As I anticipated in an earlier posting, today the BEA revised its estimate of 4Q GDP. What I got completely wrong was the direction — my bad. GDP grew by 5.9% — revised upward from the earlier estimate of 5.7%. I had thought the number would have been revised downward because of the worse than expected trade data. As it turned out, upward revisions in private inventory investment and nonresidential fixed investment were more than enough to overcome any downward revision due to the increased trade deficit and the lower than expected consumer spending.
So, I take it back — the economy really was doing well in the 4th quarter of last year. Let’s see if we can sustain that growth and if we see an improvement in the employment numbers.
By the way, I will make another prediction: don’t read too much in to next week’s employment data. The survey was taken in the middle of the snow storms which may skew the data.
A story in today’s Wall Street Journal (In Italy’s Mills, a New Spin) on the fashion industry highlights the role of manufacturing in an intangible-intensive, innovation-driven economy.
“If we lose the Italian mills, we lose the creativity needed for fashion,” says Sal Giardina, an adjunct professor of textiles at New York’s Fashion Institute of Technology. “Fabrics are the common denominator of fashion. From birth to death, we are never more than three feet away from a textile product.”
Much has been said about this high value-added strategy. As I have noted before, manufacturing is an intellectual capital dependent activity. A key part of that IC is the supply-chain relationship. The need to have production and design closely linked is something that a number of technology industries re-learn every few years. As the article illustrates, it is important in any industry with short product life cycles — such as fashion.
The article also points outs the countervailing forces:
Yet consumers have been demanding cheaper clothes, and one way retailers have achieved these improvements is by pressuring apparel manufacturers to lower prices by more than 20% for each of the past two seasons. Many have done so by moving more production to China, Sri Lanka, Thailand and other low-labor-cost regions of the world.
How these two forces play out will determine the fate of many industries — and the fate of many national economies.
Here is a quick take on three interrelated items worth reading:
Greg Tassey’s paper Rationales and mechanisms for revitalizing US
manufacturing R&D strategies outlines the importance of manufacturing to a technology-based economy and a new economic framework for policy.
The Geography of Innovation describes the role of regional innovation clusters and how to promote them.
The Power of Place 2.0 summarizes 10 policy ideas for “creating jobs, improving technology commercialization, and building communities of innovation.”
All three are built on the central concept that innovation and intangibles (including knowledge) drive economic growth — the concept that also is at the core of Athena Alliance and our notion of the I-Cubed Economy.
Gary Pisano of the Harvard Business School has a new working paper on
The Evolution of Science-Based Business: Innovating How We Innovate. First of all, Pisano differentiates between technology-based and science-based businesses. Technology-based businesses, like software and electronics, develop and apply existing science. Science-based businesses, such as biotech, must engage in developing new science. That difference makes science-based businesses far more risky – since the science may or may not pan out:
Science‐based businesses are at the frontier of knowledge. Technical failure is the norm, not the exception. What is known pales in comparison to what remains to be discovered.
. . .
Thus, not only might the financial costs of exploration be high, but critical technical uncertainties may not be easily or quickly resolvable early in the development process. And, even if an organization can resolve those uncertainties through research, there is no guarantee the resulting intellectual property will be appropriable. “Deeper understanding” may be critical to further development, but it is generally not patentable.
That fact of “science” limits how such science-based businesses can raise capital. After discussing the limits of venture capital and capital markets, he offers this discussion of IP monetization:
An alternative or complementary strategy for a firm to raise capital for its R&D is to “monetize” its intellectual property. That is, rather than trying to develop a whole product and earning revenues on product sales, the company essentially licenses out the project to another firm. Such licensing has become a huge part of the R&D world in most technology intensive industries. There are literally thousands of R&D agreements and licensing deals that occur every year. One of the chief benefits of intellectual property monetization is that it enables firms to manage risks. It also enables firms with complementary capabilities to access know‐how.
Monetization of intellectual property is not a new phenomenon. Firms have licensed intellectual property for more than a century. However, the extent of this IP monetization appears to have grown dramatically in the last few decades. Since science‐based businesses rest on intellectual capital, it stands to reason that markets for know‐how will play an ever more important role in the future. However, we must also understand that monetization of IP has limits as a device for creating the required integration.
Market mechanisms work best when the relevant “modules” of knowledge are clearly defined. Thus, modularity facilitates collaboration (Teece 1982). This is one reason Open Source projects like Linux have been so successful. The modular architecture of Linux enables thousands of software developers from around the world to make contributions without ever having to talk to each other directly or to meet face to face. The IP monetization approach is often predicated on an assumption that the IP in question is a discrete module or asset that can be bought and sold. However, as mentioned earlier, in science‐based contexts, the immaturity of the underlying knowledge base makes it less likely for modularity to exist. This suggests that achieving the required integration through licensing and the market for‐ know will fall short in science‐based contexts.
I’m not sure he has completely grasped the role of IP monetization. In some industries, such as electronics, the licensing process is one of integrating modules. But in biotech, the process seems to have two other roles: division of labor and capital formation. The division of labor function of licensing spreads the work among several organizations, specifically between the new drug development and approval process and the production and marketing processes. Licensing (and sale) of biotech IP also functions in the timeless manner of swapping long term revenues for upfront capital. Licensing and other forms of IP monetization use the revenues from the previous science-based success to fund the next scientific gamble. Thus, it may be perfectly suited to the high risk nature of these types of businesses.
Ultimately Pisano argues that these science-based endeavors require new organizational models — based on a view from Alfred Chandler that “it is hard to think about technological innovation as anything but tightly intertwined with organizational and institutional innovation.” As he notes:
Science‐based businesses in biotech and elsewhere have ‘borrowed’ many elements of organizational technology (venture capital financing, use of the public equity markets for liquidity, monetization of intellectual property, etc.) that have been used, often successfully, in other technology contexts such as electronics and software. However, as argued above, science‐based sectors create novel organizational challenges around the simultaneous need to manage risk, integrate cross knowledge bases, and leverage cumulative learning. Addressing these challenges calls for new “organizational technology.”
Here I would completely agree. But I would not limit the observation to only science-based businesses. Most innovation-based businesses (whether new science-based, based on existing science, or non-technological) face the same three challenges of risk, multiple knowledge bases, and learning. We can look to science-based businesses for clues to the emerging organizational models. But those models, I would argue, will end up being widely applicable in the I-Cubed Economy.
Here is an interesting excerpt from the UK’s Ministry of Defense look at the future: Global Strategic Trends Out to 2040:
Success in future conflict, especially against adaptive and agile adversaries, will require a shift away from kinetic to influence activity, underpinned by a greater understanding of the enemy. This understanding will require more emphasis on intelligence gathering, cultural awareness, individual and collective training, and focused comprehensive approaches.
By “kinetic”, they mean firepower. In other words, the old industrial age method of warfare — which General Nathan Bedford Forrest characterized as “Get there firstest, with the mostest” — is giving way to an intangible based model.
And speaking of financial innovations, here is an example of a recent one — created by the government. David Wessel’s column in the Wall Street Journal (A Stimulus ’09 Success Story) explains how this innovation in state and local financing came about:
In 2009, the driving force wasn’t fairness or tax reform. It was an emergency. The bond market was closed to most cities and states. Many institutional investors weren’t buying, and firms that had been insuring shaky municipal borrowers were imploding. An urgent need to draw new investors to buy muni bonds gave birth to the taxable, federally subsidized “Build America Bonds.”
The experiment worked. It helped revive the muni-bond market, keeping local construction projects going. Last year, $64 billion in Build America Bonds were issued in 45 states, about 20% of all muni offerings; this year will be bigger.
Wall Street and U.S. Treasury estimates show that, after the federal subsidy, muni issuers of Build America Bonds save between one-quarter and one-half percentage point on borrowing costs versus issuing tax-exempts. That’s $1.25 million and $2.5 million annually on a $500 million bond issue. New York’s Metropolitan Transportation Authority figures it saved $46 million over the life of a $750 million Build America Bond issued last spring.
The result is not just a revitalization of the muni bond market but a shift in the market toward a type of financial product that everyone seems to think is a better way to finance state and local governments. As Wessel notes, “Sometimes, the system works.”
Amen to that.