Disclaimer: I am now retired, and am therefore no longer
an expert on anything. This blog post
presents only my opinions, and anything in it should not be relied on.
In my view, Haskel/Westlake’s “Capitalism Without Capital”
is not so much an argument that the increasing importance of “intangible assets”
constitutes a new and different “intangible economy”,
as strong evidence that the ever-increasing impact of software means that a
fundamental idea of economics – that everything
can be modeled as a mass of single-product manufacturers and industries – is
farther and farther from the real world.
As a result, I would argue, measures of the economy and our well-being
based on those assumptions are increasingly distorted. And we need to do more than tweak our
accounting to reflect this “brave new world”.
First, my own brief “summary” of what Haskel/Westlake say. They start by asserting that present-day
accounting does not count intangible company investments like software during
development, innovation property such as patents and R&D, and “economic
competencies” such as training, branding, and business-process research. In the case of software development, for
example, instead of inventory that is capitalized and whose value is represented
at cost until sold, we typically have expenses but no capitalized value right
up until the software is released and sold.
A software company, therefore, with its continual development cycle,
appears to have zero return on investment on a lot of its product portfolio.
Haskel/Westlake go on to argue that a lot of newer companies
are more and more like software companies, in that they predominantly depend on
these “intangible assets.” The new breed
of company, they say, has key new features:
1.
“sunk costs” – that is, you can’t resell
development, research, or branding to get at its monetary value to you.
2.
“spillovers” – it is exceptionally easy for
others to use your development-process insights and research.
3.
“scalability” – it requires relatively little
effort and cost to scale usage of these intangible assets from a thousand to a
million to a billion end users.
4.
“synergies” – research in various areas,
software infrastructure, and business-process skills complement each other, so
that the whole is more than the sum of the value-added of the parts.
5.
“uncertainty” – compared to, say, a steel
manufacturing firm, the software company has far more potential upside from its
investments, and often far more potential downside.
6.
“contestedness” – such a company faces much
greater competition for control of its assets, particularly since they are so
easy to use by others.
Finally, Haskel/Westlake say that, given their assumption
that “intangible companies” make up a significant and growing part of the
global economy, they already have significant impacts on that economy in
particular areas:
·
“Secular stagnation” over the last decade is
partially ascribed to the increasing undervaluing of these companies’ “intangible
assets”.
·
Intangible companies increase income inequality
because they function best with physical communication by specialized managers in
cities.
·
Intangible companies are under-funded, because
banks are not well suited to investing without physical capital to repossess and
resell. Haskel/Westlake suggests that
greater use of equity rather than loans is required, and may be gotten from
institutional investors and by funding collaborating universities.
·
Avoiding too much failure will require new
business practices as well as new government encouragement, e.g., via better
support for in-business control of key intangible assets (clear
intangible-asset ownership rules) or supporting the new methods of financing
the “intangible companies.”
It’s the Software, Sirs
Let’s look at it a different way. Today’s theories of economics grew out of a
time (1750-1850) when large-scale manufacturing was on the rise, and its
microeconomics reflects that, as does the fact that data on economic
performance (e.g., income) comes from surveys of businesses, which is then “adjusted”
to try to include non-business data (trade and reconciling with personal income
reports). From 1750-about 1960, manufacturing
continued to increase as a percentage of overall economic activity and
employment, at the expense of farming.
From 1960 or so, “services” (ranging from hospitals to concierges) began
to carve into that dominance, but all those services, in terms of jobs, could
still be cast in the mold of “corporation that is mostly workers producing/dealing
with customers, plus physical infrastructure/capital”.
Now consider today’s typical large software-driven
company. Gone is the distinction between
line and staff. Manufacturing has shrunk
dramatically as a share of economic activity, both within the corporation and
overall. Bricks and mortar is
shrinking. Jobs are much more things
like developers (development Is not manufacturing nor engineering but applied
math), marketers/branders, data scientists (in my mind, a kind of developer),
help desk, Internet presence support.
The increased popularity of “business agility” goes along with shorter
careers at a particular company, outsourcing, intra-business “services” that
are primarily software (“platform as a service”, Salesforce.com). Success is defined as control over an
Internet/smartphone software-related bottleneck like goods-ordering (Amazon),
advertising (Google), or “apps” (Apple).
Now consider what people are buying from these
software-driven firms. I would argue
that it differs in two fundamental ways from “manufacturing” and old-style “services”:
1.
What is bought is more abstract, and therefore
applicable to a much wider range of products.
You don’t just buy a restaurant meal; you buy a restaurant-finding
app. You don’t just browse for books;
you browse across media. What you are
selling is not a widget or a sweater, as in economics textbooks, but information
or an app.
2.
You can divide up the purposes of buying into
(a) Do (to get something done); (b) Socialize/Communicate,
as in Facebook and Pinterest; and (c) Learn/Create, as in video gaming and blog
monetization. The last two of these are
really unlike the old manufacturing/services model, and their share of business
output has already increased to a significant level. Of course, most if not all software-driven
companies derive their revenues from a mix of all three.
The result of all this, in economic terms, is complexity,
superficially masked by the increased efficiency. Complexity for the customer, who narrows his or
her gaze to fewer companies after a while.
Complexity for the business, whose path to success is no longer as clear
as cutting costs amid stable strategies – so the company typically goes on
cutting costs and hiring and firing faster or outsourcing more in default of an
alternative. Complexity for the
regulator, whose ability to predict and control what is going on is undercut by
such fast-arriving devices as “shadow banking”, information monopolies, and
patent trolling.
In other words, what I am arguing for is a possible
rethinking of macroeconomics in terms of different microeconomic foundations,
not the ones of behavioral economics, necessarily, but rather starting from the
viewpoint “what is really going on inside the typical software-driven corporation”
and then asking how such a changed internal world will reflect back to the
overall economy, how macroeconomic data can capture what is going on, and how
one can use the new data to regulate and anticipate future problems better.
John LeCarre once said that the key problem post-Cold-War
was how to handle the “wrecking infant” – here he was referencing an amoral
businessman creating Third-World havoc, although you can translate that to the
situation in the US right now. The
software-driven business, in terms of awareness of what to do, is a bit of a wrecking
infant. If it isn’t helped to grow up,
the fault will not lie solely in our inability to anticipate the distorting
rise of intangible assets, its side-effect, but also in our failure to deal
adequately with its abstraction, new forms of organization and revenue, and
complexity.
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