What is a DSS?What is a DSS?

““Decision Support System”: An Decision Support System”: An information system that uses the information system that uses the combination of data, decision models and combination of data, decision models and algorithms, and human intuition, knowledge algorithms, and human intuition, knowledge and judgment to aid a decision maker in and judgment to aid a decision maker in reaching a specific decision.reaching a specific decision.

Tools:Computers andIT. VB, VBA,

Excel, InterDev,Etc.

Humans:Multiple ways

to makedecisions.

Algorithms:Math/Flow Chart

stuff that helps thetools help the humans

make decisions.

DSS

DSS

Data:Facts pertinentto the decision

at hand.

The Need for Computerized The Need for Computerized Decision Support and the Decision Support and the Supporting TechnologiesSupporting Technologies

Speedy computationsSpeedy computations Overcoming cognitive limits in Overcoming cognitive limits in

processing and storageprocessing and storage Cognitive limits may restrict an Cognitive limits may restrict an

individual’s problem solving capabilityindividual’s problem solving capability Cost reductionCost reduction Technical supportTechnical support Quality supportQuality support Competitive edge: business processes Competitive edge: business processes

reengineering and empowermentreengineering and empowerment

Primary Decision Support Primary Decision Support TechnologiesTechnologies

Management Support Systems (MSS)Management Support Systems (MSS) Decision Support Systems (DSS)Decision Support Systems (DSS) Group Support Systems (GSS), Group Support Systems (GSS),

including Group DSS (GDSS)including Group DSS (GDSS) Executive Information Systems (EIS)Executive Information Systems (EIS) Expert Systems (ES)Expert Systems (ES) Artificial Neural Networks (ANN)Artificial Neural Networks (ANN) Hybrid Support SystemsHybrid Support Systems Cutting Edge Intelligent Systems Cutting Edge Intelligent Systems

(Genetic Algorithms, Fuzzy Logic, (Genetic Algorithms, Fuzzy Logic, Intelligent Agents, ...)Intelligent Agents, ...)

Let’s look at some leading Let’s look at some leading companiescompanies

www.cognos.comwww.cognos.com– ““the world's leading vendor of Business the world's leading vendor of Business

Intelligence solutions for e-business”… a DSS Intelligence solutions for e-business”… a DSS company.company.

– Handles chunks of the NASDAQ Web site.Handles chunks of the NASDAQ Web site. www.datajungle.comwww.datajungle.com

– Provides the data for the much of the above.Provides the data for the much of the above.

Tools:Computers andIT. VB, VBA,

Excel, InterDev,Etc.

Humans:Multiple ways

to makedecisions.

Algorithms:Math/Flow Chart

stuff that helps thetools help the humans

make decisions.

DSS

DSS

Data:Facts pertinentto the decision

at hand.

Tools:Computers andIT. VB, VBA,

Excel, InterDev,Etc.

Humans:DecisionMakingProcess

Algorithms:Math/Flow Chart

stuff that helps thetools help the humans

make decisions.

DSS

DSS

Data:Facts pertinentto the decision

at hand.

Tools:Computers andIT. VB, VBA,

Excel, InterDev,Etc.

Humans:DecisionMakingProcess

Algorithms:Math/Flow Chart

stuff that helps thetools help the humans

make decisions.

DSS

DSS

Data:Facts pertinentto the decision

at hand.

(2nd Half of Class - next two weeks)

Human Cognition and Human Cognition and Decision StylesDecision Styles

Every person makes decisions differently!!!Every person makes decisions differently!!! As a good consultant / analyst, you need to As a good consultant / analyst, you need to

research the decision styles of your research the decision styles of your system’s target audience / user base.system’s target audience / user base.

Cognitive StyleCognitive Style

Two major types:Two major types:–Analytic decision Analytic decision makermaker

–Heuristic decision Heuristic decision makermaker

Some (other) Decision Some (other) Decision StylesStyles

HeuristicHeuristic AnalyticAnalytic Autocratic Autocratic Democratic Democratic Consultative (with individuals or Consultative (with individuals or

groups)groups) Combinations and variationsCombinations and variations

For successful decision making support, For successful decision making support, an MSS must fit the an MSS must fit the – Decision situation Decision situation – Decision styleDecision style

The system The system – should be flexible and adaptable to different should be flexible and adaptable to different

usersusers– have what-if and goal-seeking have what-if and goal-seeking – have graphics have graphics – have process flexibilityhave process flexibility

An MSS should help decision makers use An MSS should help decision makers use and develop their own styles, skills, and and develop their own styles, skills, and knowledgeknowledge

Different decision styles require different Different decision styles require different types of supporttypes of support

Major factor: individual or group decision Major factor: individual or group decision maker maker

The Decision MakersThe Decision Makers IndividualsIndividuals GroupsGroups

IndividualsIndividuals

May still have conflicting objectives May still have conflicting objectives Decisions may be fully automatedDecisions may be fully automated

GroupsGroups

Most major decisions in medium and large Most major decisions in medium and large organizations are made by organizations are made by groupsgroups

Conflicting objectivesConflicting objectives are common are common Variable sizeVariable size People from different departmentsPeople from different departments People from different organizationsPeople from different organizations The The group decision making processgroup decision making process can be very can be very

complicatedcomplicated Consider Consider Group Support SystemsGroup Support Systems (GSS) (GSS)

Organizational DSSOrganizational DSS can help in enterprise-wide can help in enterprise-wide decision making situationsdecision making situations

The Decision-Making The Decision-Making Process Process

Systematic Decision-Making Process Systematic Decision-Making Process (Simon [1977])(Simon [1977])

IntelligenceIntelligence DesignDesign ChoiceChoice ImplementationImplementation

Modeling is Modeling is EssentialEssential to the Process to the Process

Intelligence phaseIntelligence phase– Reality is examined Reality is examined – The problem is identified and definedThe problem is identified and defined

Design phaseDesign phase– Representative model is constructedRepresentative model is constructed– The model is validated and evaluation criteria are setThe model is validated and evaluation criteria are set

Choice phaseChoice phase– Includes a proposed solution to the Includes a proposed solution to the modelmodel – If reasonable, move on to theIf reasonable, move on to the

Implementation phaseImplementation phase– Solution to the original problemSolution to the original problem

FailureFailure: Return to the modeling process: Return to the modeling process

Often Backtrack / Cycle Throughout the Process Often Backtrack / Cycle Throughout the Process

What-If AnalysisWhat-If Analysis Golf example from last week -- “What if I Golf example from last week -- “What if I

changed the price of bags from $105 to $150?” changed the price of bags from $105 to $150?” (we’d make more bags).(we’d make more bags).

Goal SeekingGoal Seeking Backward solution approachBackward solution approach Example: If Cisco returns 20% per year, how Example: If Cisco returns 20% per year, how

much would I have to buy now to retire (65) much would I have to buy now to retire (65) with a million dollars?with a million dollars?

In a DSS the what-if and the goal-seeking In a DSS the what-if and the goal-seeking options options mustmust be easy to perform be easy to perform

Which systems support which phases?

Tools:Computers andIT. VB, VBA,

Excel, InterDev,Etc.

Humans:Multiple ways

to makedecisions.

Algorithms:Math/Flow Chart

stuff that helps thetools help the humans

make decisions.

DSS

DSS

Data:Facts pertinentto the decision

at hand.

Many differentnames!

Acronym HeavenAcronym Heaven

DSS, EIS, ES.DSS, EIS, ES. DSS, EIS differ in sensitivity of information DSS, EIS differ in sensitivity of information

being offered (EIS is more sensitive).being offered (EIS is more sensitive).

ES: Expert SystemsES: Expert Systems

Knowledge Base (facts, rules)Knowledge Base (facts, rules) Inference Engine (software)Inference Engine (software) User InterfaceUser Interface

EXPERT SYSTEMSEXPERT SYSTEMS Expert system: Information system that applies Expert system: Information system that applies

reasoning capabilities and stored knowledge to reasoning capabilities and stored knowledge to reach a conclusion (low level “AI”).reach a conclusion (low level “AI”).

Collect, store, formalize and use large stores of Collect, store, formalize and use large stores of task task specificspecific expertise expertise

What is expertise?What is expertise?– KnowledgeKnowledge: Structured information: Structured information– HeuristicsHeuristics: Rules of thumb compiled from experience: Rules of thumb compiled from experience

Simple example: “Diagnosing” whalesSimple example: “Diagnosing” whaleshttp://www.aiinc.ca/demos/whale.htmlhttp://www.aiinc.ca/demos/whale.html

The Expert SystemThe Expert System

KnowledgeBase

User Workstation

Driverswith Pagers

ExpertAdvice

UserInterfacePrograms

UserInterfacePrograms

InferenceEngine

Program

InferenceEngine

Program

Expert System DevelopmentExpert System Development

Workstation

KnowledgeEngineering

KnowledgeAcquisition

Program

KnowledgeAcquisition

Program

Expert and/orKnowledge Engineer

EXPERT SYSTEM COMPONENTSEXPERT SYSTEM COMPONENTS

Expert Systems ExampleExpert Systems Example ITT Commercial Finance Corp., Expert Credit System ITT Commercial Finance Corp., Expert Credit System

(ECS)(ECS) Uses experience and knowledge of senior credit managers.Uses experience and knowledge of senior credit managers. Analyzes credit information, identifies credit proposal Analyzes credit information, identifies credit proposal

strengths and weaknesses, makes recommendations.strengths and weaknesses, makes recommendations. Available to all decision-making managers (user-friendly, Available to all decision-making managers (user-friendly,

as well).as well). 23 offices, 250 users.23 offices, 250 users. $500,000 savings in hard costs, $1 M bad loan write off $500,000 savings in hard costs, $1 M bad loan write off

savings estimated.savings estimated.

EXAMPLE: CREDIT CARDSEXAMPLE: CREDIT CARDS

American Express does not have fixed American Express does not have fixed account limits, but instead decides each account limits, but instead decides each credit authorization on a case-by-case credit authorization on a case-by-case basis. What might be some basis. What might be some rules or rules or heuristics for this decision processheuristics for this decision process??

Expert Systems ExamplesExpert Systems Examples Karl Irwin gets engaged.Karl Irwin gets engaged. Diagnosing illnesses.Diagnosing illnesses.

Expert Systems: Leading Expert Systems: Leading CompaniesCompanies

EXSYS (EXSYS, Inc.)   EXSYS (EXSYS, Inc.)   http://www.exsys.comhttp://www.exsys.com

K-Vision (Ginesys Corp.)   K-Vision (Ginesys Corp.)   http://www.ginesys.comhttp://www.ginesys.com

KnowledgePro (Knowledge Garden, Inc.)   KnowledgePro (Knowledge Garden, Inc.)   http://www.kgarden.comhttp://www.kgarden.com

EXAMPLE: CHOOSING WINESEXAMPLE: CHOOSING WINES

What are relevant facts about wines and What are relevant facts about wines and meals?meals?

What are some example rules of thumb for What are some example rules of thumb for pairing different kinds of wine with pairing different kinds of wine with different kinds of meals?different kinds of meals?

WINE EXAMPLE: FACTSWINE EXAMPLE: FACTSFacts about meals (8

facts)Facts about wines (8 facts)

Main_course: Meat, Fish,Poultry, Cajun

Sauce: Tomato, Non-tomato

Flavor: Strong, Delicate

Suggested_color: Red, White

Suggested _body: Full, Light

Suggested _wine: Chablis,Chardonnay, Burgundy,Beaujolis

WINE EXAMPLE: IF-THEN WINE EXAMPLE: IF-THEN RULESRULES

Intermediate Conclusions

If Main_course is Meat or Sauce is Tomatothen Suggested_color is Red

If Main_course is Fish or Poultry and Sauce isNot_Tomato thenSuggested_color is White

If Flavor is Strongthen Suggested_body is Full

If Flavor is Delicatethen Suggested_body is Light

WINE EXAMPLE: IF-THEN WINE EXAMPLE: IF-THEN RULESRULES

Final Conclusions

If Suggested_body is Light and Suggested_color isWhite then Suggested_wine is Chablis

If Suggested_body is Full and Suggested_color isWhite then Suggested_wine is Chardonnay

If Suggested_body is Full and Suggested_color isRed then Suggested_wine is Burgundy

If Suggested_body is Light and Suggested_color isRed then Suggested_wine is Beaujolis

DomainDomain:: Narrow and well defined Narrow and well defined ExpertiseExpertise:: Requires true expertise in short Requires true expertise in short

supplysupply ComplexityComplexity:: Problem is too complex for Problem is too complex for

conventionalconventional programmingprogramming StructureStructure:: Solution process must cope with ill- Solution process must cope with ill-

structure, uncertainty, missing datastructure, uncertainty, missing data AvailabilityAvailability:: Have a willing, articulate expert!! Have a willing, articulate expert!!

WHEN IS AN EXPERT WHEN IS AN EXPERT SYSTEM APPROPRIATE?SYSTEM APPROPRIATE?

DSS vs. Expert SystemDSS vs. Expert System

DSS: DSS:

– Fixed models and Fixed models and formulasformulas

– Usually user driven; Usually user driven; user has expertise, user has expertise, user asks the questionsuser asks the questions

– Does not explain Does not explain answersanswers

Expert system Expert system

– Mimics human Mimics human reasoning abilitiesreasoning abilities

– Usually machine Usually machine driven; machine has driven; machine has expertise; machine expertise; machine asks the questionsasks the questions

– Has explanation Has explanation facilityfacility