Transcript MBA 669 - Infrastructure

MBA 669
Special Topics:
IT-enabled organizational Forms
Dave Salisbury
[email protected] (email)
http://www.davesalisbury.com/ (web site)
This Week’s Fun Stuff
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Codification of knowledge, expertise and
procedures
IT and the control of information/decisionmaking
IT and the standardization and
homogenization of organizations and
industries
Issues surrounding the codification of
expertise and decision-making
Why We Invest in IS&T
Revenue
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Management
Support & Decision
Systems
IS&T
Investment
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Costs
Profit
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IT and locus of control
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Some cases used to push decisionmaking to lower levels
Some cases used to get control
What is the effect of advanced IT in
organizations?
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Liberating or constraining?
Autonomy or top-down control?
Isomorphism and homogenization
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Infrastructure
Standards
Systems
Codified procedures
Simon & the rational person
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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...
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Communicate and/or distribute
knowledge
Collaborate with other workers
Routinize procedures
Capture and codify knowledge
Create knowledge
Two key issues
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Uncertainty
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Lack of information
Ambiguity
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Lack of structure
Online analytical processing
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Enables interactive examination/manipulation of
detailed & consolidated data from many perspectives
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Consolidation
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The aggregation of data.
From simple roll-ups to complex groupings of interrelated
data
Drill-Down
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Analyze complex relationships to discover patterns, trends,
and exception conditions in real time
Display detail data that comprise consolidated data
Slicing and Dicing
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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-Analysis
Sensitivity Analysis
Important
Decision
Support
Systems
Analytical Models
Goal-Seeking Analysis
Optimization Analysis
Data mining for decision support
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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
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A model (in decision making) is a simplified
representation of reality.
The benefits of modeling in decision making
are:
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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
Artificial
Intelligence
Cognitive
Science
Applications
•Expert Systems
•Fuzzy Logic
•Genetic Algorithms
•Neural Networks
Robotics
Applications
Natural
Interface
Applications
•Visual Perceptions
•Locomotion
•Navigation
•Tactility
•Natural Language
•Speech Recognition
•Multisensory Interface
•Virtual Reality
AI application areas in business
Neural Networks
Fuzzy Logic Systems
Genetic Algorithms
Virtual Reality
AI Application
Areas in
Business
Intelligent Agents
Expert Systems
Expert systems
The Expert System
Expert
Advice
User
User
Interface
Programs
Inference
Engine
Program
Knowledge
Base
Workstation
Expert System Development
Knowledge
Engineering
Knowledge
Acquisition
Program
Workstation
Expert and/or
Knowledge Engineer
Expert system applications
Decision Management
Diagnostic/Troubleshooting
Maintenance/Scheduling
Design/Configuration
Major
Application
Categories
of Expert Systems
Selection/Classification
Process Monitoring/Control
Why have expert systems?
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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
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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
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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
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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
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The “myth” of technology neutrality that
enables blame to be passed
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“The computer did it”
“That’s what the model came up with”
“The computer requires it”
Use of technology implies control by
technology
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At once empowered and dominated
Dependent on it to complete tasks
Lost expertise
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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