MBA 669Special Topics: IT-enabled organizational Forms

Dave Salisburysalisbury@udayton.edu (email)

http://www.davesalisbury.com/ (web site)

This Week’s Fun Stuff

Codification of knowledge, expertise and procedures

IT and the control of information/decision-making

IT and the standardization and homogenization of organizations and industries

Issues surrounding the codification of expertise and decision-making

IS&TInvestment Profit

Revenue

Costs

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Why We Invest in IS&T

ManagementSupport & Decision

Systems

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IT and locus of control

Some cases used to push decision-making to lower levels

Some cases used to get control What is the effect of advanced IT

in organizations? Liberating or constraining? Autonomy or top-down control?

Isomorphism and homogenization

Infrastructure Standards Systems Codified procedures

Simon & the rational person

Humans can be rational actors, their rationality is bounded by their limitations

Humans tend to satisfice, or settle on the first acceptable option, rather optimizing

Information stored in computers can increase human rationality if accessible when needed

The central problem is not how to organize to produce efficiently, but how to organize to make decisions (i.e. process information)

IT provides assistance to...

Communicate and/or distribute knowledge

Collaborate with other workers Routinize procedures Capture and codify knowledge Create knowledge

Two key issues

Uncertainty Lack of information

Ambiguity Lack of structure

Online analytical processing

Enables interactive examination/manipulation of detailed & consolidated data from many perspectives

Analyze complex relationships to discover patterns, trends, and exception conditions in real time

Consolidation The aggregation of data. From simple roll-ups to complex groupings of

interrelated data Drill-Down

Display detail data that comprise consolidated data Slicing and Dicing

The ability to look at the database from different viewpoints.

When performed along a time axis, helps analyze trends and find patterns

Decision support systems

What If-AnalysisWhat If-Analysis

Sensitivity AnalysisSensitivity Analysis

Goal-Seeking AnalysisGoal-Seeking Analysis

Optimization AnalysisOptimization Analysis

ImportantDecision SupportSystemsAnalytical Models

ImportantDecision SupportSystemsAnalytical Models

Data mining for decision support

Software analyzes vast amounts of data

Attempts to discover patterns, trends, & correlations

May perform regression, decision tree, neural network, cluster detection, or market basket analysis

Models as decision making aids

A model (in decision making) is a simplified representation of reality.

The benefits of modeling in decision making are: Cost of virtual experimentation is much

lower Simulated compression of time. Manipulating the model is much easier The cost of mistakes are much lower Modeling for “what-ifs” Analysis and comparison of a large number

alternatives Models enhance and reinforce learning

Artificial intelligence

CognitiveScience

Applications

CognitiveScience

Applications

ArtificialIntelligenceArtificial

Intelligence

RoboticsApplications

RoboticsApplications

NaturalInterface

Applications

NaturalInterface

Applications

•Expert Systems•Fuzzy Logic•Genetic Algorithms•Neural Networks

•Visual Perceptions•Locomotion•Navigation•Tactility

•Natural Language•Speech Recognition•Multisensory Interface•Virtual Reality

AI application areas in business

Neural NetworksNeural Networks

Fuzzy Logic SystemsFuzzy Logic Systems

Virtual RealityVirtual Reality

Expert SystemsExpert Systems

AI ApplicationAreas inBusiness

AI ApplicationAreas inBusiness

Intelligent AgentsIntelligent Agents

Genetic AlgorithmsGenetic Algorithms

Expert systems

The Expert SystemThe Expert System

KnowledgeBase

User Workstation

ExpertAdvice

UserInterfacePrograms

UserInterfacePrograms

InferenceEngine

Program

InferenceEngine

Program

Expert System DevelopmentExpert System Development

Workstation

KnowledgeEngineering

KnowledgeAcquisition

Program

KnowledgeAcquisition

Program

Expert and/orKnowledge Engineer

Expert system applications

Decision ManagementDecision Management

Diagnostic/TroubleshootingDiagnostic/Troubleshooting

Maintenance/SchedulingMaintenance/Scheduling

Design/ConfigurationDesign/Configuration

Selection/ClassificationSelection/ClassificationMajor ApplicationCategoriesof Expert Systems

Process Monitoring/ControlProcess Monitoring/Control

Why have expert systems?

Standardize procedures and their application throughout organization

Share codified procedures more readily

Protect against loss of expertise Preserve expertise for more

important tasks Replace expertise with systems

Codification & leveraging processes

Focus on business processes rather than divisions or functions

Processes tend to cross divisions and functions

IT as enabler of process focus Choosing what goes to people and

what goes to IT Re-engineering focus

Standardization

Standardization as diminishing freedom or as enhancing reliability?

Does structure constrain or enable? What impact does it have on

codification of knowledge (see more on this Tuesday)?

Good or bad? Why or why not?

Widespread analytics

Heavy use of modeling and optimization routines

Enterprise approach (can’t be piecemeal to get the big benefits)

Ever more sophisticated tools Again, most of this was not doable until

the advent of sophisticated IT Still need to apply expertise, experience

and intuition

Diffusion of responsibility

The “myth” of technology neutrality that enables blame to be passed “The computer did it” “That’s what the model came up with” “The computer requires it”

Use of technology implies control by technology At once empowered and dominated Dependent on it to complete tasks

Lost expertise

Codification detaches knowledge from context

Experts are no longer so, and considered expendable

Technology replaces bodies This effect is moving up the

corporate ladder Lack of flexibility in applying the

rules