SEC Requires New Human Capital Disclosures

I have long advocated for greater disclosure of information on intangible assets in company financial reports. Specifically, the MD&A (Management Discussion and Analysis) section of SEC-required financial statements should require more qualitative disclosure of intangibles. This would allow for more information on intangibles while sidestepping the difficult problem of assigning a financial value to the asset.

Earlier this year, the SEC took a major step forward in that direction by finalizing a rule amending Regulation S-K to require disclosure of information on a company’s human capital. [It should be noted that this new rule, which took effect November 9, makes a number of changes beyond disclosure of human capital.]

The rule takes a principles-based approach to disclosure rather than a prescriptive approach. This means that the requirement is for general disclosure of material information rather than requiring specific types of information. The rule requires a “description of the registrant’s human capital resources, including the number of persons employed by the registrant, and any human capital measures or objectives that the registrant focuses on in managing the business (such as, depending on the nature of the registrant’s business and workforce, measures or objectives that address the development, attraction and retention of personnel).”

The key point is that whatever human capital metrics or other information the company uses to manage must be disclosed.

While this may sound vague, the new rules won’t operate in a vacuum. For example, as one commentator points out, there are already International Standards Organization (ISO) recommendations for human capital metrics, such a development and training costs, and turnover rates. Not surprisingly, accounting/consulting firms (such as PWC) also have approaches to help companies decide what and how to disclose.

Some argue that the SEC should have gone farther to require more disclosure on Environmental, Social, and Governance (ESG) issues. It should be noted that the two Democratic members of the SEC voted against the new rule because the changes didn’t go far enough – in both the scope of the ESG items covered and the lack of any prescriptive requirements. This may foreshadow additional action by the SEC in this area, especially given the incoming Biden Administration. I suspect, however, the SEC will want to see how the new requirements actually work before making any changes. I also suspect, however, that this is just the beginning of additional disclosures in company’s MD&A filings.

Early innovation at Amazon

But not what you think.

This insight is from a review (by James Ledbetter) of a new book collected writings by Jeff Bezos:

Bezos and his wife initially packed up Amazon orders while kneeling on a concrete floor. His idea for improvement was kneepads; when an employee suggested packing tables, Bezos declared him a genius. “The next day I went and bought packing tables and doubled our productivity,” he writes.

Score one for the importance of business process innovation!

October was a “so-so” month for intangible employment

This morning’s employment data from BLS for October is better than expected but still rather disappointing (even though the unemployment rate dropped significantly). Employment rose by 638,000 compared to the 600,000 economists expected. Almost all of that growth was in tangible producing goods and services industries. Similar to the previous months, increases occurred in industries where there is physical presence with customers, specifically Accommodation & Food Services and Trade, Transportation & Utilities.

On the intangible-producing side of the economy, employment in Professional & Business Services expanded at a healthy rate. Almost every other industry grew only very modestly, if at all. But once again, there was a large drop in government employment offsetting most of the gains.

I’ll repeat myself from the last two months. Once again, under normal circumstances this would be a positive increase. However, in the age of COVID-19, this is only a modest rebound in employment. And keep in mind the worrisome trend of furloughed workers being permanently let go.

Much more needs to be done.

Trade in Intangibles – Sept 2020

Earlier this year I posted an analysis of how the then-new pandemic economic shock was affecting our intangibles trade surplus. Back the, IP trade was affected but other sectors only suffers slightly. With all the ups and downs of the past 6 months, it is time for an update based on BEA’s latest trade data for September.

Overall, the intangibles trade surplus has rebounded somewhat since hitting bottom in April. While not yet back to January’s level, it is at least closer to the pre-pandemic trendline. This is being driven by Business Services and Financial Services which dropped in the beginning of the pandemic and are beginning to rebound slightly. Maintenance & Repair Services and net revenues from Intellectual Property Products also took a hit at the beginning of the pandemic but have flatten rather than rebounding. Telecommunications, Computer & Information Services remained flat for the past year or so. Insurance Services and Personal, Cultural & Recreational Services continued their steady decline.

A closer look at specific industries reveals a more nuanced and worrisome picture.

First, there is a new sector added to this analysis: Personal, Cultural, and Recreational Services (see more detailed discussion below on BEA’s revisions to the data). Two points to make here. One, the balance of trade in this category has seen a 5-year steady and dramatic decline. Two, trend was not substantially interrupted by the pandemic. The pandemic caused a slightly turnaround as exports saw a blip in the summer rebound. But exports have flattened recently and imports have continued a steady rise.

The trade surplus in Maintenance and Repair services took a nose dive at the beginning of the pandemic and has not yet begun to recover as exports remain stuck at a lower level.

Our surplus in Intellectual Property also seems stuck at a lower level as payments out (imports) grew at about the same as revenues received (exports). As I noted back in December, the trade surplus in IP products has been declining for almost a decade as revenues (export) have remain essentially flat while payments (imports) have grown.

The pandemic seems to have had little impact on our trade deficit in Insurance Services. But that is not good news as the trendline continues to go straight down with imports climbing and exports declining slightly over the past few years.

The picture for Financial Services is somewhat better. Exports are rising while imports are flat.

The case is similar for Business Services with the surplus rebounding as exports grew faster than imports.

For Telecommunications, Computer, and Information Services, the pandemic had almost no net impact on the trade surplus as exports and imports first dropped and recovered at the same amount. This flat level, however, interrupted a 5-year trend in growth in the trade surplus in this sector.

NOTE: As part of its annual revision, BEA has updated the categories it uses to collect services trade data. As mentioned above, this includes creating a new category called Personal, Cultural, and Recreational Services. This category consists of the following subcategories (some of which were previously included in the Intellectual Property and Business Services categories:

  • Audiovisual services, which covers production of audiovisual content, end-user rights to use audiovisual content, and outright sales and purchases of audiovisual originals
  • Artistic-related services, which includes the services provided by performing artists, authors, composers, and other visual artists; set, costume, and lighting design; presentation and promotion of performing arts and other live entertainment events; and fees to artists and athletes for performances, sporting events, and similar events
  • Other personal, cultural, and recreational services, which includes services such as education services delivered online, remotely provided telemedicine services, and services associated with museum and other cultural, sporting gambling, and recreational activities, except those acquired by customers traveling outside their country of residence

BEA also created a new category called Construction Services separating the data out from the existing Business Services category. Since this category seems to cover physical construction activities, I have decided not to include it as an intangible creating activity, similar to how we treat the Travel and Transportation categories.

For more information, see the BEA article “Preview of the 2020 Annual Update of the International Economic Accounts.”

Learning from an innovation failure

Over at Digital Tonto, Greg Satell has an interesting analysis of why the streaming service Quibi failed. He points out four major flaws: too much money; no hair-on-fire use; no addressing the key bottlenecks; and, not having an adaptable strategy.

I won’t address the “too much money” issue – one that says you need to keep the company lean. I will accept his argument that “limiting the amount of money you have around forces people to face up to problems and solve them,” although my experience has been seeing undercapitalization as the problem.

The other three I think fall into the cardinal principles of innovation: experiment, expand, adapt. The three work together. What Satell calls the “hair-on-fire use case” is having a must use. Rather than identify the largest addressable market, you look for a problem with an immediate need. You use this market to refine and further develop the innovation and follow a flexible strategy to take advance of what you learn (including new opportunities).

This is a variation of what we used to call the “thin opening wedge.”

The process of learning and adapting based on real-time market information is key to success. It is almost axiomatic in innovation research that the first iterations of a new technology are inferior to the existing technology – except in one crucial characteristic. In the case of semiconductors, their advantage over vacuum tubes was in weight and power requirements. The need for low weight and energy in space and defense uses overcame the higher cost. These early markets provided not only a source of funding for further development of the technology (both product and process). They also provided a beta test function that generated important information.

Expanding and adapting is the other key. For example, look at Apple. The iPod was a cute device for music lovers (especially teenagers). It replaced the Walkman with much easier to use technology (digital rather than audio tape) both for play back (no need to carry and change tapes) and for song acquisition (via download). That was the thin opening wedge to a much more powerful platform: the iPhone. Once the iPod was married to a cell phone, the possibilities exploded. Not only was it a voice communications tool (the phone), it was a digital communications device and a digital interconnection device (email, web browsing, GPS, and all those apps).

Remember that Airbnb started out as a means to people to identify places to crash for the night. Uber was an on-demand sedan service. Amazon was a book seller based on the arbitrage between publishers’ prices and the retail bookstore prices. Each of these expanded by using the infrastructure (physical and organizational) created to service that first market.

Tied into this process of experimenting, expanding and adapting is making sure you are focusing on the right questions. Satell notes that successful innovations address the hard problems first. These are the bottlenecks that will cause the innovation to be an also-ran in a crowded field. The example he uses is Tesla and battery technology. Electric vehicles have been around since the dawn of the automobile age. In a more recent (relatively speaking) case, in the late 70’s / early 80’s I worked on a technology assessment of electric vehicles for Detroit Edison (and was licensed to drive their test vehicles – modified VW Rabbits with a ton of batteries in the back). Our conclusion was not surprising: limitations of battery technology would keep EVs in niche markets such local delivery vehicles with limited range, limited speed and the ability to recharge overnight. But even in that market, there was no great advantage for EVs over gasoline powered vehicles. Satell notes that Tesla’s breakthrough was to combine an improved, good-enough batter technology with a niche market of affluent consumers who would pay for the cache of an eco-friendly car.

In conclusion, let me just note that each of these examples of successes illustrate the principles of experiment, expand, adapt. Satell’s analysis of the failure of Quibi provided a useful counterpart to the success stories. Since the mantra of innovation includes learning from failure, I hope would-be entrepreneurs will take the lessons Satell provides to heart.

3Q GDP and investment

Obviously the big story with today’s GDP numbers is the (partial) rebound in consumer spending.

But the more important story for long run economic growth is what is (and is not) happening in business investment.

Overall, private fixed non-residential investment grew in 3Q led by investment in equipment. Business investment in equipment grew in 3Q almost to the pre-slowdown level. While all categories of equipment investment increased in 3Q, the biggest gain was in spending on information processing equipment increased – which had also increased significantly in the 2nd quarter. Such an increase bodes well for future growth.

That was the good news. The bad news is that investment in intellectual property products – the seed corn for future growth – actually declined in 3Q. Business spending on R&D declined in the 3rd quarter, as did investment in the creation of entertainment, literary, and artistic originals. Investment in software up was up slightly.

The slowdown in R&D spending is especially troublesome. It is always tempting for companies to cut back on R&D when times are tight. But given the concern about low R&D spending nationally in the U.S., the continued cut back when other parts of the economy may be starting to bounce back signals a level of uncertainly about future growth.

Innovation in response to COVID-19

New data from a UK survey indicates that the COVID-19 pandemic is jump-starting innovation (at least in the UK). The survey, The Business Response to Covid-19: the CEP-CBI survey on technology adoption, looked at four types of innovation:

  • Introduction of new products or services
  • Adoption of digital technologies such as customer relationship management systems, remote working technologies, mobile technologies, cloud computing, automation, and AI. (Process innovations)
  • Adoption of digital capabilities, such as e-commerce, advanced analytics, and cyber-security. (Process innovations)
  • Adoption of digital capabilities, such as e-commerce, advanced analytics, and cyber-security. (Process innovations)

[Note: While I am not completely clear of the difference between digital technologies and digital capabilities, the difference is apparently enough to have significantly difference levels of adoption – see below.]

The survey reports that 60% of firms indicated that they adopted new digital technologies or new management practices; 38% adopted new digital capabilities and 45% introduced new products or services. Of firms adopting new digital technologies or new management practices, 95% did so because of the pandemic. The corresponding date was 90% for adoption of digital capabilities and only 75% for new products or services.

Answers to the survey also indicated that the overwhelming number of firms (90%) expect the innovations to be permanent changes not just temporary measures to get through the crisis.

Given the lower overall rate of new products and services as well as the lower direct response to the pandemic, this suggests that process innovations are what businesses are focused on.

The results are in stark contrast to innovation in “normal” times. The UK Innovation Survey for the years 2016-2018 indicated that only 13% of businesses were involved in process innovation and 18% we involved in product innovation.

The results make intuitive sense. With lower overall demand and a concern over day-to-day operating sustainability, the pandemic is causing companies to look at greater efficiencies rather than the latest new thing.

Not surprisingly companies saw macroeconomic uncertainly as the biggest barrier to innovation (with that uncertainty in thee UK complicated by Brexit). Follow that was what we have generally seen as barriers to innovation: financial constraints and a number of factors I would lump together as absorptive capacity (e.g. lack of skills, resistance to change, lack of information, lack of technological infrastructure to support new digital technologies, applicability doubts, etc.).

Finally, the survey found – not surprisingly – that companies who had adopting new digital technologies or capacities pre-pandemic were significantly more likely to innovate in response to the crisis.

The good news here is that more firms are responding to the crises with innovations, especially process innovation. The trick is to help them sustain that activity – especially for what I would call the new-to-innovation companies.

Intangible employment flatlines in Sept

This morning’s employment data from BLS for September is rather disappointing (even though the unemployment rate dropped significantly). Employment rose by only 661,000 compared to the 850,000 economists expected. All most all of that growth was in tangible producing goods and services industries. Similar to the previous months, increases occurred in industries where there is physical presence with customers, specifically Accommodation & Food Services and Trade, Transportation & Utilities.

On the intangible-producing side of the economy, employment grew modestly in almost every industry. But those gains were offset by a large drop in government employment, which the BLS says were mainly in state and local education – probably reflecting the slow return to the classroom.

Once again, under normal circumstances this would be a positive increase. However, in the age of COVID-19, this is only a modest rebound in employment. And keep in mind the worrisome trend of furloughed workers being permanently let go. Much more needs to be done.

What ever happened to “competitiveness”?

As I was doing some research on the current debate on industrial policy (see last week’s posting), I was struck by something missing. Economic competitiveness rarely gets mentioned in the policy discussions now days. The concern that we need to compete with other nations is common, especially with respect to competing with China. But the rubric of “competitiveness” as a framework for policymaking seems to have disappeared from the public discourse.

First, a little history. The term came into the public discourse in 1984 when President Reagan created the President’s Commission on Industrial Competitiveness (aka the Young Commission), chaired by then HP CEO John Young. In part, the Commission seems to have been set up to counter the focus on industrial policy by the democrats in an election year.

Whatever the reason for its establishment, the Young Commission succeeded in changing the terms of the debate. It shifted focus 90 degrees from policies for specific industrial (often referred to as horizontal policies) to a focus on crosscutting policies that (theoretically) benefit all industries (vertical policies). Their 1985 report Global Competition: The New Reality stated that “Competitiveness can be defined as the degree to which a nation can, under free and fair market conditions, produce goods and services that meet the test of international markets while at the same time maintaining or expanding the real incomes of its citizens.” Note two important concepts: test of international markets and rising standards of living.

Young then went on to form the Council on Competitiveness in 1986 to carry on the Commission’s work and the Omnibus Trade and Competitiveness Act of 1988 addressed a number of competitiveness issues, including establishing a Competitiveness Policy Council (something that I was heavily involved in).

While the CPC had its funding eliminated in 1997, other organization such as the Council on Competitiveness, carried on the work. The World Economic Forum (WEF) annually publishes its Global Competitiveness Index and IMD (International Institute for Management Development) issues a World Competitiveness Rankings. Most recently, the Council on Competitiveness established a National Commission on Innovation and Competitiveness Frontiers.

Over the years the framework for analyzing competitiveness has evolved only slightly. The Young Commission report laid out four pillars of competitiveness:

  • technology;
  • capital;
  • human resources;
  • and, trade.

The Competitiveness Policy Council started with eight issue areas:

  • capital formation;
  • education;
  • training;
  • public infrastructure;
  • corporate governance and financial markets;
  • trade policy;
  • manufacturing; and,
  • critical technologies.

WEF’s Competitiveness Index covers 12:

  • institutions;
  • infrastructure;
  • ICT adoption;
  • macroeconomic stability;
  • health;
  • skills;
  • product market;
  • labor market;
  • financial system;
  • market size;
  • business dynamism; and,
  • innovation capacity.

All of these provide a framework of components for understanding a nation’s competitiveness.

The Council on Competitiveness’ National Commission on Innovation and Competitiveness Frontiers has taken a slightly different approach. Rather than looking at components of competitiveness, they identified three challenges:

  • Developing and Deploying at Scale Disruptive Technologies
  • Exploring the Future of Sustainable Production and Consumption, and Work
  • Optimizing the U.S. Innovation System

Based on analysis by a working group in each area, they developed a nine point action plan, to be explored further:

  • Build a Diverse Pipeline of Innovators – Encourage and support more women, and racial and ethnic minorities in the pursuit of innovation and entrepreneurship.
  • Prepare America’s Workforce for the Future – Invest more in STEM education and worker retraining for coming market disruptions.
  • Expand the U.S. Map of Innovation Investment Hubs – Build more diverse engines for innovation across the United States.
  • Secure U.S. Capabilities in Critical Technologies – Including microelectronics, artificial intelligence, and biotechnology.
  • Strengthen U.S. Economic Resiliency – Regain control of critical supply chains and reduce dependency on China and other foreign sources.
  • Confront China’s plans for technological, military, and commercial supremacy.
  • Amplify U.S. University Investments – Particularly in technology transfer, commercialization and industry engagement.
  • Bridge the “Valley of Death” Gap in Innovation – Grow government investment in small business innovation, startups, and the testing of new technologies.
  • Deepen the Sustainability Culture in U.S. Businesses – Including more efficient use of energy, use of cleaner energy, and more sustainable materials sourcing.

These are all good ideas.  And they expand the problem-set implied in the original definition of competitiveness to include environment sustainability.

However, I wish they were more explicitly tied to a competitiveness framework. For example, short-term thinking in companies’ management practices and in the financial markets were identified as an area of concern in the Young Commission and CPC reports—growing out of their frameworks that explicitly looked at financing and the financial markets as a component of competitiveness.

We need a way to look systematically at the foundations of our economic competitiveness. Just as monitoring one’s personal heath is better than waiting for a diagnosis and way better than just treating the symptoms, we need a mechanism to go beyond the current problems.

Taking this more comprehensive approach would complement the work of existing organization, such as the Council on Competitiveness. I would note that the law creating Competitiveness Policy Council is still on the books. Maybe it is time to revive it. The argument is being make that Congress should resurrect the Office of Technology Assessment to provide more systematic, comprehensive, and long-term analysis on technology issues. The same argument holds true for the Competitiveness Policy Council.

You say tomato, I say … Industrial Policy

As I have noted before, the concept of industrial policy is making a resurgence. But is beginning to sound like the old song, “You say tomato, I say tomahto” (or the modern version “you say GIF, I say gif”). In this case, you say industrial policy, someone else says innovation policy – and they really mean technology policy.

Here are a few examples. Caleb Watney in “Untangling innovation from industrial policy” argues that we shouldn’t use the term anymore — it is too encompassing and therefore vague. Adam Thierer in “On Defining ‘Industrial Policy‘” takes the narrower approach, focusing on “developing or retrenching selected industries to achieve national economic goals” (a definition he borrows from historian Ellis Hawley as published in the 1986 AEI book The Politics of Industrial Policy). Dylan Gerstel and Matthew P. Goodman (From Industrial Policy to Innovation Strategy: Lessons from Japan, Europe, and the United States) seem to wrap industrial policy in the rubric of innovation policy, by which they really mean technology policy.

These discussions recount the debate over industrial policy in the 1980s. As someone who was heavily involved in those debates, the current discussions have a feeling of déjà vu. Back then, I tried to make sense of the various conceptual frameworks and approaches to industrial policy (see “A Reader’s Guide to the Industrial Policy Debate“). Many of today’s arguments fall into those same rubrics.

In some cases, the debate is on aid to a specific industry, (e.g. save the semiconductor industry, save the auto industry, save the …) – what I have called the problem-solving approach. The danger in this approach is that it fails to consider the system-wide effect of these actions on the economy as a whole. In other cases, the debate focuses on a specific policy (e.g. trade protection, Buy America, R&D tax credits) in an instrument-specific approach. The danger here is in the law-of-the-hammer: give a child a hammer and everything looks like a nail. In other words, the policy instrument is used not necessarily because it is appropriate but because it is available.

Another version, industrial policy is essentially manufacturing policy (what I labeled back in the 1980s as the “reindustrialization” approach). And while I am a strong manufacturing-matters advocate, I also strongly believe that industrial policy goes beyond manufacturing.

Two other versions of industrial policy routinely appear in the debate. I had labeled these as the “industrial triage” and the “reallocation” approaches. In industrial triage, some industries are doing fine while others are doomed to decline so attention should be paid to those where government help would be the most effective. The reallocation approach is similar in that it seeks to move resources from “sunset” industries to “sunrise” industries. While not using the same terms as before, part of the current debate over “industries of the future” is built upon this argument. Of course, both of these are subject to the classic criticism of “picking winner and losers.” Advocates for these approaches often respond with the argument that picking winners is exactly what we should be doing.

Only occasionally raised in the debate is the most comprehensive version of what I labelled “structural industrial policy” that focuses on the entire production system and multiple economic objectives. The earlier example I gave of this approach is the Japanese developmental state. It should be noted however that such an approach is difficult to establish and maintain due to a number of issues including political capture.

I would also note that the politics of industrial policy has changed very little over the past few decades. With some notable exceptions (such as Senator Mario Rubio), liberals argue for a more activist industrial policy while conservative argue for less. As a result, we tend to have a fear driven policy that appeals to both liberals and conservatives. Today, we have a fear-of-China industrial policy. In 1980s it was a fear-of-Japan industrial policy. In 1950s and 60s had a fear-of-Russia industrial policy. One could even argue that Hamilton’s Report on Manufacturing and Henry Clay’s American System were in part fear-of-Britain industrial policies.

I understand the political value of the fear-of approach and the reluctance to advocate for a systemic structural approach. Absent a national security rationale, such a more comprehensive approach brings attacks of “centralized planning.” But without the more systemic structural view, industrial policy devolves into piecemeal reactive actions. Such an outcome simply reinforces the critic that industrial policy is ineffective and captured by special interests. To avoid that outcome, we need to raise the debate to a higher conceptual level.