Gaming the Systems of Venture Capital and R&D

    Early investors profiting from startups while later investors lose millions is just one example of how the R&D and venture capital systems are gamed. For instance, WeWork’s founder Adam Neumann purportedly received $1.7 billion to exit WeWork while other investors have lost billions, including Softbank. Or Uber: 18 funds and individuals valued Uber at $5.4 million in 2010 and that same company is now worth about $50 billion, or 10,000 times its 2010 value. Yet later investors have lost money as Uber’s losses have risen and its share price has declined.

    From VCs to entrepreneurs, consultants, universities, and academics, the ease and frequency with which VC and R&D can be gamed has increased. Two things are behind this rise.

    First, the growing number of online technology news, investor, and consulting sites, the growth of social media, and the falling cost of blogging, posting slides and videos, and creating websites (as described in my article What’s Behind Technological Hype) provide new ways for VCs, universities, and others to tout their advances and thus game the R&D system. Many of the new online technology news sites focus on investors whose importance has increased as VC fund raising and stock market investing have exploded. These news sites along with VCs, entrepreneurs, and other supporters of startups spread articles and reports about startups, venture capitalists, and university research through sharing on LinkedIn, Facebook and Twitter.

    These trends are exacerbated by the rise of online sponsored content and native advertising, both with the look and feel of news written by independent journalists even though they aren’t. The amount spent on these new forms of advertising now exceed those spent on banner advertising. These new forms of advertising blur the lines between facts and opinion, thus enabling venture capitalists, entrepreneurs, and universities to promote their activities, and then later claim they were merely encouraging innovation and risk taking.

     A second and bigger driver of gaming the system is the rise of intermediate measures of success. From VC funding of geographical regions and organizations to the numbers of patents, academic papers, and startups, and the amount of R&D funding, intermediate measures of innovation have become more common over the last 70 years as the division of labor in R&D has changed from vertically integrated corporations (e.g., AT&T and Bell Labs) to a system of open innovation, academic research and startups. This change in the division of labor has increased the prominence of entrepreneurs, venture capitalists, small tech firms, universities, and individual academic researchers, who must be purportedly measured using quantitative yardsticks because “if you can’t measure something, you can’t understand it.” These new measures provide new ways to game the system, without encouraging real innovation. For instance, regions that have yet to produce revolutionary products or services or long-term startup successes brag about startups being formed, funding being received from VCs, and universities receiving large amounts of VC or research funding.

Venture Capitalists

   Venture capital (VC) funding has become the new measure of success for countries, states, cities, universities, and other geographical regions and organizations, as described in my recent linkedin article The Hype about Venture Capital and Entrepreneurship. Regions compete for this funding and then claim they are successful when they get funding. Universities also do this when they get research funding or startups are formed. Whether these startups and rising funding lead to revolutionary products and services is lost in the hype about numbers of startups and amounts of research funding.

    The strategy has been hugely successful with record levels of VC funding achieved in 2018 everywhere in the world. VC funding in the U.S. reached levels not seen since the dotcom bubble and other countries have seen even bigger rises. For instance, funding for British and South-East Asian startups exceeded $5 and $3 billion respectively in 2019, rising from almost zero five years before, while the VC media writes articles with titles such as “Are these the future unicorns of Amsterdam?,” without mentioning the large losses of these startups. Even South America, Eastern European countries, and small Asian countries are part of the VC and startup boom.

    VCs have achieved this success through several means. First, they have convinced pension funds, corporate venture capitalists, sovereign wealth funds, and other public investors that investments in startups are much more profitable than are investments in publicly traded companies. Second, they use the changes in online media described above to spread their message, benefiting from the fact that people believe things the more they hear them.

    Third, professional and business service consultants help these VCs because they want to sell them new strategies and business models along with basic accounting and legal advice. For instance, McKinsey, Accenture, and other large consulting firms have promised economic gains as large as $15.7 trillion from artificial intelligence by 2030, a promise that will be forgotten long before companies realize they have wasted billions of hours in management attention. Moreover, with a five-times increase in the number of such consultants since 1970, the number of people who have an incentive to hype startups continues to rise. 

    Fourth, VCs and consultants have become good at using buzzwords such as AI, blockchain, algorithms, revenue growth, business models, and platform management in online media and in their proposals. According to one study, 40% of 2,830 purported AI start-ups surveyed in Europe don’t actually use AI and that companies using AI in their pitch are likely to get 15-50% more funding. For instance, McDonald’s acquired the startup Dynamic Yield for $300 million in 2018, later to find that its platform has nothing to do with AI, according to its former head of content. The head of content made the case that “marketers, investors, pundits, journalists and technologists are all in on an AI scam.”

    Similarly, platform management is also a widely abused buzzword, building from the hype offered by business schools. It is not a coincidence that most of the current loss-making startups, from ride, scooter, bike, and office sharing, to food delivery and peer-to peer loans, offer platforms.

    Incumbents do similar things to game the system, none of which contributes to real innovation. For instance, incumbents such as IBM, Oracle, Microsoft, and Google mention AI, blockchain and other hot technologies in their quarterly results and press releases, but have yet to release few details about the killer apps of these technologies. Contrast this with the personal computer’s killer apps of word processing and spreadsheets that were providing real benefits to millions of users by the early 1980s, a mere five years after the first desktop computer was released in 1975.

    The big problem is that the rising hype by incumbents, VCs, and startups has not translated into revolutionary new products, services, or processes, or of profitable startups. The profitability of startups doing IPOs fell to18% in 2018, record lows not seen since the dotcom bubble, even as the median time to IPO rose from 2.8 years in 1998 to 7.7 years in 2016. From ride sharing to food delivery, peer-to peer loans, and bicycle, office, and scooter sharing, today’s startups are losing more money than the most famous of loss-makers, Amazon, a startup that was profitable before it had reached the current ages of Uber and Lyft.

Universities and academics

    Universities also game the system, although few academics would admit this. Thirty years ago, Edwin Mansfield found through surveys of companies that academic research was important to a small number of industries, principally pharmaceuticals, instruments, and electronics. But new studies ignore real products and services and focus on the relationship between patents and papers. These studies show a strong linkage between the so-called science of academic papers and the innovation of patents.

    While this may convince universities and their academics that they are making meaningful contributions to America’s R&D system, there is no evidence that new science-based technologies are coming out, particularly when compared to the glory years of the 1940s, 1950s and 1960s. The 1940s, 1950s and the 1960s were the age of polymers, transistors, integrated circuits, magnetic storage, lasers, LEDs, LCDs, glass fiber, and silicon solar cells, while the list for the last 30 years is embarrassingly small. Once we note that the Internet came from technologies that originated in the 1950s and 1960s, we are left with biotechnology, lithium-ion batteries, and perhaps organic LEDs, not an impressive list when one considers the huge increase in government and university funding that occurred in the 1960s and 1970s.

    Moreover, proponents of linkages between academic papers and patents have never shown a linkage between patents and productivity, or that corporate R&D people read or utilize academic papers. The number of patents has risen about six times over the last 30 years even as productivity growth has slowed. The reality is that most of these increases came from the patent offices reducing the novelty requirements to attract more patent applications. The number of academic papers has also exploded, exceeding two million in 2016, yet more science-based technologies are not coming out.

     Universities have raised the hype in the last 20 years by increasing the number of entrepreneurship programs. As described in a recent linkedin article Rising Technological Hype from Universities, the number of entrepreneurship programs grew from about 16 in 1970 to more than 2000 in 2014. Many emphasize the vision and genius of entrepreneurs, opportunities are everywhere, incumbents are regularly being disrupted and  experimentation is more important than careful economic analysis. For instance, in their 2014 paper about entrepreneurship, three Harvard professors argue: the “probabilities of success are low, extremely skewed and unknowable until an investment is made,” thus encouraging anyone with an idea to run with it, and without doing much economic analysis. Inaccurate and misleading forecasts by MIT’s Technology Review and Scientific American, supported by university scientists and engineers, make it easier for universities to make these claims.

    This type of hype continues to expand the number of people who think VC funding and entrepreneurship are essential measure of progress, particularly at universities. Many universities are trying to measure professors in terms of entrepreneurial activities, in addition to measuring them by publications, both at the expense of teaching. Not only have they hired consultants to help students formulate ideas and business models, they want professors to participate in these activities, presumably trying to commercialize the ideas described in their papers. Whether their academic papers are relevant for new products, services, or processes, or whether their skills are relevant for starting companies are questions that are largely ignored, and thus the efforts to increase the participation of professors in entrepreneurial activities are likely to produce more hype than revolutionary changes, or successful startups.

Are there better measures of success?

      VC funding, R&D spending, and even numbers of patents and papers have been misinterpreted as measures of success. None of them measure the success of a geographical region or an organization entity, and the first two merely measure an input to a complex long-term process. The output from this process includes startups only some of which go on to release revolutionary products and services, become profitable, and thus lead to higher productivity, employment and standard of living. The latter outputs are much more relevant measures of output than the inputs of VC funding and R&D spending or the outputs of patents and papers. 

     Policy makers, universities, and concerned citizens should be focused on output not input. Rather than evaluate regions or universities by the amount of VC funding they obtain or the number of startups they create, it would be better to focus on the number of profitable startups they create over the long run, or their contribution to new products and services. What new startups have been created, how old are they, what is their employment, and how did universities help these startups succeed?

     Universities should also focus on their contribution to the new products and services. What are those products and services, what types of benefits have they brought, and what was the contribution of universities in terms of academic papers, consulting, and other research activities? Because patents are not a good surrogate for new products and services, one must look closely at new products and services to find the contribution from universities.

    These types of analyses will be difficult to do and there will be time lags. But there are no shortcuts. Making universities and cities more innovative requires hard work, going far beyond the hype that permeates most current discussion of innovation.