Intangible investments, tangible wealth

In the intangible economy, wealth is still mostly tangible and rising equity and real estate values are drivers of increased global wealth – not savings and investment.

Late last year McKinsey Global Institute (MGI) put out a report on The rise and rise of the global balance sheet: How productively are we using our wealth? which revealed an interesting feature of the intangible economy: while investment is increasingly in intangibles, wealth is overwhelmingly tangible. Intangible account for only 4% of real global assets as of 2020. Real estate (land and structures) account for 68%. The remainder is made up of other tangible assets such as infrastructure, machinery & equipment, and inventory.

Looking more broadly at the global balance sheet, the value of these real (aka non-financial) assets account for roughly a third of total global assets. The other two-thirds of wealth are financial assets held by financial corporations (the financial sector) and financial assets held by households, governments, and nonfinancial corporations (the financial system). Analysis of the growth in these global assets reveals a worrisome fact. Over the past two decades asset growth has been largely due to rising prices (valuation) for equities and real estate. Increased savings and investment account for just over a quarter in wealth creation.

I have two take-ways from this report. My main take-away is about the difficulty of measuring the value of intangible assets as assets. The report uses data from existing System of National Accounts framework. In the US data, the only intangibles included are intellectual property products which include only software, research & development, and entertainment, literary & artistic originals.

It should be noted that the authors of the report are well aware of the importance of intangibles as a factor in production (see MGI report Getting tangible about intangibles: The future of growth and productivity?.  For comparability’s sake they used the globally accepted framework.

However, as part of their sensitivity analysis, they modified the treatment of intangibles. They first expanded the list to include additional intangibles from the INTAN-Invest project database such as organizational capital, training, and brand investments. Adding these doubles the value of intangibles. Next, they removing the standard accounting practice of depreciating IP on a 5-year schedule. This quadruples the value of intangibles.

Admittedly, these modifications result in only minor changes in the relative size of intangible assets compared with total. But they do illustrate the difficulty in using intangibles as a store of value.

[Note there are other frameworks as well. For example, World Bank’s Changing Wealth of Nations series https://www.worldbank.org/en/publication/changing-wealth-of-nations includes human and natural capital in its analysis. It should be pointed out however that measuring human capital and natural capital is a work in progress.]

My second take-away is more of a macroeconomic concern about the relatively small contribution of saving and investment to overall wealth creation. To the extent that additional wealth created by rising asset prices is channeled back into the economy in the form of savings and investment, this can be a positive spur to economic growth. However, this is not necessarily what happens. As the report states, the process could “encourage investors to seek asset price increases rather than more traditional benefits from operating assets.” In other words, create an asset bubble.

The report discusses to role of low real interest rates, among other factors, in fostering this situation. If we are moving to an era of higher interest rates (as it appears that we are), the future growth of the economy may be more fragile than we thought.

For this, and other, reasons, the report concludes that we need to find “alternative long-term stores of value.” However, it also lays out the case as to why it is difficult for intangibles to play that role:

“Although intangibles have attracted plenty of investment, they have not served as a long-term store of value at scale. Measured using current assumptions for their value rather than the broader societal value they might bring, they constitute only a tiny part of total net worth. But these assumptions and the amount of private value intangibles can hold depend on the economic and competitive context. Most intangibles can be scaled at near zero marginal cost and are not “used up” in production. That means the returns on intangibles investments can flow to a variety of stakeholders. At one extreme, if competition is strong and IP protection light, all value of intangibles investment will quickly pass to consumers as customer surplus, increasing real income and standards of living for all but not serving as a long-term store of value for those making the investment. At the other extreme, the policy and competitive environment could allow companies investing in intangibles to protect—and scale—the value of those investments ad infinitum, through IP protection, protection of trade secrets, sustained advantages of scale, barriers to entry, or not containing monopoly power. In such a setting, intangibles investments could become long-term stores of value for savers and increase the value of their investments over time, but at the expense of competition and consumers. What policy mix is needed to extract more value and return from intangibles investment and yet also preserve customer surplus and strong competition? And what might then be the right way to measure intangibles at a company and societal level?”

For all these reasons, I am beginning to believe that we need to modify our view intangibles. We need view intangibles as an “asset” in the sense of something useful (using the Merriam-Webster’s definition of an asset as an advantage or a resource) – not an asset as in a store of value. In other words, focus on intangibles as input to the production process. As such, we need to focus measurement on investment metrics, rather than valuations.

More on this to come.

BEA data shows strong growth in knowledge-related business investment in 4Q 2021

Growth was led by increased investment in information processing equipment but all other nonresidential fixed private investment actually declined, with investment in transportation equipment taking a big hit.

This morning’s numbers for US GDP for the 4th quarter of 2021 and-year-2021-advance-estimate are looking good. According to BEA, GDP rose at an annual rate of 6.9% in 4Q and by 5.7% for the year.

Business (non-residential fixed) investment in knowledge-related areas grew at an annual rate of 14.2%. This grow was due to a 22.7% increase in information processing equipment (which had declined in the previous two quarters). Investment in software was up by an annual rate of 12.2% and R&D spending up by 6.5%.

Total business investment in all other areas declined by an annual rate of 14.6% — driven in large part by a drop in investment in transportation equipment of 45.3%. Investments in non-residential structures and in “other equipment” were down by 11.9% and 11.7% respectively. Investments in non-residential structures have declined in 8 of the past 9 quarters (1Q 2021 being the one exception). The continuing declines in investments in non-residential structures and transportation equipment are especially worrisome.

In my earlier posting on 3Q 2021 I expressed concern that the decline in investment in information processing equipment in 2Q 2021 and 3Q 2021 may be a reflection of the ongoing semiconductor shortage. Hopefully the rise in investment in information processing equipment in 4Q 2021 is due to steps to alleviate that shortage.

As I also noted in last quarter’s posting, knowledge related business investments did not suffer as great a cutback as other business investments in the COVID-19 slowdown and have been growing since 2Q20. They now account for 59% of total business investment (up from 50% in 3Q19). Looking at only the two digital-related investments of information processing equipment and software, this subcategory makes up 42% of business investments.

[Note: I define knowledge-related investment as the combination of investment in Information Processing Equipment, R&D, and Software. The first of these three categories is reported in the GDP data as a subcategory of Non-residential Fixed Investment: Equipment. The latter two are reported as subcategories of Non-residential Fixed Investment: Intellectual Property Products.]

Intangible assets v. intangible assets

We generally think of intangible assets in discreet categories. Depending on which framework you choose, these include worker skills and know-how, innovative work organizations, business methods, brands, and formal intellectual property, such as patents and copyrights (see my earlier paper Intangible Assets as a Framework for Sustainable Value Creation). Increasing we see descriptions and analysis of asset complementarities and the interactions among intangibles. For example, there are clearly synergies among knowledge creation, human capital (workers skills), and organizational features and capabilities.

However, there are times when the development of different intangible assets can be at odds with one another. The following insight on enforcement of patents from Stephen Miller (What Do Patents Mean? in Issue in Science and Technology) is a case in point:

“Another reason a company may take no action against a likely infringer is that the company already has an existing or potential relationship with the infringing company, often in another sector or sectors of business, as a partner, a customer, or a supplier. If the real or perceived value of that relationship is greater than the estimated value of the invention, which in its early stages is usually quite uncertain, then the patenting company may choose not to go after the infringer. I saw this happen at a time when my company was negotiating a business deal with another company that I was confident had been infringing one of my patents. Our management decided the value of the deal being negotiated was greater than the value of the technology under my patent, so they refused to try to enforce it.”

So, the goal of maintaining relational capital was in conflict with the protection of intellectual property (and ultimately with the R&D investments made to produce that intellectual property). Are there any other examples where intangibles might work at cross-purposes?

By the way, Miller’s article is a straightforward discussion of how patenting works in the real world. If you want to understand How companies really use patenting and (one of my pet peeves) why patents are problematic indictors of innovation, read this article.

December employment growth slows in intangible producing industries

Employment growth slowed in December according to the BLS data released this morning.  Nonfarm payrolls were up by only 199,000 employees, compared to 249,000 in November. By contrast, employment grew by 648,000 in October, 379,000 in September and 483,000 in August.

Both tangible and intangible producing industries grew by lower amount in December but the slowdown was more pronounced in intangible producing industries. Employment in intangible-producing industries grew by just 58,100 – a marked decline from November’s disappointing increase of 97,400. This compares to increases of 187,500 in October, 132,800 in September and 310,800 in August. Employment in tangible-producing industries was up by 140,800 in December, close to the 155,900 increase in November.

The biggest slowdown was in intangible Professional and Business Services, which grew by only 34,400 in December compared to 61,500 in November and 112,800 in October. Arts, Entertainment, and Recreation also saw a sharp decline in employment growth, rising by only 7,000 compared to growth of 10,200 in November. The sector had been growing at an average rate of 54,000 in the 3rd quarter of 2021 and a much higher rate than that earlier in the year.

The bright spot in the tangible producing industries was in Accommodation and Food Services, which grew by 52,600 in December compared to only 31,000 in November. Employment in this industry is very volatile however. For example, it grew by 352,400 in July but only 7,500 in August.

As I have noted in earlier postings, the labor market seems to have settled back into the post-Great Recession, pre-pandemic pattern of relatively equal growth in tangible-producing versus intangible-producing industries – but at a slower rate. The COVID-19 pandemic has done little to disrupt to dramatic shift in the tangible-intangible structural balance that emerged after the Great Recession.

For more on the categories, see my explanation of the methodology in an earlier posting https://intangibleeconomy.wordpress.com/2020/06/11/which-jobs-got-hit-in-the-covid-crash-tangible-versus-intangible/

November employment growth slows in both tangible and intangible industries

Employment growth slowed in November according to the BLS data released this morning. Nonfarm payrolls were up by only 210,000 employees, compared to 546,000 in October and 379,000 in September.

Employment rose in both intangible-producing and tangible-producing industries at a slower pace than in previous months. Employment in intangible-producing industries grew by just 91,300 while employment in tangible-producing industries was up by only 118,200. This compares to increases of around half a million in both tangible-producing and intangible-producing industries during the past summer.

Interestingly employment in the tangible portions of the education and health care sectors (Nursing & Residential Care Facilities and Child Day Care Services) actually declined while employment in the intangible portions increased (but at a slower rate). Employment in Personal & Laundry Services, Telecommunications, and Government also declined. One of the few industries to see an increase in employment compared to last month was Tangible business services, due to higher than last month’s employment in Services to Building & Dwellings and the Postal Service.

As I have noted in earlier postings, the labor market seems to have settled back into the post-Great Recession, pre-pandemic pattern of relatively equal growth in tangible-producing versus intangible-producing industries – but at a slower rate. The COVID-19 pandemic has done little to disrupt to dramatic shift in the tangible-intangible structural balance that emerged after the Great Recession.

For more on the categories, see my explanation of the methodology in an earlier posting https://intangibleeconomy.wordpress.com/2020/06/11/which-jobs-got-hit-in-the-covid-crash-tangible-versus-intangible/

Overall knowledge-related business investment continued to grow in 3Q 2021

But the semiconductor shortage may be creating problems for investment in information processing equipment

As BEA’s data released yesterday showed, GDP growth in the 3rd quarter of 2021 came in at a disappointing 2% annual rate. This was well below the 6.5% growth rate of the previous quarter and below general expectations. However, business (non-residential fixed) investment in knowledge-related areas grew by 5.7%. This grow was due to healthy increases in investment software (up by almost 15%) and R&D spending (up by over 9%). Investment in information processing equipment unfortunately declined by 6%. Total business investment in all other areas declined by 3.5%.

The decline in investment in information processing equipment is especially worrisome. This marks the second quarter in a row of declines following four earlier quarters of growth. This may be a reflection of the ongoing semiconductor shortage.

Another casualty of the computer chip shortage is the auto industry. Both expenditure on motor vehicles and parts and investment in transportation equipment dropped dramatically in the 3rd quarter. That decline accounts for much of the overall slow growth in GDP. If motor vehicle expenditures had simply stayed at the 2Q level, the overall GDP growth rate would have been double, at a respectable 4%.  

Knowledge related business investments did not suffer as great a cutback as other business investments in the COVID-19 slowdown and have been growing since 2Q20. They now account for 58% of total business investment (up from 50% in 3Q19). Looking at only the two digital-related investments of information processing equipment and software, this subcategory makes up 40% of business investments.

[Note: I define knowledge-related investment as the combination of investment in Information Processing Equipment, R&D, and Software. The first of these three categories is reported in the GDP data as a subcategory of Non-residential Fixed Investment: Equipment. The latter two are reported as subcategories of Non-residential Fixed Investment: Intellectual Property Products.]

Lessons from agriculture on going beyond technological innovation

One does not normally think of technological innovation and agriculture. But I recently came across an article in PwC’s Strategy & Business on “The fourth industrial revolution in agriculture” from a couple of years ago. The authors, Sebastiaan Nijhuis and Iris Herrmann, describe how technologically sophisticated agriculture has become and how agribusiness is going about implementing new technologies. These technologies range from AI to track and better manage cows for more efficient milk production to the use of drones and IoT sensors to improve crop yields.

https://www.strategy-business.com/article/The-fourth-industrial-revolution-in-agriculture

However, what really struck me about the article was not the new technologies. Rather it was their argument on the need for organizational and strategic change to better utilize the technologies. And, in turn on how the development of these technologies will force those changes in ways we might not expect. For example:

“One firm is developing a swarm of miniature autonomous robots that can plant seeds. Controlled by a farmer’s handheld tablet, which is operated with the help of satellites and cloud-based software, the swarm will be able to put each seed in the right place with greater precision than current approaches can. Not incidentally, the technology will eliminate the need for planter bars, tractors, and tractor operators.”

They go on to note that:

“The most common response of companies has been to plug new technology into old business models, with the hope of enhancing those models with smarter tools and more data. But that tactic is flawed. Making old models work better isn’t enough — not when technologies are enabling all-new models that can render the old ones obsolete.

Many pesticide and fertilizer companies, for example, are using 4IR [4th Industrial Revolution] technologies to provide better products and roll them out faster than before. That might sound like a success story, but precision farming — which uses IoT sensors, high-resolution 3D aerial imagery from drones, and AI-powered analytics to analyze the characteristics of soil and the behavior of crops down to the square inch — may soon significantly reduce the need for fertilizers and pesticides altogether.

A better approach for those manufacturing companies is to discover and develop these new business models, creating new markets along the way. Instead of looking for a better product, companies should look for better solutions for the problems that their customers face, whether those customers are farmers, agricultural suppliers, or end consumers. Many successful solutions will bring together products and services from multiple companies, rather than just using products manufactured by the solution provider.”

Good advice in general – not just for agribusiness.

More on disclosure of human capital data

One of the most important policy steps the US could take to heighten awareness of intangible assets is to require companies to include them in companies’ financial statements (see earlier postings). In a speech given earlier this summer, SEC Chairman Gary Gensler reiterated his support for enhanced disclosure by companies of their human capital:

Further, investors have said that they want to better understand one of the most critical assets of a company: its people. To that end, I’ve asked staff to propose recommendations for the Commission’s consideration on human capital disclosure.

This builds on past agency work and could include a number of metrics, such as workforce turnover, skills and development training, compensation, benefits, workforce demographics including diversity, and health and safety.

Disclosure helps companies raise money. It helps the efficient allocation of capital across the market. And it helps investors place their money in the companies that fit their investing needs.

As the SEC works through its process, it is important to understand what companies are already doing. A new study out from the analytics organization JUST Capital (The Current State of Human Capital Disclosure in Corporate America: Assessing What Data Large U.S. Employers Share) provides some helpful insights.

The report identifies 35 human capital metrics (28 of which they were able to collect data). The metrics cover six themes: employment and labor type; job stability; wages, compensation, and benefits; workforce diversity, equity, and inclusion; occupational health and safety; and, training and education. The specific metrics are very detailed. For example, the employment and labor type theme includes not only the number of employees but the number of on-site contractors and on-site temporary or seasonal workers. The job stability theme includes the amount of voluntary turnover by gender and race/ethnicity. The wages theme includes the minimum wage to local minimum wage ratio.

Their analysis of the data collect from 100 of the largest U.S. companies shows why SEC action is needed. To start with, disclosure of human capital data is low. The disclosure rate is below 20% for the majority of metrics. The most commonly disclosed metric was the number of full time employees; even there the disclosure rate was below 40%.

And even then when the data is disclosed, it is likely to be included in a Corporate Social Responsibility Report, Sustainability Report or other Impact Report rather than in the company’s financial report (10-K). As important as these reports are, the study points out that they are optional publications with no set standards for reporting and no auditing requirements. Thus, they are difficult to use to make comparisons across companies and may lack accountability.

The report explains why this lack of data standardization matters: “Without the ability to compare how companies are performing on various human capital metrics, investors can’t make well-informed decisions about where to direct their holdings, potential hires can’t factor a company’s treatment of workers into their employment choices, and customers can’t shift their purchasing practices to support companies leading the way.”

Likewise, the same need for comparability is the reason for why such data disclosure must be mandatory. I understand that some object to increased mandatory reporting, arguing that it gives away important information to competitors. Remember that there was a time when the disclosure of even basic financial data such as revenues, expenses and profits was opposed on the grounds it was proprietary. But as I noted back in 2005 in our paper on Reporting Intangibles, without such information investors and others are flying blind.

Managers also need better data. The JUST Capital study l0oked at public disclosure of human capital metrics. I wonder how many companies don’t even collect such data. Mandatory disclosure may force companies to do what they should be doing anyway: collecting data to better understand and manage their intangible assets including human capital.

So, the sooner the SEC moves to requiring more disclosure of data on human capital, the better. And thanks to JUST Capital for continuing to push on this topic.

Importance of local assets

Over the years, one of the leading themes of the Intangible Economy has been the need for communities to build upon the local assets. So, I am always on the lookout for interesting examples.

One such example comes from Sparta, Greece. Petros Doukas, the Mayor of Sparta, describes what they are doing to build on local assets. They are deliberately not trying to become a “high tech” center. Instead, they are looking at areas where they have some type of existing advantage and have identified the sectors of agriculture, tourism, cultural activities, and sports. You can see his remarks describing what they are doing in each of these areas at this YouTube video starting at about minute 16:15

[FYI – This clip is part of an excellent discussion on local development as part of the Framing the Future series organized by the Global Federation of Competitiveness Councils (GFCC) (click here to see the links to previous sessions).]

Sparta is an example of the economic gardening approach to local development. And as I pointed out in an earlier posting (“A New Narrative for Rural America”, Knowledge Management as an Economic Development Strategy and “Building on Local Information Assets”), communities following this strategy adopt a “build, not buy” approach to growing local businesses. 

That is not to say that efforts to create technology and innovation clusters are not important. They are. But as Mayor Doukas points out, many communities would be better off adopting a lower tech strategy. In any event, deciding which way to go starts with understanding your local assets.

Thinking about manufacturing and services

One of the ongoing themes of my work has been the restructuring of the economy including the fusion of manufacturing and services. I have long argued that these categories are not useful in helping to understand economic activity. There are some cases where the categories are clear. For example, haircuts are clearly a service. But increasingly the boundaries are fuzzy. So-called manufacturing companies are more and more selling their products as a service and service activities are an increasing part of value-added.

And sometimes, services want to be seen as manufacturers. A story in today’s New York Times on the public-private revolving door for tax lawyers and accountants reminded me of how far and how creatively services can be considered “manufacturing.” Before it was repealed in 2017, Section 199 of the tax code provided a tax deduction for “domestic production” aka manufacturing. While revenues from retail food preparation were explicitly not allowed to take the deduction, creative interpretations of “production” were accepted including the notorious cheesecake-slicing-as-production claim mentioned in the Times story. And there was a florist who claimed the manufacturing deduction as they were using individual flowers to produce bouquets.

Interestingly, the law specifically included engineering and architectural services as qualifying activities. I assume these services were seen as important adjuncts to construction (itself a qualifying production activity).

I should note that the opposite classification of construction as services or manufacturing is used by the Institute of Supply Managers, which includes construction in its services index. I suspect that this is a legacy of the original formulation of this as the index of non-manufacturing, as opposed to their index of manufacturing (see earlier posting).

These stories about manufacturing versus services should give us pause. Admittedly, the cheesecake example is somewhat silly (of course not to those who got the tax break). But if assembling a car from various parts is considered manufacturing, isn’t assembling a bouquet from various parts also? If testing a computer chip is considered part of the manufacturing process, what about chip design services? And then there is the thorny question of these activities being carried out by outside firms (considered a service) rather than in-house (considered part of manufacturing).

We need a serious effort to rethink how we envision the economy. Part of that is embracing the idea of making value as opposed to making things (see earlier posting). But it also includes restructuring our industrial categories – possibly around types of end output (e.g., food, shelter, transportation, health, entertainment, etc.). All of the recent discussions about supply chains indicates how interconnected economic activities are and how these activities cluster into groups.

I’m not smart enough to come up with the best framework. I hope someone is. Otherwise, we will continue to make economic policy based on a view that is clearly out of date.