Declining innovation productivity

Upon exploiting labour and natural resource advantage in fuelling economic growth, many developing countries including Bangladesh, Malaysia, Thailand, and Saudi Arabia are eying on innovation as the next frontier to sustain growth.  Innovation is perceived to be an endless opportunity for creating wealth. Investment in research is supposed to keep creating new ideas to fuel innovation driving growth. But it seems innovation mine is getting deeper and deeper. It's taking increasing efforts to face the reality of finding fewer ideas. Such reality is posing growth challenges to both advanced and developing countries.

Big ideas are getting harder to find. To maintain the growth rate of the innovation economy, exponential increase in research funding is offsetting declining productivity, raising a vital question: is the endless frontier of growth coming to an end?

With the savings from his wife's salary, Carl Benz financed the R&D in securing the first patent for inventing automobile in 1879. It did not take long for Mr. Benz to generate profitable revenue out of automobile production and sales. Similarly, out of the idea of emitting light by heating filament with electricity, Mr. Edison started the electric lighting business, requiring a very little investment for R&D. It seems that most of the low hanging fruits in the innovation orchard have already been picked up. Upon gobbling up $80 billion R&D investment, self-driving cars are yet to produce revenue.  Similarly, as opposed to the need of no risk capital to build Microsoft, software startups are eating up the largest chunk of risk capital finance. Such eroding R&D productivity is slowing down innovation-led growth, consequently encouraging advanced economies to pursue protectionism. On the other hand, developing countries are finding it very difficult to generate revenue from R&D investment-making middle-income trap inescapable.

Is the endless frontier coming to an end? In a report to the US president Roosevelt, Prof. Vannevar Bush in 1945 made a case that investment in scientific research leads to discoveries and inventions driving innovation-creating new wealth and jobs. Innovation in products and processes to produce them opens the opportunity of offering better quality products at lower costs increasing both consumer and producer surpluses simultaneously, driving economic growth. Based on the understanding that as scientific progression has no end, it follows that the investment in science will lead to the endless frontier of economic growth supporting invention and innovation. After World War II, in the USA, such compelling argument culminated into the formation of public funded research programmes fuelling the private initiatives of innovation and entrepreneurship. Most of the European and other industrial economies followed this model. And often in preaching development model to less advanced countries, pundits often prescribe investment in science and technology education and research to replicate this model.

Research productivity is primarily measured as the ratio between investment made for research and additional revenue earned by integrating research outputs in the form of ideas into products and processes to produce them. So, basically, the purpose of research funding is not limited to produce intellectual assets.

Once innovation used to be the creative spark of a solo genius. "It's certainly true if you go back one or two hundred years, like when Edison invented the light bulb," research finding states. But it is no longer the case, as "it's a massive piece of technology and one guy basically invented it. But while we think of Steve Jobs and the iPhone, it was a team of dozens of people who created the iPhone." The basic economic concept is that as you keep increasing funding for research, researchers will keep coming up with growing ideas, consequently getting more economic growth. Quite contrary to such common belief, researchers are disappointed to find that while research efforts are rising substantially, research productivity-commercially attractive ideas being produced per researcher-is declining sharply.

Declining research productivity is being offset by increasing the number of researchers. Basically, steep increase in research and development funding has been offsetting the decline in research productivity to keep the economy of the US and other western countries growing. The number of Americans engaged in R&D has jumped by more than twenty-fold since 1930 while their collective productivity has dropped by a factor of 41. As it's getting harder and harder to create economically attractive new ideas out of research, to roughly maintain growth, the strategy has been to throw more and more scientists at it. For example, in order to keep doubling the Silicon chip density over every 18 months, the research effort behind the chip innovations rose by a factor of 78 since 1971. It could be put in another way, the number of researchers required today to maintain innovative pace in microelectronics in the early 1970s is now more than 75 times larger. Other industries also exhibited falloffs in idea productivity. To maintain steady growth in agricultural yield during 1960-2015, the research expenditures directed at improving yields, including cross-breeding, bioengineering, and crop protection during that period rose "tremendously" - anywhere from a threefold to a more-than 25-fold increase, depending on the crop and specific research measure.

There is a common belief, particularly among developing countries, that programming knowledge and a few computers are good enough for starting a software firm. But, according to annual study of PricewaterhouseCoopers and the National (USA) Venture Capital Association, among venture capital investments, software is reaping the lion's share: $21.5 billion in 2014, or 42 per cent of all dollars invested, compared with $6 billion for biotechnology and $2.4 billion for industrial and energy companies. Why is so much risk capital needed to finance take off of software start-ups is an important question to look into. Software-intensive innovations now mostly focus on interpreting data produced by sensors of real-life scenarios. R&D effort in developing algorithms in processing those data to extract meaningful information is quite substantial. Often it takes years' of research work to develop the algorithm to process images in separating over ripped tomato from just rightly ripped ones. The funding need in supporting multi-year R&D effort of highly qualified people is quite substantial. But, once the algorithm is perfected, writing the code for automated execution of developed algorithms is quite negligible. Israeli software firms are leading equity fundraising. In 2017, Israeli software companies led all sectors in capital-raising, according to the survey, garnering $1.9 billion in 208 deals; as life sciences, companies followed closely behind with $1.2 billion raised, an increase of 41 per cent compared with the $850 million raised in the field in 2016. Leading the pack was SirinLabs, the Israeli-founded, Switzerland-based block chain firm known for developing a $17,000 secure smartphone for high-end clients, which raised close to $158 million in December 2017. Sirin Labs' new project is block chain-secured, open-source phone and PC called FINNEY. Bancor, an Israeli start-up that developed a virtual currency conversion platform, raised $153 million in June 2017.

Stanford's reported research findings conclude that research productivity fell, on average, about 10 per cent per year-requiring 15 times more researchers today than it did 30 years ago to produce the same rate of economic growth. Such declining research productivity is not only a concern for advanced countries but it is also a serious issue for middle-income countries who are aspiring to be advanced economies by leveraging innovation through increased investment in research and development. This rapidly declining innovation productivity is raising a vital question-is middle-income trap inescapable for developing countries? To turn the answer into NO-we need to engineer far smarter strategies and policies than ever before.

M Rokonuzzaman PhD is academic, researcher and activist on Technology, Innovation and Policy.

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