Question 1: You are Professor and Head of
the Department of Information and Systems Management at Hong Kong
University of Science and Technology. I also note that you are a CPA
but assume from your current position that your focus following
University was primarily in Information Systems. How did the idea for
this new book come about and what background do you have in accounting
or what research did you do to prepare you for this subject?
Answer: These ideas have been
germinating for some time, and grew as a result of the unanswered
questions I faced in both the accounting and technology fields. I have
been working on this book, in one way or another, over the past 30
years, in both practice and in academe. On the accounting side, I have
long been displeased with accounting’s inability to describe process,
risk or systems underlying a firm’s operations. On the technology side,
I have long been dissatisfied with our difficulties in making a
value-motivated business case for technology investments. Accounting
abuses during the Internet bubble motivated me to summarize my concerns
–
and the evidence for them – in this book, as well as initial steps
towards resolving these problems.
Bill Gates,
arguably the most influential information technology pundit during the
heady years of the dot-com frenzy, commented ‘the Internet bubble was
the biggest disruption to real innovation in history.’ The Internet
bubble sucked up hundreds of thousands of talented knowledge workers,
and trillions of dollars of resources, giving both to the wrong people.
The bubble inflated on the hype and flawed numbers concocted by flawed
and contradictory valuation systems.
In my mind, two
disparate fraternities shoulder most of the responsibility for
corporate valuation during the dot-com frenzy. The investment
community, with hyperactive analysis and seductive sales pitches,
promoted equity investments using valuations that always seemed on
their way up. The accounting profession, charged since the 1930s with
keeping the investment community in check, provided their moral
conscience.
Well, that’s
the theory.
The priesthood
of accounting, versed in their litany of audit, represents the voice of
probity in the temples of industry. Not far away casting their lots on
Wall Street, are the sinners, stock traders, cheered on by celebrity
analysts. To my surprise, the same language is spoken in both the
temples and the Street – the language of financial accounting. The
priests are empowered to draw up lists of sins and are revered for the
special talents they display. Sinners are not expected to avoid sins;
they need only confess their errors openly. An annual audit is their
plenary indulgence. And by the way, the priesthood is saddled with a
medieval language which daily grows less relevant to a technology laden
market. In my opinion, the priesthood is so ineffective in restraining
sin because the sinners themselves can’t tell when they are
sinning.
I began
thinking about these problems in the 1970s as a Certified Public
Accountant (CPA) employed at the accounting firm of Touche Ross.
Our offices,
in the financial center of Chicago, were shared by corporate financial
analysts and investment bankers. When our paths crossed, as they
sometimes
did on lifts or during lunch, I was perplexed by the fact that the same
language was used in both places. Even more amazing was the occasional
transmogrification of the highest of high priests in our accounting
firm.
When they would leave to the employ of their client firms for corporate
jobs, they – often as not – would visibly metamorphosed into
particularly
wanton sinners. As I struggled against these contrasts, I found that –
for all the purported rigor and formalism of our shared language, that
language
was not, in truth, all it was reputed to be.
I suppose as a
CPA that I am technically a member of the priesthood, though no doubt
that
priesthood would consider me apostate. For the past 30 years I have
concentrated
on information technology and on the management of technology. I have
also grown increasingly skeptical of the efficacy of the accounting’s
dated liturgy. Too many features of 21st century commerce
are simply inexpressible in the language of accounting.
Our present
language of accounting evolved from business conventions used in the
14th century Venetian merchant marine, and in the 16th century English
manorial system for accounting for crops. The fact that neither of
these businesses survives in its historical form is sure to cast
suspicions that as the language
got old, it was unable to express the needs of a complex and evolving
world.
The opinion
that the language of financial accounting is precise, rigorous, and
objective is shared by an embarrassingly large share of both
communities. Accountants argue that their numbers are ‘objective’ and
‘consistent’ thus as close to the truth as is possible; analysts make
similar claims about their predictions. Yet no less an authority than
Harvey Pitt, Chairman of the SEC observed that "there is no true number
in accounting, and if there were, auditors would be the last people to
find it." Only charlatans would claim to speak a language in which only
the truth is ever told – and ‘truth’ in valuation is as much a matter
of degree as intent.
Since there is
no such thing as a faultless account valuation, one might conclude that
assessments of corporate value without an estimate of the error in that
value also
must be the work of charlatans. Yet this is the world of the accounting
priesthood. Account valuations are stated with precision to the penny,
and any assessment of error in their accounts – the ‘materiality’ – is
carefully guarded and reported only under coercion from the courts.
The broad gap
between accounting practice, on the one hand, and investment, on the
other, might be expected to create tensions. In fact, a calm exists
between the priesthood, and the legion of inveterate sinner-analysts –
an equilibrium lubricated by generous salaries and even more generous
commissions.
The sinners on
The Street may indeed be sinning because they have no way of
understanding
the liturgy. Can unavoidable sins truly be sins after all? Mr. Pitt
seems
not to think so, remarking that
"No investor –
certainly not any ordinary investor – can read these [financial
reports] in a way that’s useful. An investor can’t know what’s been
left out, why it’s left out or how it compares with other companies’
calculations. The quality of financial reporting leaves a great deal to
be desired. Even if there were no issuer problems, the information is
not timely – it’s stale when investors get it. Worse, it’s impenetrable
" Or as it was bluntly put by Lehman Brothers accounting expert Robert
Willens: "I don’t know anyone who uses GAAP net income anymore for
anything."
Being a CPA
myself, Mr. Willens’ and Mr. Pitt’s criticisms clearly hit a nerve. For
nearly
30 years I have observed my colleagues both in academe and in practice.
I analyzed in my book ‘Valuing Technology’ my understanding of
what
it is that both the sinners and priesthood were up to – and more
importantly,
how both have grown totally ineffective in addressing the dictates of
the
knowledge economy.
Question 2: Obviously, the subject of
accounting has become much more on everyone’s mind since the Enron
disaster. Did you see this situation developing and do you believe it
demonstrated new lessons that you would have liked to include in your
book or was your focus more on the dot com meltdown of the last several
years?
Answer: Like most people, before their
problems became public, I took Enron’s public pronouncements as well as
their financial statements at face-value. And I for one, truly wanted
to believe that Jeff Skilling had discovered a generic system for
electronic markets which was applicable across products. These sorts of
B2B exchanges were a major topic in my previous book, Global Electronic
Commerce (MIT Press, 2000).
I don’t
actually believe that Jeff Skilling started out with anything less than
good (if
not over ambitious) intentions. Certainly the subsequent cover-up is
reprehensible, but if Skilling had wanted to bilk the public, he is
clever enough to have avoided such a messy and complex denouement.
Instead, I
believe that Jeff Skilling (perhaps overenthusiastically and
uncritically) championed Enron’s vision of electronic B2B markets. He
did so in the context of intense competition and politics within Enron.
Skilling had initially argued that electronic markets only work with
fungible commodities (i.e., each unit is interchangeable with another),
until some of Enron’s information technology staff came up with a
"principal-intermediated" model of trading (similar to the NASDAQ stock
trading system) which allowed non-fungibles such as electricity and
bandwidth to be traded. In this model, Enron was forced to
take large positions (perhaps 10% to 50% of the market) in contracts
for
perishable commodities (e.g., a contract for electricity on Sunday has
effectively
perished by Monday). This "principal-intermediated" model of trading
system
was able to make markets in electricity and bandwidth; a truly "open
platform"
system which merely searched through orders and matched up buyers and
sellers
could not make markets in such contracts because they are too
illiquid.
The problem is
that by taking positions in these contracts, Enron also shouldered the
risk
of the contracts expiring without ever being sold. Even a small number
of expirations could wipe out the profits from other trading. Such
"principal-intermediated" markets require specialization and an
intimate understanding of demand for the commodity. For example, NASDAQ
dealers and NYSE specialists typically specialize in only a few
companies they know well. Enron probably had this intimate knowledge of
demand in oil and gas contracts, but it is doubtful they had it across
the 1000 or so markets in which they dabbled.
Add to this a
lot of young, ambitious and adrenaline charged traders, and a culture
that
according to Enron’s 2000 annual report says it "is laser-focused on
earnings
per share" and risk simply grew out of control. Enron’s trading losses
were not a matter of ‘if’ but a matter of ‘when.’ I’m sure that
Skilling realized that he was in over his head when he stepped down in
Summer 2001.
The evidence of
problems had been there for some time. EnronOnline’s transaction
volumes grew at 60% in 1999, and 30% in 2000 and 2001, with declining
profitability of each transaction. Revenues grew by $10 billion from
1998 to 1999, and then jumped by another $60 billion to $100 billion in
2000. Profits before tax, on the other hand, rose by $1 billion in
1998, and by under $500m in both 1999 and
2000. Enron's return on capital was only 6.6% in 2000, less than rivals
such
as Williams and Dynegy.
Enron delayed
its day of reckoning by offloading risk to ‘special-purpose entities’ –
off-balance-sheet entities were set up. These were not wholly
independent of Enron, but were judged sufficiently separate that their
profit or loss did not have to be consolidated into the company's
results. Assets, i.e, contracts for perishables or portfolios of
perishables, were then "sold" to these entities.
Reckoning came
suddenly. In October 2001, Enron wrote-off $1 billion on water
distribution, broadband trading and other investments, and suffered a
$1.2 billion capital reduction from "hedging" (i.e. a ploy to lock in profits
through reducing the volatility
of a portfolio
by reducing the risk of loss.) Much of the subsequent investigation has
centered on the cover-up of Enron’s problems rather than the structural
problems
that led to them. But until we learn from Enron’s mistakes, there can
be
no guarantee against a similar debacle in the near future.
Question 3: In your introduction you note
that this book puts forward "your thoughts on the next stage in the
development of tools and techniques that are needed to guide investors
and managers in the as yet inadequately charted realms of the
technology-intensive, knowledge-centric industries of the twenty-first
century." What has been the reception of the book and has your hoped
for dialogue already started?
Answer: I am delighted with the
response I have received so far on ‘Valuing Technology.’ Much of the
work on the
book was done during the period of the dot.com frenzy. I expected
criticism
from dot.com evangelists and financial promoters alike. But the dot.com
crash and the subsequent outrage over abuses at the large securities
and
accounting firms have aroused a general awareness that the axis of
business
and wealth has shifted – from ‘things’ to ‘ideas.’ The transformation
has
been taking place over the past 20 years, and only in the 1990’s came
to
dominate economics. ‘Valuing Technology’ identifies and articulates
these
changes, and also shows why the classical approaches to valuation –
employed
in GAAP financial accounting, and approaches like discounted cash flow
and
residual income – work only for a declining portion of the economy.
Today,
that portion of the economy accounts for under 20% of US GDP, and less
than
15% of jobs. It is represented in the sunset industries of the
industrial
economy. My book’s publication has brought my research work over the
past
two decades to the attention of others who have been promoting the need
for revisions in accounting and financial valuation (with, I might add,
only mixed success). To some extent, we have all had to oppose powerful
and inherently conservative accounting and finance communities who have
lobbied for their traditional approaches. But because the world has
changed
so greatly over the past decade, I think there is now a critical mass
of
researchers and practitioners that recognize the need for new
approaches
to accounting and valuation. These professionals will guide and shape
accounting
and finance through the next decade.
Question 4: In your book you state that the
"last decade has seen the world move decisively from one government by
the economics of scarcity to one governed by the economics of
information." Could you give your reasons for this view and also state
why you think old line companies instead of "tech" companies seem to be
the ones currently moving most quickly upward in the stock market?
Answer: I think a dichotomization into
‘new-economy’ (i.e., ‘tech’) and ‘old-economy’ companies can be
misleading. In fact,
some of the most productive and innovative users of technology are in
what
you might call ‘old-line’ industries – companies like Wal-Mart, GE,
BankOne and Charles Schwab. When you have both scale and technology,
the rewards are multiplied. And it is often the ‘old-economy’ companies
that have sufficient scale to realize the efficiencies from applying
new technology. Thus investors are (rightly) putting their money in
large firms that know how to use technology. These are run by smart
managers in old industries.
There is also
the fact that many stocks in the ‘tech’ sector are still overvalued.
Financial accounting fails to provide credible numbers, and investors
see these as increasingly risky, and thus bid them down. For example,
Bill Gates observed "Our primary assets, which are our software and our
software-development skills, do not show up on the balance sheet at
all. This is probably not very enlightening from a pure accounting
point of view." Indeed virtually none of Microsoft’s assets show up in
their financial statements. Companies with a higher proportion of
tangible assets are better accounted for, and thus seem lest risky. In
the post-Enron world, exposure to the risk of
accounting shenanigans is a significant mover of markets.
What we do see,
though, is a continued rise in labor productivity throughout the US
economy, much of it attributable to successful technology
implementations. Productivity growth is most pronounced in six sectors
– wholesale trade (.37), retail (.34), securities (.25), semiconductors
(.17), computer manufacturing (.12) and telecommunications (.07) – and
these industries are most likely to be rewarded in the markets (the
numbers in parentheses are the contributions to the 2.32% average
annual labor productivity growth over all US industries from 1995 to
1999).
Question 5: You note in your book the
outdated nature of many long established accounting principles. If we
are to move beyond these, what better performance measurement criteria
can you suggest to give today’s investors and managers a firmer grasp
of a company’s performance?
Answer: I would suggest an integrated
methodology specifically designed address the shortcomings of the
600-year old precepts on which GAAP is based, and specifically designed
to take advantage of
the capabilities of modern tools, including (1) computers, which have
been
in development over the past four decades (2) managerial strategy
introduced over the past two decades, (3) Bayesian statistics largely
developed in the 20th century, and (4) engineering, developed over the
19th and 20th centuries. I am in the process of doing this now, and
will release the methodology – which I am tentatively calling Financial
Dynamics – in my upcoming book due out later this year. I have
implemented the methodology in a software package.
The major
advantage of Financial Dynamics over traditional valuation models is
that it provides formal roles for all of the major classes of objective
and subjective information at the analyst’s disposal. Without specific
formal roles for available
information, analysts are driven to ad hocracy – i.e., willy-nilly
incorporation
of information in incomplete or flawed fashion into the limited models
available for computing value.
The classical
example is the failure of GAAP accounting to report anything at all of
risk, variance or unit volume statistics in a transaction flow, let
alone investor and consumer sentiment about the company and its
products. Thus forecasts (and thus financial valuations using forecast
future cash flows and earnings) are likely to exclude most of the
information needed for accuracy. Analysts introduce these after
application of DCF or other valuation approaches, and
then in an ad hoc and usually imprecise way. Such forecasts may or may
not
be inaccurate. But they are likely to be inconsistent, and their
assumptions, accuracy, transparency, and validity are difficult to
ascertain, and probably severely lacking.
Financial
dynamics turns the perspective of traditional accounting for wealth
accumulation on its head. In the agricultural and industrial economies,
the value of a
business was measured by its stored assets minus claims to those
assets. This is implicit in traditional accounting reports that depict
a business in vaguely articulated formal and informal processes that
generate stored wealth (i.e., assets) while using up, via expenses,
some part of the firm’s wealth endowment.
Financial
dynamics (FD) focuses, instead, on the processes that impel the value
flows through the firm. This makes much more sense in the knowledge
economy, where the major (knowledge) assets are difficult to store,
quickly grow obsolete, and because they are ‘non-rival’, may be
impossible to unequivocally own or protect from theft. In the knowledge
economy, value comes from ‘ideas in action’. Knowledge assets possess
negligible value until they are put to work.
In accountings
‘stored wealth’ perspective on corporate value, stocks have played the
central
role in audit and bookkeeping. In Financial Dynamics, stocks, if they
exist
at all, are just another cost of doing business. And usually less is
more, whether we are speaking of inventory, equipment or any other
traditional store of wealth.
The Financial
Dynamics perspective is a ‘value flow’ perspective, thus the valuation
model focuses on transaction flows that reflect the creation of value.
These give us
a time-series model which can both ‘learn’ – i.e. integrate new
objective data – and also make the most of insights, qualitative
knowledge and other sorts of ‘subjective’ data.
Question 6: In your book you note that
there are four major influences on a technology company’s wealth –
technology
acceleration, network externalities, organizational scaling, and
geographical
scaling. Could you briefly define these and use a current example of an
Asian company to demonstrate how they work together?
Answer: There have been four influences
in business which have grown in importance because of the demands for
managing ever more complex technologies. All reflect the way that
production and value-creation scale – over time (technology
acceleration), over space (geographical scaling), over customers
(network externalities), and over employees (organizational scaling).
The added complexity is both the source of competitive advantage, as
well as a catalyst for change.
Advances in
technology force firms to effectively manage complexity as a predicate
to their own survival. Over time, this added knowledge intensity shifts
the balance
of costly resources invested in skill sets, maintaining barriers to
entry, reaching customers, and controlling supply and production.
Management may perceive these changes only as an evolutionary shift in
the cost or availability of particular resources, or as temporary fads
in a fickle marketplace. Over time, the effect can be dramatic, as
particular aspects of business crossover from insignificance to
being critical to the strategy of the company. Crossover occurs
when the cost of a particular resource scales – often in a
highly non-linear fashion. Scaling is the rate at which a
particular cost grows or declines over time, with volume, over
organization size, or with customer base. Four major types of scaling
are dominant in knowledge intensive businesses – (1) intelligence
scaling and knowledge networks,
(2) technology acceleration, (3) geographical scaling, and (4)
organizational scaling. We will describe each of these in turn.
(1)
intelligence scaling and knowledge networks: New wealth is generated
when individuals scale-up their personal intelligence by tapping into a
global network of knowledge. Webster’s dictionary defines a network as
‘a complex, interconnected group or system of storage sites (called
nodes) and transport functions.’ In knowledge networks, an extended
group of people with similar interests or concerns interacts to share
knowledge and experiences. Data communications networks have provided
the most prominent innovations in computers over the past decade. These
networks take digitized knowledge and make it available worldwide. Such
‘intelligence’ sharing has revolutionized the marketplace, created new
sources of wealth, and restructured the character of work.
(2) technology
acceleration: Moore’s Law suggests that the cost effectiveness of new
replacement computers improves exponentially; conversely, our
investments in computing need to be depreciated using an exponential – not
linear – model. The economics of the computer business have
changed to such an extent quantitatively, that they have yielded a
qualitative change in the allocation of costs over time. In practice,
Moore’s Law directly affects accounting for semiconductors and products
that use them. Consider computer manufacturers Dell and Gateway, who
use internal models that completely depreciate inventory over a 3-month
period.
(3)
geographical scaling: Each new technology has the potential to remap
the ‘distances’
between people and places; this in turn demands that firms restructure
the "things" they do to remain competitive. In general, the remapping
enabled
by new information and communications technologies makes the world smaller.
So pronounced has been the effect that it is perhaps more difficult to
measure the shrinkage of the world today than it was even a
decade ago.
The
geographical scaling enabled by communications technologies strongly
impacts fields
that are knowledge intensive. In software, banking, insurance, and
R&D,
the trend is toward globalization, speed and responsiveness, and
greater
information sharing with customers. Globalization also increases the
importance
of government policy and infrastructure investment in finance,
security,
encryption, taxation, censorship, ownership and regulation, and so
forth.
Money and business will go where it is treated well.
(4)
organizational scaling: Global transportation and communication
networks have brought
about fundamental changes in the structure of organizations in three
ways.
First, they have flattened the hierarchy or firms, eliminating vertical
‘stovepipes’ by enabling communication across and around organizational
lines. Firms have become inured to the speed and efficiency of
horizontal
communications. Second, downsizing has culled workers with lower skill
levels
from organizational ranks. Firms increasingly are composed of a small
core
of smart, adaptable employees who can learn to use technology to
greatly
enhance their effectiveness and efficiency. Obtaining such efficiencies
was the focus of much of the reengineering movement in the 1990s.
Finally,
super-efficient market coordination through global networks provide
efficient
market alternatives to internal production.
While not
strictly Asian, Dell Computer sources much if not most of its
components from Asia. In fact it is dependent on the nimble response
Asian suppliers to make
its model work. The nimble response of Asian suppliers, with the well
lubricated logistics for global shipment let Dell benefit from a
significant geographic scaling. Dell provides the ‘network’ that allows
this extended network of producers to communicate with Dell’s
customers, and to share the benefits of Dell’s branding and support.
This network externality has conquered the less developed models of
Dell’s competitors. It’s supply-chain management is built around i2
software with the goal of replacing inventory with information – and
keeping both inventory and employees at a minimum. This has resulted in
a very lean organizational scale which was once only known to the
Japanese auto manufacturers. And the main reason for Dell’s obsession
with inventory control is that procurement costs decline by 1% per week
because of technology acceleration. A 1/10th percent
reduction in inventory levels results in the same profit contribution
as a 10% increase in production efficiency. Dell’s business model
simply would not be competitive without taking advantage of all four
scaling effects.
Question 7: In Chapter 9 of your book you
point out that financial analysts often do much to misstate and often
offer flawed views of how the stock market works for technology
companies. Can you explain your views on this and again take a real
life example in Asia to demonstrate your point?
Answer: Capital markets are not simply
machines for calculating prices; they provide a focus of social,
political and commercial sentiment in the business community. They
provide the source of funds – either debt, equity, or increasingly a
dizzying plethora of hybrids that fit neither one category nor the
other; the mere existence of these markets implies a potential use for
funds that are invested in firm projects – and thus represent an
opportunity cost, and; they provide a nexus for investor sentiment –
one which influences trading behavior, communicates trader sentiment,
and sets investors’ expectations. Thus a valuation based on
fundamentals of the business is only a first step in assessing the
security price for a particular company’s stock. Because of their
social and political role, markets are not necessarily efficient, nor
are they always rational. Investors may play games with available
information, or create information asymmetries for their own benefit.
Even though this behavior may appear ‘irrational’ from a strictly
return maximizing standpoint, there are very predictable mechanisms
that bias prices away from that which would appear in a theoretically
‘efficient’ market. This seemingly ‘inefficient’ or ‘irrational’
behavior often projects itself onto equity market prices.
Consider the
‘rationality’ of the market in the case of Hong Kong high flyer Pacific
Century Cyberworks (PCCW). PCCW, founded in 1999 without products or
business rationale, represents a classic example of a speculative
bubble and the way in which public perception was manipulated in
wholesale fashion to enrich its founders at the expense of others. The
great names of investment banking played their role and the market
completely ‘bought’ the story sold by the scion of one of Hong Kong’s
powerbrokers. PCCW was able to enrich early-round investors by sucking
in later investors or company vendors at higher prices per share. That
is how an equity spiral works – when the last willing investor has
bought in, and the last willing vendor has accepted the paper, then the
bubble bursts. On the 15th of February 2000, PCCW shares closed at
HK$26.35, which turns out to be their record high. PCCW used its
inflated stock to buy Cable & Wireless HKT Ltd, a highly indebted
former monopoly utility companies with media interests and unsuccessful
in adapting to the Internet age. PCCW-HKT shares are now trading at
around $2 a share.
Oddly enough,
since PCCW’s founding in 1999, independent analyst David Webb
(www.webb-site.com) had provided extensive data supporting a fair
value for PCCW stock of not more than $5, a figure which was widely
accepted in the finance community. Yet the public was will to pay more
than five times that much for PCCW shares. So much for market
efficiency.
Question 8: In Chapter 11, you give ten
prescriptions for constructing successful strategies in
knowledge-intensive businesses. Could you explain those and again give
examples from real life for our
readers?
Answer: I suppose these were just more
specific ways of saying ‘keep it simple’ and ‘keep your market focus.’
To quickly reiterate, these ten prescriptions for constructing
successful strategies in knowledge-intensive business are:
- Analyze
your technology choices with two goals – first and foremost, minimize
future uncertainty; second maximize performance.
- Choose
technologies that pay off quickly. Don’t pin down talented people on
low-yield projects.
- Don’t try
to value a technology until you know what you want and why
you need it. You can’t choose your value metric without defining
critical activities and their objectives.
- Choose
technologies that complement and supplement each other – this promotes
organizational learning, and shares support costs across technologies.
A firm is an integrated system of value generating processes, not a
parts list.
- Choose
cheap technologies to support and complement the expensive technologies.
- If there
are two available technologies – one simple, the other complicated –
choose the simple technology.
- Use
everything you know in your business, even if it seems irrelevant. This
helps maintain your
competitive edge. It helps you define marketable technologies in
networked markets with room for only one leader.
- Do
everything you
can in your own facilities with your own employees. Employees need the
experience to learn new technologies. Keep your employees loyal –
competitors
can easily steal knowledge.
- Have
enough employees with expertise in the technologies that you know you
will need.
- Elegant
technology is no substitute for market leadership. Choose technologies
that your customers want; not technologies that your engineers want to
work with.
My choice for the
company that best embodies these strategies is Microsoft, although like
any company, it is far from perfect. One can see how Microsoft balances
R&D with long-term payoffs with the need to keep competitive its
core products, Windows and Office (points 1 and 2). Microsoft, being
market driven, typically has an idea of what it wants when it hits the
market (point 3) and is masterful at linking and leveraging its
complementary strengths (point 4). Though it
may not seem so, Microsoft does tend to favor cheap and simple
technologies (points 5 and 6) but these can get complex in trying to
retain its monopolies. Its R&D with long-term payoff is both a
vehicle for corporate learning, but for finding new twists for existing
products (points 7, 8 and 9). And point 10 ‘elegant technology is no
substitute for market leadership’ – need I say more?
Question 9: Also in the same chapter, you
list strategic questions that every manager should be asking his or
herself. Can you list these and explain just how a complete and
accurate accounting system answers each of them?
Answer: The knowledge economy is one
where power has transitioned to the consumer. These five question are
intended to remind the manager of that fact when setting strategy. Let
me quickly reiterate these questions:
What
is the competitive situation in the marketplace and how does it help or
hurt us?
Where and
how do we fail to be competitive in comparison to other market
participants?
What do
our customers want, and how (and how well) do we provide it?
What are
our key failures in market performance?
What are
the costs (drop in value) of not taking immediate action to address the
first four questions?
‘Completeness’ of
accounting is the relevant concept. Today’s generally accepted
accounting principles (GAAP) include ‘The Entity Concept’ – the concept
that accounting quits at the legal boundary of the firm. The
consequence of such traditions is seen in the Enron debacle – risky
assets and losses were hived off to ‘special purpose entities’ where
they could be kept out of the accounting statements, thus perpetrating
a massive (but perfectly legal) fraud. A complete accounting system
must account for all value or loss generating activities up and down
the value chain. A complete accounting system must fully report the
risk distribution of value or loss generating activities up and down
the value chain. GAAP does neither. Instead it hides behind legal
obfuscations line special purpose entities and uncertain intellectual
property rights in its defense of incomplete reporting. If GAAP were
expanded in such a fashion, then answering these questions for
competitors in a given market would be much simpler and more direct.
With current GAAP accounting, it is essentially impossible.
Question 10: Since the Dot com debacle of
the last several years, have you seen any improvement in the tools of
measurement and analysis that allow investors and managers to better
value and understand their technology investments? Could a similar
meltdown occur in the near future?
Answer: There is considerably more
discussion, but at this point, I have not seen a satisfying improvement
in the quality or comprehensiveness of valuation approaches. The
problem is that valuation has become vastly more complex with the
emergence of so-called knowledge economy firms – firms whose products
and operations revolve around information technology, the Internet, and
other information intensive activities. At the root of this quest for
better ways to track the performance of businesses when investments are
primarily in intangibles such as process knowledge, customer knowledge,
or technical knowledge. Such businesses now contribute over 80% of GDP
in developed economies. They include information technology powerhouses
like Microsoft and Cisco, who are being joined by knowledge firms in
biotechnology such as Pfizer and Pharmacia, and eventually
nanotechnology.
Valuation
approaches for ‘intangibles’ which track assets only as storable
commodities at historical cost misses most of the value creation going
on in the 21st century. For this reason, too, I am uncomfortable with
most of the newer ‘stored wealth’ approaches currently used to value
so-called ‘knowledge capital.’ ‘Stored wealth’ approaches attempt to
classify particular historical costs for patents, software and so
forth. Such approaches are reflected in the software and goodwill
accounting regulated by FASB 86 and FASB 141 and is reflected in
various ‘brand equity’ formularies now popular in marketing. Columnist
and management writer Tom Stewart summarized in his book Intellectual
Capital: The New Wealth of Organizations various definitions of
intellectual capital
– i.e., knowledge, information, intellectual property, experience –
that
can create future wealth. But a ‘stored wealth’ definition of
intellectual capital is, at best, a slippery concept, covering
everything from a patent granted on a new type of gadget to the
personal relationship between a top salesman and his best customer. Yet
this is the most common approach seen for ‘intangibles’ like brand
equity, R&D and so forth.
The real
problem lies in measurement, and in consequence the strategic use of
any derived valuation. The knowledge economy does not see
production in terms of lumps of value (like lumps of gold) that sit
around forever until sold. In contrast, a ‘value flow’ perspective on
valuation makes the intrinsic assumption that information, knowledge
and other intangibles only generates only through application in the
revenue generating activities of the firm. Traditional notions of
discounting future revenue streams to compute value, or matching
expenses to ongoing activities are perfectly applicable in
this scenario.
The process
perspective that I take presumes a clear understanding of how the
particular knowledge assets in which the firm invests can in fact be
used in the future to generate value. Since there is no certainty in
future corporate action, contingent scenarios (such as those addressed
in real options and decision tree valuations) need to be considered in
calculating value.
Question 11: At this point, if I could turn
away from your book to another subject you have often focused on –
global technology policy. Hong Kong, Singapore, Shanghai, Beijing and
Taiwan are all competing to become the focus of technology investment
for the region. Of the many competitors is there any one city or area
that you think stands out as
best understanding the challenge and moving to address it?
Answer: I would have to say Singapore
at this time, followed by Taiwan and Shanghai. Each faces its own
endowments and challenges, so the verdict is still out as to whether
their policies will pay off. I have been disappointed with my home
city, Hong Kong, which has opted to protect its civil service, finance
community and property
developers over more enlightened policies at a time when business is
increasingly
global and virtual.
Question 12: Also, are their particular
Asian companies that you feel best demonstrate an in depth
understanding of technology investment and could be models to others in
the region? Also, could you explain why and give examples?
Answer: I think of the large companies
in the region, that Flextronics in Singapore and Sony and Yamaha in
Japan
are great examples. But all over the region, one can find small and
medium
sized firms that embody the spirit of sound technology investment. It
is
these firms that will grow to be world contenders over the coming
decade.
And it is in the small and medium sized firms that I see Asia’s
greatest
potential for the future.
Question 13: This book – Valuing Technology
– was your second book published in the last two years. Do you
currently
have a new book or project in production and could you tell us a little
about it?
Answer: Thank you for asking. I have
actually outlined several books extending the research in ‘Valuing
Technology.’ I warned in this book that I was unable to offer an
exact system for computing the value of knowledge-intensive companies.
In my next book, tentatively titled ‘Financial Dynamics’ which is due
out this year, I have set as my mission the construction of a
comprehensive system of valuation for businesses whose core
competencies are predicated on knowledge-intensive processes. The book
will be sold with software that implements the methodology.
My goal in
writing ‘Financial Dynamics’ is to accurately assess value in the
technology intensive firms of the knowledge economy, just as historical
cost based accounting was able to in the old agricultural and trading
economies. The goal of
‘Financial Dynamics’ is not just valuation as an end in itself, but
also
to provide tools to move strategy from an ad hoc art form to an
objective,
informed and scientific discipline based on comparative values of
strategies.
The knowledge economy has presents investors and managers with
incredible
challenges, because the tools that we have traditionally used to
measure
performance – accounting metrics – are increasingly divorced from
fiscal
reality.
Strategy in
technology firms has grown complex over the past decade, and managers
have to be much smarter to do it well. They urgently need new tools to
decide how to extract value from new technology. In the context of
these new models, though,
classical tools of valuation – double entry bookkeeping and discounted
cash flow – rely on business models from a simpler era, and produce
results
that may be inaccurate or irrelevant to current strategy. Management
strategy
must be carried out in a market-oriented context of equity capital,
R&D, promotion and delivery. Strategy, in this sense, is a rational
process of deliberate calculation and analysis, designed to maximize
long-term value.
The most
striking change brought about by the increasing complexity of
technology is the
need for more and more investment not directly related to constructing
the revenue generating goods and services of the firm. In extractive
industries
such as mining and petroleum; or in low technology production such as
household consumables, expenses such as R&D, process control,
quality assurance, customization and so forth are minimal. These
‘support activities’ become the major contributors to corporate
expenses in knowledge intensive technology companies. They dwarf the
‘primary activities’ that are directly involved with assembling and
packaging the products that are sold. Software represents an extreme –
it is entirely comprised of fixed costs of supporting activities; the
marginal cost of producing an additional copy of software is
essentially zero, even though there is a positive unit revenue expected
from each sale.
To improve the
breadth and accuracy of valuation tools, I have shifted the focus of
Financial
Dynamics’ valuation to a dynamic, process-based, value flow
orientation;
away from the classical ‘stored wealth’ perspective. This allows a more
accurate and objective basis for forecasting future earnings and cash
flows,
and thus fits better with modern ‘discounting’ to obtain firm, project
and
asset valuation. It should also improve the accuracy of older
approaches
like discounted cash flow which try to artificially graft concepts of
intertemporal economies, discounting and contingent commodities onto a
centuries old framework of ‘stored wealth.’
