Complex Decisions and

builderanthologyΤεχνίτη Νοημοσύνη και Ρομποτική

19 Οκτ 2013 (πριν από 3 χρόνια και 10 μήνες)

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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

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?

AI Research Areas


Computer Science


Parallel Processing


Symbolic Processing


Neural Networks


Robotics Applications


Visual Perception


Tactility


Dexterity


Locomotion and Navigation

AI 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

AI Questions


What is intelligence?


Can machines ever think like humans?


How do humans think?


Do we really want computers to think like
us?

Other AI 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

The Future



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