
Enterprise Interface Portals
EIP
Web-based interface
Integration of MIS, DSS, EIS, and other technologies
Gives all intranet users and selected extranet users access
To a variety of internal and external business applications and services
Typically tailored to the user giving them a personalized digital dashboard 29
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30. Enterprise Information Portal Components
Enterprise Information Portal Components 30
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31. Knowledge Management Systems
Knowledge Management Systems
The use of information technology to help gather, organize, and share business knowledge within an organization
Enterprise Knowledge Portals
EIPs that are the entry to corporate intranets that serve as knowledge management systems 31
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32. Enterprise Knowledge Portals
Enterprise Knowledge Portals 32
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33. Artificial Intelligence (AI)
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 33
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34. Attributes of Intelligent Behavior
Attributes of Intelligent Behavior
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
Respond quickly and successfully to new situations
Recognize the relative importance of elements in a situation
Handle ambiguous, incomplete, or erroneous information 34
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35. Domains of Artificial Intelligence
Domains of Artificial Intelligence 35
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Cognitive Science
Based in biology, neurology, psychology, etc.
Focuses on researching how the human brain works and how humans think and learn 36
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Robotics
Based in AI, engineering and physiology.
Robot machines with computer intelligence and computer controlled, humanlike physical capabilities. 37
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Natural Interfaces
Based in linguistics, psychology, computer science, etc.
Includes natural language and speech recognition
Development of multisensory devices that use a variety of body movements to operate computers
Virtual reality
Using multisensory human-computer interfaces that enable human users to experience computer-simulated objects, spaces and “worlds” as if they actually exist 38
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Expert Systems ES
A 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 39
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40. Expert System Components
Expert System Components
Knowledge Base
Facts about specific subject area
Heuristics 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 40
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41. Expert System Components
Expert System Components 41
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42. Methods of Knowledge Representation
Methods of Knowledge Representation
Case-Based – knowledge organized in form of cases
Cases: examples of past performance, occurrences and experiences
Frame-Based – knowledge organized in a hierarchy or network of frames
Frames: entities consisting of a complex package of data values 42
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43. Methods of Knowledge Representation
Methods of Knowledge Representation
Object-Based – knowledge organized in network of objects
Objects: data elements and the methods or processes that act on those data
Rule-Based – knowledge represented in rules and statements of fact
Rules: statements that typically take the form of a premise and a conclusion
Such as, If (condition) then (conclusion) 43
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44. Expert System Benefits
Expert System Benefits
Faster and more consistent than an expert
Can have the knowledge of several experts
Does not get tired or distracted by overwork or stress
Helps preserve and reproduce the knowledge of experts 44
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45. Expert System Limitations
Expert System Limitations
Limited focus
Inability to learn
Maintenance problems
Developmental costs
Can only solve specific types of problems in a limited domain of knowledge 45
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46. Suitability Criteria for Expert Systems
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 46
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Development Tool
Expert System Shell
Software package consisting of an expert system without its knowledge base
Has inference engine and user interface programs 47
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Knowledge Engineer
A professional who works with experts to capture the knowledge they possess.
Builds the knowledge base using an iterative, prototyping process. 48
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Neural Networks
Computing systems modeled after the brain’s mesh-like network of interconnected processing elements, called neurons
Interconnected processors operate in parallel and interact with each other
Allows network to learn from data it processes 49
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Fuzzy Logic
Method of reasoning that resembles human reasoning
Allows for approximate values and inferences and incomplete or ambiguous data instead of relying only on crisp data
Uses terms such as “very high” rather than precise measures 50
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Genetic Algorithms
Software that uses
Darwinian (survival of the fittest), randomizing, and other mathematical functions
To simulate an evolutionary process that can yield increasingly better solutions to a problem 51
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Virtual Reality (VR)
Computer-simulated reality
Relies on multisensory input/output devices such as
a tracking headset with video goggles and stereo earphones,
a data glove or jumpsuit with fiber-optic sensors that track your body movements, and
a walker that monitors the movement of your feet 52
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Intelligent Agents
A software surrogate for an end user or a process that fulfills a stated need or activity
Uses its built-in and learned knowledge base
To make decisions and accomplish tasks in a way that fulfills the intentions of a user
Also called software robots or bots 53
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User Interface Agents
Interface Tutors – observe user computer operations, correct user mistakes, and provide hints and advice on efficient software use
Presentation – show information in a variety of forms and media based on user preferences
Network Navigation – discover paths to information and provide ways to view information based on user preferences
Role-Playing – play what-if games and other roles to help users understand information and make better decisions 54
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55. Information Management Agents
Information Management Agents
Search Agents – help users find files and databases, search for desired information, and suggest and find new types of information products, media, and resources
Information Brokers – provide commercial services to discover and develop information resources that fit the business or personal needs of a user
Information Filters – receive, find, filter, discard, save, forward, and notify users about products received or desired 55
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