Table Of ContentThe Rise of the
Expert Company
HOW VISIONARY COMPANIES ARE
USING ARTIFICIAL INTELLIGENCE TO ACHIEVE
HIGHER PRODUCTIVITY AND PROFITS
Edward Feigenbaum
Pamela McCorduck
H. Penny Nii
M
MACMILLAN
LONDON
Copyright © Edward Feigenbaum, H. Penny Nii and Pamela
McCorduck 1988 Introduction copyright © Tom Peters 1988
All rights reserved. No reproduction, copy or transmission
of this publication may be made without written permission.
No paragraph of this publication may be reproduced, copied
or transmitted save with written permission or in
accordance with the provisions of the Copyright Act 1956
(as amended). Any person who does any unauthorized act
in relation to this publication may be liable to criminal
prosecution and civil claims for damages.
Chapter 16 of this book was written by Paul Harmon.
Copyright © Harmon Associates 1988. All rights reserved.
Used by permission.
First published in the United States of America 1988 by Times
Books, New York
First published in the United Kingdom 1988 by
MACMILLAN LONDON LIMITED
4 Little Essex Street London WC2R 3LF
and Basingstoke
Associated companies in Auckland, Delhi, Dublin,
Gaborone, Hamburg, Harare, Hong Kong, Johannesburg,
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ISBN 0-333-49659-0
A CIP catalogue record for this book is available from the
British Library.
Printed in Great Britain by
Mackays of Chatham plc, Chatham, Kent.
The Rise of the Expert Company
Also by Edward Feigenbaum and Pamela McCorduck
THE FirrH GENERATION:
Artificial Intelligence and Japan’s
Computer Challenge to the World
Also by Pamela McCorduck
FAMILIAR RELATIONS
WORKING TO THE END
MAacHINgEs WHo THINK
UNIVERSAL MACHINE
Also by H. Penny Nii
THE First ARTIFICIAL INTELLIGENCE COLORING BOOK
Contents
Foreword: The Rise of the Expert Company
by Tom Peters
1. Working Smarter / 3
2. The Microcosm Called Northrop / 16
3. What's an Expert System? / 37
4. Internal Cost Savings and Product Quality Control / 49
IBM / 50
FMC / 78
Toyota / 83
The British National Health Service | 86
5. Quality and Consistency in Decision Making / 97
American Express | 92
Nippon Life Insurance Company / 114
The British Pension Advisor / 118
Sanwa Bank | 119
6. Technology Insertion: Hard Work, Vision, and Luck / 123
7. Making Waves at Du Pont / 134
Vv
vi - Contents
Preserving, Using, and Selling Expertise / 157
Nippon-Kokan Steel / 158
The Lend Lease Corporation of Australia | 162
Schlumberger Ltd. / 166
Westinghouse / 169
A New Business to Be In / 174
Texas Instruments / 174
Arthur Andersen / 188
The Fujitsu Company / 192
The Fifth Generation in Japan and Europe / 196
Restructuring a Business to Enlarge Customer Choice / 275
Digital Equipment Corporation / 216
Navistar / 232
12. Stimulating Innovation by “Working Smarter’ / 239
Canon / 240
Kajima | 244
The Second Era of Knowledge Processing / 250
13.
14. Looking Around and Looking Ahead / 258
Appendix: Expert Systems in Use
by Paul Harmon / 273
Glossary / 317
Foreword
THE RISE OF THE EXPERT COMPANY by Tom Peters
THE WORLD OF ORGANIZING HUMAN ACTIVITIES is undergoing
its first genuine revolution since the correctly labeled in-
dustrial “revolution” of the late eighteenth century. The
information-processing technologies that are powering the
new revolution may eventually have even more impact on
human organization—public and private—than did the mass
production revolution, powered first by steam. It is even
plausible to state that this information-technology-inspired
transformation in the way we organize and execute affairs
is the most fundamental since the Chinese developed hier-
archical models of administration to pull together their vast
empire several thousand years ago.
The still-youthful applications of artificial intelligence
(along with the accelerating spread and deployment of high-
speed, high-storage-capacity microcomputers) really provide
our first inkling of what that revolution will eventually be
all about. Most new technologies are initially applied to pe-
ripheral or even frivolous tasks (for instance, the first tape
recorder, which was developed in Japan, was used in bars,
where drunks enjoyed listening to their own slurred voices).
So, too, with information technology. For its first twenty-
five years or so, following the beginning of widespread use
after World War II, the only serious impact was on the most
mundane of tasks, such as payroll processing. _
Miniaturization and the microcomputer user’s growing
vii
viii « Foreword
ability to break the barriers of the plodding, conservative
Management Information Systems (MIS) baronies have be-
gun to change this, attested to by 9 million personal com-
puter (PC) sales in 1987 in the U.S., and the explosion of
software houses, which have introduced 15,000 new pro-
grams in the last three years. But most current PC uses will
surely be viewed in twenty years, perhaps even in ten, as
small potatoes, too. AI is increasingly where the action is.
And, thanks to this pioneering book, even the skeptical lay-
man will readily see that.
Artificial intelligence is a harsh term, as threatening to “‘us
professionals” (most readers of this book) as the powered
loom was to artisans two hundred years ago and ‘‘automa-
tion” was to the blue-collar worker some forty years ago.
After all, tools to date, starting with the wheel, have simply
replaced brute physical labor (even the most blue ‘collar of
white-collar work, such as the laborious task of doing pay-
roll). But now the quintessential human trait, intelligence,
is at risk to machines. That was the vague fear we all har-
bored, and the AI gurus did not help allay it. They sang of
a revolution that would replace skilled professionals. Yet the
first applications of AI seemed trivial, which added to the
confusion.
While this one book will not by itself cause the world to
reverse its direction of spin, it is, in my view, the first mo-
tivating, demystifying exposition of the real, practical—and
yet exciting, even inspiring and definitely revolutionary—
world of AI.
You will find no theory here, though there are enough
definitions and explanations to stoke your interest, if you
are a total novice to the field. What you will find, painstak-
ingly provided by pioneer and renowned AI scholar Ed Fei-
genbaum and his colleagues, Pamela McCorduck and
H. Penny Nii, are cases. Beautiful, rich cases. Practical cases
that you can sink your teeth into. Compelling cases about
people (impassioned AI champions) and turf fights (usually
practical AI experimenters taking on the often-reactionary
central MIS function). In all, there are some twenty cases.
The manufacturing sector is well represented (Navistar,
FMC, IBM, Du Pont, DEC, Westinghouse et al.), and so is
Foreword - ix
the service sector (American Express, Arthur Andersen). The
public sector (British National Health Service, British Pension
Advisory Service) is here, too; and Japan’s pathbreaking
firms are also examined in detail—Kajima in construction,
Canon, Fujitsu, steelmaker Nippon-Kokan, Toyota and Nip- |
pon Life.
The book, you might say, consists of twenty good yarns.
The first comes from Northrop. A pair of relatively powerless
(junior) engineers tackle the laborious, essential, and high-
skill task of translating engineering drawings into a detailed
plan for manufacturing complex aircraft parts. One of the
upstarts builds his first expert system on an Apple computer
at home, with surreptitiously acquired resources and lots of
cover provided by his partner. User number one is his wife,
naive to engineering, who is awakened at 3:00 a.m. to be
the guinea pig. From such a humble beginning, startling
results are achieved. A difficult task that used to take several
days is reduced to ten to fifteen minutes, and reliability soars.
Moreover, the expertise of aging engineers in short supply
is captured forever.
If Northrop’s way of backing into AI (albeit involving a
critical task) is at one end of the spectrum, the monster IBM
is at the other. AI, says its grandees, is the future. But the
lovely description of the beginning of the AI revolution at
Big Blue is again practical. There are now fully four dozen
significant Al systems up and running at IBM, with at least
120 significant systems under active development. We are
allowed to peek at one that aids production of the state-of-
the-art one-megabit chip at IBM’s Burlington, Vermont, fa-
cility and another that helps with final inspection of big disc
drive mass storage systems at IBM-San Jose. Yet a third IBM
system is a pioneering attempt to apply AI to complex, ex-
pensive internal processes, which are so far resistant to pro-
ductivity improvement efforts. —
Other ‘bet the company” AI sagas emerge at such places
as DEC and, most surprising of all, Navistar (the old Inter-
national Harvester). Both of these firms’ pioneering—and
revolutionary—systems are aimed only secondarily at in-
creasing efficiency. The chief objective is adding value for
the customer by substantially customizing every product.
x * Foreword
Big systems with giant payoffs are also explored in a case
study from American Express, where credit approval process
expertise is captured, causing big efficiencies, and even
greater (revolutionary is, once more, not too strong a word)
improvement in effectiveness, an improvement the customer
can feel. The sometimes almost lurid details of the tortuous
implementation process at Amex are in themselves a dandy
guide for would-be AI champions.
But most exciting to me was the Du Pont story. Du Pont
certainly wins hands down at the numbers game. It has two
hundred expert systems already up (a staggering number,
considering the authors’ estimate that 1,500 systems were
up and running worldwide by the end of 1987) and a whop-
ping six hundred in the works!
It’s at Du Pont that we learn about ‘““Mike-in-the-Box,”’ the
actual name of one expert system that is the essence of this
exciting and eminently practical book. The real Mike is sim-
ply the best engineer Du Pont has at purging a distillation
column of impurities, one of the most demanding of human
tasks in the real world of commercial chemical engineering,
especially when it comes to producing 99.9 percent pure
material for solid state electronics applications. A great deal
of the real Mike’s unique expertise is boiled down to
hundreds of ‘‘rules’’ and captured in an expert system run
on a PC. (Almost all of Du Pont’s applications are PC-based.)
The overall Du Pont AI champion, Ed Mahler, oversees his
“pirate-ship operation’ with just a tiny full-time staff. He
largely eschews giant investments and instead urges engi-
neers, by the bushelsful, to spend just one month and five
to ten thousand dollars in developing each new PC-based
system. The average impact of each is about a hundred thou-
sand dollars! The pleasantly nonthreatening term for a Du
Pont system is Partners for Experts.
Mike-in-the-Box, ‘‘God in the works” (the captured ex-
pertise of an aging, irreplaceable blast furnace expert at
Nippon-Kokan), ‘‘Geoff’s Book” (thousands of expert rules
from the head of the senior, top estimator at building con-
tractor Lend Lease of Australia), and J. A. Gilreath (Schlum-
berger’s ace oilfield data interpreter, whose expertise is now
enshrined in that company’s Dipmeter Advisor system) are
