• Alec Sorensen

A Brave New World: Succeeding in the Intangible Economy

Updated: Jan 21, 2019



2018 was the year of data. Between large-scale breaches, concerns about ownership and privacy, and record valuations for data-intensive tech companies, data secured its place as a critical asset in the global economy. The Economist heralded this change with a bold cover story claiming data had replaced oil as the world's most valuable resource.

But the importance of data belies the emergence of another resource with even more far-reaching implications - Intellectual Property (IP).


For the first time ever, a company's most valuable asset is not its plant and equipment, or its inventory, or even its employees.


Instead, up to 60% of company valuation is now driven by intangible assets. These are the patents, processes, and trade secrets that companies spend millions of dollars to develop and that comprise the backbone of our knowledge economy. But while companies have sophisticated strategies to manage their other assets (inventory, human capital, etc), IP remains under-served.



Growth in new IP combined with the emergence of machine learning and artificial intelligence has created an enormous opportunity. In 2019 and beyond, forward-leaning companies will have tools to develop data-driven strategies to generate new revenue from existing IP and to access cutting-edge IP from universities, government labs, and start-ups to build better, more differentiated businesses.


Data on patenting behavior of top companies confirms the close relationship between IP and innovation. Comparing Forbes’ most innovative companies to the rest of the Fortune 500 shows the number of patents per dollar of revenue is 200% higher for these innovation leaders than for the rest of the market.


Even oil companies – not necessarily known for innovation – are benefiting from a strategic focus on IP. As part of their efforts to increase exposure to renewables, one large O&G operator recently kicked-off a data-driven portfolio analysis to identify IP focused on energy efficiency. The company found a set of patents that it spun off into a successful startup that secured an eight-figure term-sheet. As a result, the oil company gained access to a $10B market while still guaranteeing their own access to the technology and lowering its unit cost.



With so much upside from deals like these, why do most companies fail to get value from their IP?


The answer is twofold. First, patents are complex documents and most large companies own hundreds, if not thousands of patents. Even companies with smaller portfolios lack the bandwidth to effectively evaluate their IP. Second, companies have historically lacked visibility on IP market dynamics and on which partners to license or commercialize their technology.


1) Bandwidth Constraints


Patent documents are an invaluable tool to develop a data-driven commercialization strategy. However, patent documents are technical and full of legalese, making it difficult and time-consuming for experts and lay-people to evaluate IP. Additionally, there is no universally-accepted approach to evaluating IP or calculating the strength of a patent relative to all other patents in its field. Current approaches range from simply counting the number of patents (we recently saw this in a $100M due diligence) to using regressions to calculate a price. Without an accepted approach to evaluation, companies often struggle to implement systematic approaches to evaluate and prioritize their IP assets.




With new machine learning models, we can show large portfolios using intuitive visualizations and simple relative valuations

2) Limited Visibility


Even if organizations do evaluate their own IP, they often struggle to make smart IP decisions in an opaque, inefficient market where there is little public information on macro patenting trends and even less information on which assets are on the market and which types of technologies companies are looking for. Without this visibility, companies fail to commercialize 95% of IP and technology scouts miss technologies that don’t come out of well-known institutions like Stanford, MIT, etc. Historically, the alternative has been to use law firms, brokers, or consultants, which are prohibitively expensive and have a mixed track record.


More recently, organizations have attempted to build online clearinghouses to help match IP supply and demand. Some have identified successful business models by focusing on a specific region (e.g., Ocean Tomo Bid-Ask), or strategic purchasers (e.g., RPX). Most IP clearinghouses; however, have failed to generate sufficient transaction volume because online clearinghouses do not address the fundamental challenges to IP transactions and commercialization. Even if you can bring together both sides of the market, sellers still need a way to find the RIGHT buyers for a given technology, while buyers need to find the RIGHT technology and evaluate it against all other IP for a given technology.



Tradespace has focused on the tools companies need to make the smarter decisions about developing, commercializing, and investing in intellectual property.


We use machine learning to find patterns in over 50 million patent documents. These techniques let us identify which data points best predict value, defensibility, and marketability. This helps companies decide which assets to prioritize for patenting, commercialization, and acquisition. We've found that this type of systematic, data-driven approach to IP resource management and commercialization allows organizations to improve outcomes by benchmarking impact against other business units, competitors, or the market writ large.


Furthermore, we use predictive analytics to identify which companies are best-suited to commercialize a technology. In addition to providing commercialization targets for IP generators, our intuitive search platform to allow technology scouts quickly find the strongest IP in any given field, and actively connects interested buyers and sellers. We have seen that that if you connect two organizations around the right piece of technology, the likelihood of a successful outcome is extremely high.


Bringing it all together


What does all this mean for companies? As pressure to optimize IP grows, companies must now find ways efficient ways to make sense of their own portfolios and effectively navigate the market for technology commercialization. With more data available than ever before, companies can now develop comprehensive, data-driven IP strategies. Advances in data science and tools like Tradespace make it easy to execute these strategies. Still, technology alone isn’t enough. Corporate leaders must embrace the new role of IP in our economy and devote real resources to developing, protecting, and commercializing their most valuable assets.

ABOUT THE AUTHOR

Alec Sorensen

A former management consultant to Fortune 500 companies, Alec founded Tradespace to speed innovation and revolutionize the way companies get value from their IP. Using data on 100M patents and advanced analytics, Tradespace makes it faster and easier for companies to source new technology, get innovations to market, and make smarter technology decisions.


Before launching Tradespace, Alec spent five years with Avascent, the top defense and aerospace consulting firm. He led engagements focused on strategic growth, commercialization and M&A. In addition to his corporate work, Alec worked closely with the Canadian Government to reshape their IP policy to drive innovation. For more information, contact asorensen@tradespaceinc.com

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