Decision Support, Knowledge Management and Expert Systems Brian Mennecke

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