decision support, knowledge management and expert systems brian mennecke
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Decision Support, Knowledge Management and
Expert Systems
Brian Mennecke
How can IT be used to support decision makers?
• By supporting various individual and team activities and roles:– Communication and team interaction– The assimilation and filtering of data– Assist with problem recognition– Assist with problem solving– Putting together the results into a cohesive package
Data is turned into information, but the decision maker also needs Knowledge to make decisions
• Types of knowledge:– Descriptive Knowledge– Procedural Knowledge– Reasoning Knowledge
• Forms of Knowledge – Tacit Knowledge– Explicit Knowledge
Examples of technologies that can support or enhance the transformation of knowledge
(IBM Systems Journal) Tacit to Tacit Tacit to Explicit
E-meetings Answering questions
Synchronous collaboration (chat) Annotation
Explicit to Tacit Explicit to Explicit
Visualization Text search
Browsable video/audio of presentations
Document categorization
Knowledge Management Tools
• Text and Forms management• Database and Reporting management• Spreadsheet, Solvers and Charts
management• Programming management.• Rules management
Decision Support Systems (DSS)DSS can be classified as– data-oriented
• provide tools for the manipulation and analysis of data
– model-based• generally have some kind of mathematical model of the decision
being supported
A model of a DSS
KnowledgeManagement
DecisionMaker
OtherInformation
Systems
External andInternal Data
Data ManagementAttribute Data
Model ManagementAspatial Models
Dialog ManagementAttribute-Based Queries and Reports
AttributeData
ObjectData Knowledge
Management
DecisionMaker
OtherInformation
Systems
External andInternal Data
Data ManagementAttribute Data
Data ManagementAttribute Data
Model ManagementAspatial Models
Model ManagementAspatial Models
Dialog ManagementAttribute-Based Queries and Reports
Dialog ManagementAttribute-Based Queries and Reports
AttributeData
ObjectData
A model of a Spatial DSS
KnowledgeManagement
DecisionMaker
OtherInformation
Systems
External andInternal Data
Data ManagementAttribute DataSpatial Data
Model ManagementAspatial ModelsSpatial Models
Dialog ManagementAttribute-Based Queries and ReportsSpatial-Based Queries and Reports
AttributeData
ObjectData
SpatialData
So, how does a DSS benefit decision makers
• Supplements the decision maker
• Allows improved intelligence, decision, and choice activities
• Facilitates problem solving
• Provides assistance with non-structures decisions
• Assists with knowledge management
Information Requirements by Management Level
StrategicManagement
TacticalManagement
OperationalManagement
Decis
ions
Information
Structured vs. Semi-Structured
• For each decision you make, the decision will fall into one of the following categories:– Structured Decisions– Unstructured – Semi-Structured
Structured Decisions
• Often called “programmed decisions” because they are routine and there are usually specific policies, procedures, or actions that can be identified to help make the decision– “This is how we usually solve this type of
problem”
Unstructured Decisions
• Decision scenarios that often involve new or unique problems and the individual has little or no programmatic or routine procedure for addressing the problem or making a decision
Semi-structured Decisions
• Decision scenarios that have some structured components and some unstructured components.
The Role of the Decision Maker• Decision makers can be
– Individuals– Teams– Groups– Organizations
• All of these types of decision makers will differ in their knowledge and experience; therefore, there will be differences in how they will react to a given problem scenario
The Decision Making Process
• Regardless of the type of decision maker, all decisions involve the following steps– Intelligence – Design– Choice– Decision – Implementation
Strategies for Making Decisions
• Optimization• Satisficing • Elimination by Aspects• Incrementalism• Mixed Scanning• Analytic Hierarchy Process
Spatial DSS: A Geographic Information System
• A geographic information system (GIS) is a computer-based information system that provides tools to collect, integrate, manage, analyze, model, and display data that is referenced to an accurate cartographic representation of objects in space.
(Mennecke, Dangermond, Santoro, Darling, & Crossland, 1995).
Location Based Services
• Location-based services incorporate information about the user's location into the provision of products or services. These include…– Locator services (e.g., where’s the closest ATM?)– Navigation systems (e.g., in the car or on your PC)– M-commerce applications (e.g., proximity alerts,
closest service, mobile advertizing)
GIS Examples
• Online:– www.MapQuest.com – Maps.google.com
• Desktop– ArcGIS by ESRI– MS MapPoint
Expert Systems
• Advisory programs that attempt to imitate the reasoning process of human experts
• Reasons to build Expert Systems– to make the expertise of an individual available
to others in the field– to capture knowledge from an expert who is
likely to be unavailable in the future– to provide consistency in decision making
Characteristics of Human Experts• Recognize and Formulate the problem
• Solve the problem relatively quickly
• Explain the solution and rationale
• Learn from experience
• Restructure knowledge
• Break the rules when necessary
• Determine relevance
Components of an Expert System• An expert system consists of a collection
of integrated and related components, including– Knowledge Base– An Inference Engine– Explanation Facility– Knowledge Acquisition Subsystem– A User Interface.
Characteristics of Expert Systems• Expert systems have the ability to:
– Explain their reasoning or suggested decisions.
– Display “intelligent” behavior.– Manipulate symbolic information and draw
conclusions.– Draw conclusions from complex relationships.– Provide portable knowledge.– Can deal with uncertainty.
– Possibility of error.– Cannot refine own knowledge base.– Difficult to maintain.– May have high development costs.– Raise legal and ethical concerns.– Expertise is hard to extract– Expert Vocabulary and Jargon– Requires a Knowledge Engineer– Experts do not perform well under pressure
Limiting Characteristics of Expert Systems
Uses of Expert Systems
• Strategic goal setting• Planning• Design• Scheduling• Monitoring • Diagnosis
• Debugging• Repair• Instruction• Control• Prediction• Interpretation
When to Use Expert Systems
• Factors that make expert systems worth the high cost:– A high potential payoff or significantly reduced
downside risk.– The ability to capture and preserve
irreplaceable human experience.– The ability to develop a system more
consistent than human experts.
– Expertise needed at a number of locations at the same time.
– Expertise needed in a hostile environment that is dangerous to human health.
– The expert system solution can be developed faster than the solution from human experts.
– Expertise needed for training and development so as to share the wisdom and experience of human experts with many people.
When to Use Expert Systems
Sample Expert Systems
• What’s wrong with your car? http://www.expertise2go.com/webesie/car/
• Buying the right PDAhttp://www.expertise2go.com/shop/pda.htm
• Choosing a Desktop PChttp://www.expertise2go.com/shop/desktop.htm
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