Patent Data – The Modern Investor’s Crystal Ball 06/03/2017 by Intellectual Property Watch 2 Comments Share this:Click to share on Twitter (Opens in new window)Click to share on LinkedIn (Opens in new window)Click to share on Facebook (Opens in new window)Click to email this to a friend (Opens in new window)Click to print (Opens in new window) The views expressed in this article are solely those of the authors and are not associated with Intellectual Property Watch. IP-Watch expressly disclaims and refuses any responsibility or liability for the content, style or form of any posts made to this forum, which remain solely the responsibility of their authors. By Sirena Rubinoff, Morningside IP What if there was a crystal ball that could tell you where and when to invest your money? It sounds like science fiction, but engineers at MIT have actually developed a formula that can predict future events in tech development. The formula is based on a combination of big data from patent applications and smart analytics which, when put together, can estimate how fast a technology is advancing. Why patent applications? If you want to know where technology is headed, a great place to look is in a patent application database like the USPTO. One of the qualifications for getting a patent granted is “novelty,” which means new, similar innovations won’t appear anywhere else. Once enough data is collected from the database, it can be used to map out and predict unique advancements in specific areas of technology. The magic formula With nearly 3 million patents filed in 2015, there is no lack of data – in fact, it’s quite the opposite. The only way to make sense of big data like this is to create an algorithm that can extract relevant information from the massive set. An MIT team did this by writing an equation that could calculate a technology’s rate of improvement based on two key factors: Average Forward Citation – the number of times a patent is cited by other subsequent patents. Average Publication Date – newer patents are more likely to represent advancing technologies. Interestingly, the MIT engineers discovered that the number of patents related to a specific technology doesn’t have any correlation to actual advancement in that technology. For example, you might think that a technology with thousands of new patents would represent greater progress than a tech with just a handful of new patents – but this doesn’t seem to be the case. One explanation is that the overall rate of improvement is not highly impacted by slightly new inventions and, generally speaking, when a technology starts to mature, incoming patent applications begin representing smaller and smaller innovations. For example, there’s a multitude of new patents in battery technology, but many are related to sub-categories of different types of lithium battery (e.g. lithium-ion, lithium-polymer, lithium manganese dioxide, lithium-iron disulfide, etc.). While important, these very minor innovations are not going to have a major impact on the overall advancement of battery technology. What were the results? MIT engineers used the equation above to study 28 different technologies and found: The biggest technological advances were in optical & wireless communications, 3D printing and MRI technology. The smallest technological advances were in batteries, wind turbines and combustion engines. Based on their findings, the MIT engineers predicted that technology in online learning and digital representation were going to take off, while tech in food engineering and nuclear fusion will slow down. Can I get in on this? MIT’s ‘crystal ball’ equation is not “something to hand out to the masses to play with,” said Chris Benson, a former graduate student in MIT’s Department of Mechanical Engineering who helped develop the predictive formula. He sees it primarily as a tool to help someone working in a given technology “understand what the future technological capabilities that they’re interested in are.” It’s likely that government and industry labs, venture capitalists and startups will all want to take advantage of the predictive service Benson has described. After all, accurate results could mean a huge payoff for investors and, in the government sector, the right investments could lead to better quality of life for everyone. But what about those who cannot gain access to MIT’s assistance? Online tools to make your own prediction There are other tools you can use to glean information from patents. One of the most popular is called a patent map. This tool helps to identify patterns and trends through the use of visual representations of interrelated areas of intellectual property. You can create your own patent map here and use it to view interconnection for up to 100 patents. Patent maps can get very complex very fast, so check out this Guide by IPVision, MIT’s patent mapping company, for more details. Use the data to your own benefit In today’s fast-paced world of tech development, the correct analysis of patent applications could make all the difference in determining where to invest your time and money. Before you move forward with your next big project or investment, take a look at what the patent data has to say about the technologies involved and their rates of innovation that can be predicted for the future. Author bio: Sirena Rubinoff is the Content Manager at Morningside IP. She earned her Masters and undergraduate degrees from the Medill School of Journalism at Northwestern. After completing her graduate degree, Sirena won an international fellowship as a Rotary Cultural Ambassador to Jerusalem. Sirena specializes in topics related to patents & IP, the legal industry, and the translation industry as a whole. Image Credits: Morningside IP Share this:Click to share on Twitter (Opens in new window)Click to share on LinkedIn (Opens in new window)Click to share on Facebook (Opens in new window)Click to email this to a friend (Opens in new window)Click to print (Opens in new window) Related "Patent Data – The Modern Investor’s Crystal Ball" by Intellectual Property Watch is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.