The Strategic
Management of
Information
Technology
Chapter 10
Complex Decisions and
Artificial Intelligence
Transaction Processing
System
Input Output Process
Information
Communication
Systems Development
Process Flow
? Process Flow/Elements
? Components/Elements
? Responsibilities
Overview
? Business Problems
– Complex,less structured
? Data
– Non-numerical,messy,complex relationship
? Artificial Intelligence
– Goal is to make computers,think” like humans
Specialized Problems
? Diagnostic
? Speed
? Consistency
? Training
Building Expert Systems
? Knowledge Base
? Knowledge Engineers
? Case-Based Reasoning
? Limitations of Expert Systems
Expert System
? Expert
? Symbolic and/or Numeric Knowledge
? Knowledge Base
? Expert Decisions made by non-experts
Decision Support System
Compared to Expert System
DS S ES S
Go a l
He lp Us er M ak e
De cis ion
Provide Expert
Advic e
M e th od
Da ta
Model
Pre se ntation
As ks Q ues tions
Applie s rule s a nd
Explains
Ty p e o f
P ro b lem s
Ge nera l,limited by
use r
Na rrow Domain
Building Expert Systems
? Shell = Tool to Build Expert System
? Knowledge Engineer Builds
? Cooperative Expert Key
? Components,
– Knowledge Base
– Information Engineer applies rules to new data
for each conclusion
? Custom Program,Shell,or Pre-packaged
Additional Issues to Consider
? Pattern Recognition/Neural Nets
? Voice and Speech Recognition
? Language Comprehension
? Massively Parallel Computers
? Robotics and Motion
? Statistics,Uncertainty,Fuzzy Logic
Expert Systems
? Goal,Make same decision an expert would
make with the same data
? Capture and program expert’s knowledge
? Advantage of speed and consistency
Expert Systems Problem Type
? Narrow,well-defined domain
? Solutions require an expert
? Complex logical processing
? Handle missing,ill-structured data
? Need a cooperative expert
Limitations of Expert Systems
? Fragile Systems
– Small environment changes can force revision
of all of the rules
? Mistakes
– Who is responsible?
? Expert
? Multiple Expert
? Knowledge Engineer
? Company that uses it
Limitations of Expert Systems
? Vague Rules
– Rules can be hard to define
? Conflicting Experts
– With multiple opinions,who is right?
– Can diverse methods be combined?
Limitations of Expert Systems
? Unforeseen events
– Events outside of domain can lead to nonsense
decisions
– Human experts adapt
– Will human novice recognize a nonsense
result?
Artificial Intelligence
Research Areas
? Computer Science
– Parallel Processing
– Symbolic Processing
– Neural Networks
? Robotics Applications
– Visual Perception
– Tactility
– Dexterity
– Locomotion and Navigation
Artificial Intelligence
Research Areas
? Natural Language
– Speech Recognition
– Language Translation
– Language Comprehension
? Cognitive Science
– Expert Systems
– Learning Systems
– Knowledge-Based Systems
Neural Networks
? Based on brain design
? Hardware and software
? Recognize patterns
– Design specifications
– Spiegel Catalogs
– Pick stocks
Machine Vision
? Advantages of Machine Vision
– Broader spectrum of light
– Will not suffer fatigue
– Damage less easy
? Literal
– Problems less detection than processing
Speech Recognition
? Voice,primarily ID
? Speech
– Transcripts
– Hands-free operations
? Limitations
– Need to train
– Accents and colds
– Synonyms,punctuation,context
Artificial Intelligence
Questions
? What is intelligence?
? Can machines ever think like humans?
? How do humans think?
? Do we really want computers to think like
us?
Artificial Intelligence
Applications
? Massively Parallel Processing
– only if task can be split into independent pieces
– math computation and database searches
? Robotics and Motion
– welding and painting
? Statistics,Unclear,and Fuzzy Logic
– use subjective and incomplete description
Future Applications
? Intelligent Agents
– Learn what you want from what you ask for
and go get it for you
– Automated personal assistant
– Network traffic can be a problem
– Agents are independent of one another
Product
Change
Process Change
Dynamic
Stable
Stable Dynamic
Mass Customization Invention
Mass Production Continuous Improvement
Product-Process Change Matrix
Product
Change
Process Change
Dynamic
Stable
Stable Dynamic
Mass Production
Change conditions Periodic/forecastable changes in product
market demand and process technology
Strategy Production
Key organizational tool Standardized,dedicated production process
Workflows Serial,linear flow of work,executed to plan
Employee roles Separate doers and thinkers
Control system Centralized,hierarchical command system
I/T alignment challenge Automation of manual processes to achieve cost
justified efficiency enhancement
Critical synergy Reliance on invention form to supply new
product designs and new process tech.; linked
with invention forms in single corporate entity
Product-process change matrix
Product
change
Process change
Dynamic
Stable
Stable Dynamic
Invention
Change conditions Constant/unforecastable changes in product
market demand and process technology
Strategy Production of unique or novel product or
process
Key organization tool Specialization of creative or high craft skills
Workflows Independent work
Employee roles Professionals and craftspeople
Control system System decentralized to specialized individuals
and groups
I/T alignment Development and distribution of customized
systems
Critical synergy Mass production form supplied with new
processes; operates in market niches too
dynamic or small for mass production;
sometimes incorporated into single corporate
entity with multiproduct mass-production forms
Figure 3 Product-process change matrix
Product
change
Process change
Dynamic
Stable
Stable Dynamic
Mass Customization
Change conditions Constant/unforecastable changes in market
demand; periodic/forcastable changes in
process technology
Strategy Low cost process differentiation within new
markets
Key organization tool Loosely coupled networks of modular,
flexible processing units
Workflows Customer/product unique value chains
Employee roles Network coordinator and on-demand processors
Control system Hub and web system; centralized network
coordination,independent processing control
I/T alignment Integration of constantly changing network info
processing/communication requirements;
interoperability,data communication,and
coprocessing critical to network efficiency
Critical synergy Reliance on continuous improvement form for
increasing process flexibility within processing
units
Figure 5 Product-process change matrix
Product
change
Process change
Dynamic
Stable
Stable Dynamic
Continuous Improvement
Change conditions Constant/unforecastable changes in process
technology,periodic/forecastable changes in
market demand
Strategy Low cost process differentiation within
mature markets
Key organization tool Self-managing/cross-functional teams
Workflows Intensive and reciprocal workflow within teams
Employee roles Dual,combined doers and thinkers
Control system Microtransformations; rapid and frequent
switching between decentralized team decision
making and team-managed command systems
I/T alignment Design of cross-functional info and
communication systems that support micro-
transformations
Critical synergy Mass-customization form supplied with flexible
new processes; sometimes functions as
transition form in re-engineering to mass
customization
Figure 6 Product-process change matrix
P
E
R
F
O
R
M
A
N
C
E
F
O
C
U
S ORGANIZATIONAL FOCUS
New core
competence Phase 3 Redefinition
Phase 2
Enhancement
Transition Barriers Phase 1 Automation
Value -added
process and services
Excellence
Efficiency
Internal Operations Customer and Supplier
interface
New Business
Units
Management of
Information
Technology
Chapter 10
Complex Decisions and
Artificial Intelligence
Transaction Processing
System
Input Output Process
Information
Communication
Systems Development
Process Flow
? Process Flow/Elements
? Components/Elements
? Responsibilities
Overview
? Business Problems
– Complex,less structured
? Data
– Non-numerical,messy,complex relationship
? Artificial Intelligence
– Goal is to make computers,think” like humans
Specialized Problems
? Diagnostic
? Speed
? Consistency
? Training
Building Expert Systems
? Knowledge Base
? Knowledge Engineers
? Case-Based Reasoning
? Limitations of Expert Systems
Expert System
? Expert
? Symbolic and/or Numeric Knowledge
? Knowledge Base
? Expert Decisions made by non-experts
Decision Support System
Compared to Expert System
DS S ES S
Go a l
He lp Us er M ak e
De cis ion
Provide Expert
Advic e
M e th od
Da ta
Model
Pre se ntation
As ks Q ues tions
Applie s rule s a nd
Explains
Ty p e o f
P ro b lem s
Ge nera l,limited by
use r
Na rrow Domain
Building Expert Systems
? Shell = Tool to Build Expert System
? Knowledge Engineer Builds
? Cooperative Expert Key
? Components,
– Knowledge Base
– Information Engineer applies rules to new data
for each conclusion
? Custom Program,Shell,or Pre-packaged
Additional Issues to Consider
? Pattern Recognition/Neural Nets
? Voice and Speech Recognition
? Language Comprehension
? Massively Parallel Computers
? Robotics and Motion
? Statistics,Uncertainty,Fuzzy Logic
Expert Systems
? Goal,Make same decision an expert would
make with the same data
? Capture and program expert’s knowledge
? Advantage of speed and consistency
Expert Systems Problem Type
? Narrow,well-defined domain
? Solutions require an expert
? Complex logical processing
? Handle missing,ill-structured data
? Need a cooperative expert
Limitations of Expert Systems
? Fragile Systems
– Small environment changes can force revision
of all of the rules
? Mistakes
– Who is responsible?
? Expert
? Multiple Expert
? Knowledge Engineer
? Company that uses it
Limitations of Expert Systems
? Vague Rules
– Rules can be hard to define
? Conflicting Experts
– With multiple opinions,who is right?
– Can diverse methods be combined?
Limitations of Expert Systems
? Unforeseen events
– Events outside of domain can lead to nonsense
decisions
– Human experts adapt
– Will human novice recognize a nonsense
result?
Artificial Intelligence
Research Areas
? Computer Science
– Parallel Processing
– Symbolic Processing
– Neural Networks
? Robotics Applications
– Visual Perception
– Tactility
– Dexterity
– Locomotion and Navigation
Artificial Intelligence
Research Areas
? Natural Language
– Speech Recognition
– Language Translation
– Language Comprehension
? Cognitive Science
– Expert Systems
– Learning Systems
– Knowledge-Based Systems
Neural Networks
? Based on brain design
? Hardware and software
? Recognize patterns
– Design specifications
– Spiegel Catalogs
– Pick stocks
Machine Vision
? Advantages of Machine Vision
– Broader spectrum of light
– Will not suffer fatigue
– Damage less easy
? Literal
– Problems less detection than processing
Speech Recognition
? Voice,primarily ID
? Speech
– Transcripts
– Hands-free operations
? Limitations
– Need to train
– Accents and colds
– Synonyms,punctuation,context
Artificial Intelligence
Questions
? What is intelligence?
? Can machines ever think like humans?
? How do humans think?
? Do we really want computers to think like
us?
Artificial Intelligence
Applications
? Massively Parallel Processing
– only if task can be split into independent pieces
– math computation and database searches
? Robotics and Motion
– welding and painting
? Statistics,Unclear,and Fuzzy Logic
– use subjective and incomplete description
Future Applications
? Intelligent Agents
– Learn what you want from what you ask for
and go get it for you
– Automated personal assistant
– Network traffic can be a problem
– Agents are independent of one another
Product
Change
Process Change
Dynamic
Stable
Stable Dynamic
Mass Customization Invention
Mass Production Continuous Improvement
Product-Process Change Matrix
Product
Change
Process Change
Dynamic
Stable
Stable Dynamic
Mass Production
Change conditions Periodic/forecastable changes in product
market demand and process technology
Strategy Production
Key organizational tool Standardized,dedicated production process
Workflows Serial,linear flow of work,executed to plan
Employee roles Separate doers and thinkers
Control system Centralized,hierarchical command system
I/T alignment challenge Automation of manual processes to achieve cost
justified efficiency enhancement
Critical synergy Reliance on invention form to supply new
product designs and new process tech.; linked
with invention forms in single corporate entity
Product-process change matrix
Product
change
Process change
Dynamic
Stable
Stable Dynamic
Invention
Change conditions Constant/unforecastable changes in product
market demand and process technology
Strategy Production of unique or novel product or
process
Key organization tool Specialization of creative or high craft skills
Workflows Independent work
Employee roles Professionals and craftspeople
Control system System decentralized to specialized individuals
and groups
I/T alignment Development and distribution of customized
systems
Critical synergy Mass production form supplied with new
processes; operates in market niches too
dynamic or small for mass production;
sometimes incorporated into single corporate
entity with multiproduct mass-production forms
Figure 3 Product-process change matrix
Product
change
Process change
Dynamic
Stable
Stable Dynamic
Mass Customization
Change conditions Constant/unforecastable changes in market
demand; periodic/forcastable changes in
process technology
Strategy Low cost process differentiation within new
markets
Key organization tool Loosely coupled networks of modular,
flexible processing units
Workflows Customer/product unique value chains
Employee roles Network coordinator and on-demand processors
Control system Hub and web system; centralized network
coordination,independent processing control
I/T alignment Integration of constantly changing network info
processing/communication requirements;
interoperability,data communication,and
coprocessing critical to network efficiency
Critical synergy Reliance on continuous improvement form for
increasing process flexibility within processing
units
Figure 5 Product-process change matrix
Product
change
Process change
Dynamic
Stable
Stable Dynamic
Continuous Improvement
Change conditions Constant/unforecastable changes in process
technology,periodic/forecastable changes in
market demand
Strategy Low cost process differentiation within
mature markets
Key organization tool Self-managing/cross-functional teams
Workflows Intensive and reciprocal workflow within teams
Employee roles Dual,combined doers and thinkers
Control system Microtransformations; rapid and frequent
switching between decentralized team decision
making and team-managed command systems
I/T alignment Design of cross-functional info and
communication systems that support micro-
transformations
Critical synergy Mass-customization form supplied with flexible
new processes; sometimes functions as
transition form in re-engineering to mass
customization
Figure 6 Product-process change matrix
P
E
R
F
O
R
M
A
N
C
E
F
O
C
U
S ORGANIZATIONAL FOCUS
New core
competence Phase 3 Redefinition
Phase 2
Enhancement
Transition Barriers Phase 1 Automation
Value -added
process and services
Excellence
Efficiency
Internal Operations Customer and Supplier
interface
New Business
Units
