Startups of the near future: fundamental research

Startups of the near future: fundamental research

The title looks paradoxical: everyone knows that fundamental research, firstly, takes a long time to finish, and secondly, is poorly monetized. These characteristics are directly opposite to those implied by the directions of work of a successful startup.

It’s true if we rely on the usual, everyday understanding of the term "fundamental research", but there are other definitions (for more details, continue reading). Furthermore, the situation is changing rapidly. In any case, fundamental research can include publications on topics that bring huge profits. A startup that can show success in the field of fundamental research has a chance to monetize its achievements by selling them to a giant company that is able to use the research for purely applied purposes, which will ensure high profits for startup investors.

This is not demagogy: there are many discoveries made by small groups or even individuals, on the basis of which new economic branches have emerged. One of the most impressive examples is the famous Diffie-Hellman protocol, which has made a real revolution in cryptography. Without this protocol, neither cryptocurrencies, modern electronic signatures or many commonly used encryption methods would be possible. Without exaggeration, this protocol was the first major breakthrough in cryptography in several thousand years. It’s even more impressive considering the fact only three people took part in its creation (besides Diffie and Hellman, the authorship also belongs to Ralph Merkle; before them, Malcolm Williamson expressed similar ideas). Yes, they were talented established experts in their field, but the efforts of these few people were enough to change the world in a way that neither ancient rulers nor modern magnates had dreamed of. The first commercially significant encryption algorithm (also suitable for creating electronic signatures) based on the Diffie-Hellman protocol, known as RSA appeared just a year after the publication of the protocol description.

We can fairly call this example a rare exception, because there are few such successful cases, but there are similar ones. Well-known to chemists, an effective and in-demand chromatographic method of separation and analysis of substances, invented by Mikhail Tsvet, could be developed even by a schoolboy, since there is nothing complicated about it. There is nothing complicated about the idea of blockchain — the second most important basis of cryptocurrencies along with the Diffie-Hellman protocol. The technology of so-called zone melting, an effective method of purification of many substances proposed by William Pfann in the middle of the last century, is also fundamentally simple; but without this technology, it would be impossible to obtain the substances vital to the modern electronics industry.

What links these examples and allows them to be classified as basic research — rather than applied research, which seems more logical at first glance? That these inventions and discoveries are successful developments of methods, techniques, approaches, tools and concepts — not final products. It is clear that from the point of view of "pure science" that even cryptography can be considered a section of applied mathematics, without separating it into an individual discipline. But for investment and business, something else is important — the economic and legal advantages of the methods and end products in comparison with each other (as well as their comparative disadvantages, of course). And, if the earlier methods and concepts lost out to the products, the situation ceased to be unambiguous in the last century.

The benefits of end products from a business perspective are:

1) Simple, long-standing and well-developed monetization. The final product is something that can be sold to the consumer in the form of a product or service in an existing market or by creating a new market. The basis of classical business; when people talk about business, they usually mean a device of the commercial process — the production and sale of the final product.

2) Good legal protection. Product solutions, if they meet simple and clear natural requirements (sufficiently original, first of all), can be protected by patent and/or copyright law under standard procedures in all developed countries.

3) Predictable payback. If the final product turns out to be in demand at a price that is profitable for its producer and seller, the breakeven point and further profit are usually reached fairly quickly and within a time frame that can be calculated in advance with good confidence. This, of course, is very important for business.

The disadvantage is the well-known narrowness of product solutions (they usually lose their advantages when transferred to other areas). In addition, even a successful grocery business is usually low-margin — or has a high entry price. In other words, for high profitability (and, at the same time, scalability of the commercial process) large investments will be required — and this condition in itself does not guarantee anything. The exceptions, of course, are just successful product startups or projects close to them, such as famous backpack Bobby from the Dutch company XD-Design (this backpack appeared as a result of a successful crowdfunding campaign, which was launched in April 2016 on Kickstarter and Indiegogo and raised £ 872,607 — much more than what was needed to implement the project). But, no matter how successful they may be, these product projects rarely bring grandiose results. Even such a well-known example as the iPhone by Apple was still created by a large international corporation with millions of admirers and an established engineering and manufacturing base. Few others could pull something like this off; even a giant like Nokia failed to do the same (although the company tried: its iconic N900 smartphone can be seen as an appropriate attempt).

The advantages of fundamental research (with new effective concepts and methods as a result) for business are different:

a) High versatility. The new effective method can be implemented in hundreds and thousands of different popular products. The monopoly of such know-how (at least temporarily) gives an important competitive advantage in a very wide field.

b) High marginality. The new effective methods and concepts can fundamentally change the economic terrain, up to the replacement of entire industries. Such concepts as "closing technologies" and "disruptive innovations" appeared as a result of the study of the processes that begin in the economy after the introduction of new efficient approaches, and the enormous profits that can be made are not necessarily related to production: it’s enough to confidently foresee the consequences of introducing new concepts to make the corresponding highly profitable investments.

c) Low entry price. It’s clear that this is not true for all fields — research in nuclear physics, for example, is by no means one of those that require small investments (not even to mention the other problems associated with government regulation of nuclear research). But, for example, mathematical research and a number of other topics still require a very modest material base for their implementation.

At the same time, fundamental research also has significant drawbacks; firstly, there is a high unpredictability of results: you can study a topic for a long time, conduct experiments, conduct experiments, develop concepts... and in the end you will not get anything valuable. Yes, for science, "a negative result is also a result"; but that's not what the business needs.

Secondly, the results of fundamental research, even commercially promising ones, have been poorly monetized until recently. Now, of course, the situation has changed: as noted above, the very fact of the appearance of such results can be used for confident and highly profitable investment. A large profit can also be obtained by the banal sale of rights or even the entire startup to some giant. Nevertheless, these obvious methods cannot be called easy to implement: they are not standard and guarantee nothing — in contrast to the simple implementation of the product on the market, which in this sense is much more predictable.

Finally, the results of fundamental research are much more difficult to protect legally. Patent law of different countries has very different attitudes to mathematical algorithms. If a really perfect invention can usually be patented without any excessive troubles, then a discovery is usually impossible to patent. The boundary between these concepts is vague, and bypassing or infringing a patent in basic research is usually so profitable that those interested in using it do it without much hesitation. Therefore, many large corporations simply conceal achievements of this kind, having no other way to reliably protect their rights. However, the practice of such violations and retaliatory concealment, by its very nature, makes it difficult for the authors of new methods, who have no opportunity to profit from the implementation of the results of their research by their own efforts. In other words, researchers face an unpleasant dilemma: to sell their achievements secretly (with understandable risks), or to try to patent them, risking something else: either get a refusal, or to accept that the patent will be repeatedly violated. And the more significant the achievement — for example, closer to a fundamental discovery — the greater the probability of both rejection and infringement (if the patent is nevertheless obtained).

Therefore, it’s not surprising that until recently fundamental research was not particularly popular with investors, because all their very tempting prospects were overlapped by obvious risks and almost inevitable problems with the sale or implementation of even excellent results (which still need to be obtained). However, due to the fact that there are almost no results of basic research on the basis of final products that can be produced, and, on the other hand, due to the fact that the procedure for monetizing the results of basic research has become easier and more reliable, basic research has become increasingly attractive to investors. This is a classic growing market: demand is increasing, but supply is not keeping up with it.

In practice, this means the following: if a startup is dedicated to the release of the final product based on its own, original methods and technologies — which are successfully patented, and these patents are highly appreciated by experts — such startup can be a very successful investment (of course, if there are no important indications to the contrary). If we are talking about a project that involves only basic research (albeit with a well-understood application of the expected results) — investment in it can be recommended only to those who are well versed in the relevant topic, or are ready to take a significant risk — relying on a significant profit in the future.