“Why don’t they use common sense?!” You may have said this phrase yourself, or heard it with your managers, when discussing an employee’s actions. However, the frustrated appeal to “common sense” doesn’t actually make any meaningful change in your organization. We all make decisions based on the information we have and the guides we have to use. So if the wrong decisions are being made in your organization, it’s time to examine the tools you give decision-makers.
As George Santayana put it, “Those who cannot remember the past are condemned to repeat it.” Well, the U.S. has returned to an environment where small companies and small-business-like teams at universities innovate outside of large companies and sell them in the market for ideas. While the notion of innovation created by small flexible firms is appealing, the contributions made by large corporate labs were a much more significant benefit to the U.S. So what happened? A recent paper, “The changing structure of American innovation: Some cautionary remarks for economic growth,” by Arora, Belenzon, Patacconi, and Suh, examines the golden age of corporate-driven research up to Ronald Reagan’s presidency, before its steady decline up to the present day.
By the late 19th century, most of the development of innovations took place in small companies, i.e., the Wright Brothers, and large corporations then acquired it in the market. The environment was similar to the one we live in today: inventors came up with ideas, venture capitalists funded, and companies commercialized the ideas. There were patent lawyers and non-practicing entities, which own patents purely to litigate on their behalf. There were still startups commercializing an idea and scaling it up themselves, but many inventors found that the market’s division of labor allowed them to focus on what they did best.
Large firms acquired the ideas created by inventors and were skeptical of the value of doing in-house science. Their modus operandi was that it was easier to buy new science off the shelf. T. D. Lockwood, head of American Bell Telephone Company’s patent department, said in 1885, “I am fully convinced that it has never, is not now, and never will pay commercially, to keep an establishment of professional inventors, or of men whose chief business it is to invent.”
The 1920s stock market boom, similar to the 1990s Dot.com bubble, was driven in large part by a considerable increase in the value that investors accorded to intangible capital and ideas held within companies. From 1921 to 1927, the number of scientists and engineers working in industrial labs increased by more than 100%.
The 1929 stock market crash and the Great Depression caused a massive and persistent decline in independent inventing and the startup-like activity around it. However, large corporate labs continued to boom, increasing staffing and research spending throughout the lean 1930s, and earning more patents. By 1930, large firms received most patents, rather than independent innovators, and this gap only widened into the 1950s. The industrial lab was king.
Bell Labs, proving T. D. Lockwood wrong, grew to be one of the most outstanding commercial labs. By the late 1960s, it employed over 15,000 people, including 1,200 PhDs, who between them made too many important inventions to list, from the transistor and the photovoltaic cell to the first digitally scrambled voice audio (in 1943) and the first complex number calculator (in 1939). Fourteen of its staff went on to win Nobel Prizes and five to win Turing Awards.
DuPont established its research facilities in 1903, and they rivaled that of top academic chemistry departments. In the 1960s, DuPont’s central R&D unit published more articles in the Journal of the American Chemical Society than M.I.T. and Caltech combined.
R&D Magazine, which awards the R&D 100 to the hundred innovations it judges most innovative in a given four year period, presented 41% of its awards to Fortune 500 companies in its 1971 iteration and 47% in 1975.
The iconic corporate lab story of time was PARC. Xerox’s Palo Alto Research Centre, located in Palo Alto, the heart of Silicon Valley, developed many of the foundational building blocks of today’s technology and economy. PARC researchers produced, among other things:
- the first computer with a graphical user interface,
- the first laser printer,
- the first Ethernet cable, and
- the first user-friendly word processor.
Following a visit to PARC in 1979, Steve Jobs incorporated many of the ideas into Apple products. Charles Simonyi, a key developer at PARC, moved to Microsoft, where he developed the Office suite. However, Xerox itself did not capitalize on these inventions.
Why Corporate Labs Succeeded
According to economist Ronald Coase, who won the Nobel Prize in 1991, the key to the success of corporate labs is transaction costs. In his 1937 work entitled “The Nature of the Firm,” Coase provides the rationale why firms exist. Given that most economic, competitive behavior takes place in open markets, labor is the exception. In most cases, when we sell our labor, we bind ourselves to a single “buyer,” our employer, for an extended period for everything we have to offer. If market competition is so efficient, why is the “gig” economy not the popular model? While the “gig” economy is growing, as I have noted before, mainly, it caters to lower-skilled employees.
Coase’s second treatise providing insight into this issue, “The Problem of Social Cost,” was published in 1960. It launched the so-called Coase Theorem, which states that if transaction costs, the costs of interacting with other individuals or institutions, e.g., the costs of drawing up and enforcing a contract, are low, people will contract to deal with the problems emerging from positive and negative externalities. However, when transaction costs are high, institutions and policies are needed to deal with the externalities instead.
Large R&D labs exist for the same reasons as firms. The transaction costs of collaboration are considerable:
- the financial costs of contracting with others;
- the costs of finding people you work well with;
- the costs of corresponding and collaborating with people far from you, and so on; and
- chance meetings are a crucial driver of serendipitous discovery and unexpected but fruitful collaborations, as we are learning with the COVID work from home.
Data shows that university lecturers collaborate more with those in their department than in other departments, and more with those in their university or city than elsewhere, despite the internet’s improved communication abilities.
Research labs provide a low-cost way to bring together an array of scientific experts from different disciplines for collaboration. Finally, as many scientific ideas have little practical applications, research labs provide a way of reducing that waste.
Why They Died
As mentioned above, the corporate labs of the 50s and 60s generated great ideas and innovation. However, starting in the 1970s, the decline began:
- Bell Labs was separated from its parent company AT&T and placed under Lucent in 1996;
- Xerox PARCwas spun off into a separate company in 2002.
- I.B.M., under Louis Gerstner, re-directed research toward more commercial applications in the mid-90s.
- DuPont’s attitude toward research changed in the 1990s, and the company’s management closed its Central Research and Development Lab in 2016.
By 2006, only 6% of the awards from R&D Magazine were going to firms in the Fortune 500. Federal labs, university teams, and spin-offs from academia are winning the majority.
So why did corporate R&D labs die? According to Arora et al., the rise and fall of corporate R&D labs are linked to the rise and fall of antitrust enforcement. However, I would argue that Milton Friedman bears an equal share of responsibility.
Following the regulations of the 1930s, firms’ abilities to grow through mergers and acquisitions decreased because of antitrust pressures. These pressures, combined with little produced by universities and independent inventors, large firms had no choice but to invest in internal R&D.
However, starting in the late 1940s, antitrust pressures had switched from mergers to monopoly power. The 1949 case against AT&T’s Bell Labs, which resulted in the forced divestment of its non-telecoms arms, and compulsory no-fee licensing of all 7,820 of its non-telecoms patents by Bell Labs. At the time, this amounted to 1.3% of the total stock of patents in force in the U.S.A. While there is evidence that this move provided a foundation for many of the significant innovations of the next fifty years in the U.S., it was effectively a large scale patent invalidation. The result was a chilling effect on innovation in big firms’ R&D labs. The further antitrust moves by the D.O.J. against I.B.M. and which broke up AT&T compounded the problem.
With the Reagan administration, the merger antitrust environment became more relaxed in the 1980s, as was seen with the emergence of corporate raiders, etc. However, this changed this status quo, and growth through acquisitions became a more viable alternative to internal research, and hence the need to invest in internal research was reduced.
Friedman’s theory, “A Friedman Doctrine: The Social Responsibility of Business is to Increase Its Profits,” was published in the New York Times in 1970, fifty years ago today. It concluded with, “there is one and only one social responsibility of business—to use its resources and engage in activities designed to increase its profits so long as it stays within the rules of the game, which is to say, engages in open and free competition without deception or fraud.”
As a result of Friedman’s work, companies started to focus solely on profit maximization. The results were:
- Companies reduced their size, scope, and vertical integration, e.g., the break of I.T.T.
- The culling of R&D labs as profit and benefits were hard to identify beforehand and often occurred far into the future.
These actions resulted in the shutting down of R&D labs or trying, as I.B.M. did, to refocus them on commercial applications. Finally, firms that had them found the benefits of innovation were captured less by the firm and tended to spill more into the general economy, reducing the return to the firm.
What was the impact of Corporate R&D Labs?
A paper by Robert Gordon points out that American G.D.P. per hour grew:
- 1.79 percent per year between 1870 and 1920
- 1.62 percent per year between 1970 and 2014 (the figure is similar if extended out to 2020).
- However, it was 2.82 percent per year between 1920 and 1970.
Others have found similar trends.
- The number of researchers needed to develop a new idea is growing.
- The rate of significant innovations is falling.
- Economic productivity is increasing more slowly.
Simple metrics like airplane engine power, crop yields, life expectancy, height, and computer processing speed are increasing at slower rates. From the industrial revolution until the mid 20th century, there was steady progress with increasing growth; however, progress has slowed since.
Arora et al. provide four reasons why the corporate labs drove faster productivity growth.
- Corporate labs work on general-purpose technologies. As the leading companies in their market hosted the labs, the companies believed that technologies that benefited their product space would help them the most. For example, Claude Shannon’s work on information theory was supported by Bell Labs because AT&T stood to benefit the most from a more efficient communication network. The same rationale was behind I.B.M.’s support of nanoscience. By developing the scanning electron microscope, and further investigations into electron localization, non-equilibrium superconductivity, and ballistic electron motions because it saw an opportunity to pre-empt the next revolutionary chip design in its industry.
- Corporate labs solve practical problems. As Andrew Odlyzko said, “It was very important that Bell Labs had a connection to the market, and thereby to real problems. The fact that it wasn’t a tight coupling is what enabled people to work on many long-term problems. But the coupling was there, and so the wild goose chases that are at the heart of really innovative research tended to be less wild, more carefully targeted and less subject to the inertia that is characteristic of university research.”
- Corporate labs are multi-disciplinary and have more resources. Arora et al. point to Google as an example. “Researching neural networks requires an interdisciplinary team. Domain specialists (e.g., linguists in the case of machine translation) define the problem to be solved and assess performance; statisticians design the algorithms, theorize on their error bounds and optimization routines; computer scientists search for efficiency gains in implementing the algorithms. Not surprisingly, the ‘Google translate’ paper has 31 coauthors, many of them leading researchers in their respective fields.” However, according to Jaime Powell stated, “the problem of falling research productivity is like the ‘high energy physics’ problem – after a while, all the experiments at a given energy level have been done, and getting to the next energy level is bound to be a lot more expensive and difficult each time.”
- Large corporate labs may generate significant external benefits. By “external benefits,” Arora et al. refer benefits to society and the broader economy, but not to the lab’s host company, as in the case of Xerox Parc. “While Xerox failed to internalize the benefits fully from its immensely creative lab … it can hardly be questioned that the social benefits were large, with the combined market capitalization of Apple and Microsoft now exceeding 1.6 trillion dollars.” However, PARC had spin-offs, in which Xerox had equity and startups that built on their ideas and hired their alumni but in which Xerox did not. Xerox didn’t do spin-offs well! On the other hand, Cisco is among the better example of how spin-offs can be well managed, acting as an internal V.C. to incentivize a team by giving them equity in a startup. If it were successful, Cisco would later acquire it.
Startups and Universities Have Not Solved the Problem
We think that the current environment, an innovation system based around an open market for ideas, with the division of labor between specialized firms, rather than specialized teams within firms, is attractive. There is constant talk of how much easier it is to start a business today with the ability to test ideas, scale with the benefits of the “gig” economy, cloud platforms, e.g., A.W.S., and SaaS models, and get Angel and V.C. funding. As attractive as this narrative is, it is false. As I have discussed before, and there is plenty of data to support the claim that new business startups are at their lowest level since the Carter Administration. Furthermore, while small new ventures are more flexible and adapt to new situations quicker, and possibly come up with new ideas more rapidly than big incumbents, they are not delivering the growth we have historically experienced. Why?
Disintegrated businesses have less incentive to research general-purpose technologies. An estimate found that over time society at large captures 98% of the value of innovations, and the innovator 2%. Thus, the Friedman theory implies that, by themselves, small businesses will not do as much research as is optimal from society’s point of view. However, for large vertically integrated companies, they can use more of the benefits of discoveries that smaller firms would not be able to capture, even with robust intellectual property protection, so it is worthwhile for them.
Finally, what we have seen over the last two decades or more is the failure of the D.O.J. to enforce proper antitrust, which has resulted in many companies acquiring startups with technology only to shut them down and kill the technology.
As Arora et al. argue that a cause of the decline in productivity is that, “The past three decades have been marked by a growing division of labor between universities focusing on research and large corporations focusing on development. The knowledge produced by universities is not often in a form that can be readily digested and turned into new goods and services. Small firms and university technology transfer offices cannot fully substitute for corporate research, which had integrated multiple disciplines at the scale required to solve significant technical problems.”
Will Corporate R&D labs return?
It appears that some are. Google, Facebook, Amazon, et al. have all developed large R&D labs. In some cases, the research is more focused, but over the benefits are there. These efforts, combined with the current trend to provide the D.O.J.’s antitrust actions with some teeth, might start a greater return to corporate R&D. Given the benefits to the country, we should hope so.
You can only determine profitability when you know your costs. I’ve discussed before that you should price according to value, not hours. However, you still need to know your costs to understand the minimum pricing and how it is performing. Do you consider each jobs’ profitability when you price new jobs? Do you know what you should be charging to ensure you hit your profit targets? These discussions about a company’s profitability, and what measure drives profit, are critical for your organization.
If you were starting your business today, what would you do differently? This thought-provoking question is a valuable exercise, especially when it brings up the idea of “sunk costs” and how they limit us. A sunk cost is a payment or investment that has already been made. Since it is unrecoverable no matter what, a sunk cost shouldn’t be factored into any future decisions. However, we’re all familiar with the sunk cost fallacy: behavior driven by a past expenditure that isn’t recoupable, regardless of future actions.
Bringing clarity to your organization is a common theme on The Disruption! blog. Defining your business model is a worthwhile exercise for any leadership team. But how do you even begin to bring clarity into your operations? If you’re looking for a place to start, Josh Kaufman’s “Five Parts of Every Business” offers an excellent framework. Kaufman defines five parts of every business model that all flow into the next, breaking it down into Value Creation, Marketing, Sales, Value Delivery, and Finance.
Bringing in new ideas, thoughts, understanding, and logic is key as your organization faces the challenges of a changing environment. But when you do an ideation session in your organization… how does it go? For so many organizations, many times, after a few ideas have been thrown out and rejected, the thought process slows down very quickly, and a form of hopelessness takes over. How does your organization have better ideation? I’ve come across a new approach with a few teams lately.
An uptick in business has begun this quarter, and companies are rushing to hire to meet this surge in demand. What amazes me is how many are so unprepared to hire. Continual recruiting is key to the survival of a company. It isn’t the same thing as hiring—continuous recruiting is building a pipeline of people that you would hire if you needed to fill a position, or “A players” you would hire if they were available.
If your organization is focused on obscurity over clarity, whether intentionally or not, your “A” player employees are vulnerable. There is a looming talent crunch. As we start to emerge from COVID, demand is increasing, and many are scrambling to fill positions to meet that demand. Headhunters and recruiters are soon going to be calling your key “A” employees. Have you been giving them a reason to stay?
As Leonard Bernstein put it so well, “To achieve great things, two things are needed: a plan and not quite enough time.” Your meetings can be shorter, more fruitful, and engaging, with better outcomes for the organization, employees, and managers. It’s time to examine your meeting rhythms and how you set meeting agendas. This week, I break down daily, weekly, monthly, quarterly, annual, and individual meeting rhythms, with sample agendas for each.
Let’s start here: Why should your company be scalable at all? If your business is scalable, you have business freedom–freedom with time, money, and options. Many business leaders get stuck in the “owner’s trap”, where you need to do everything yourself. Sound familiar? If you want a scalable business that gives you freedom, you need to be intentional about what you sell, and how.
Companies are gearing up to hire. Unfortunately, many are competing within the same talent pool. Some experts are currently predicting a strong economic recovery starting in May or June. But as the economy booms, there is going to be fierce competition for talent. How will you fare in the looming talent crisis? Your organization should be creating a plan, now, so you can attract the talent you need in the year ahead.