Tuesday, November 14, 2017

What is Essential? Measuring the Overdeclaration of Standards Patents

Standard essential patents are a relatively hot area right now, and seem to be of growing importance in the academic literature. I find the whole issue fascinating, in large part because most of the decisions are handled through private ordering, and so most of the studies are based on breakdowns.

One such breakdown occurs when companies declare too many patents essential to a standard. This happens if a company claims that too many of its patents must be practiced for the standard. The incentives for doing this are obvious: once declared essential, it is easier to argue for royalties or cross-licensing. But there are also important incentives against leaving patents out, for doing so may bring penalties in terms of participation in formation of the standard in the first place. Given that the incentives all align to disclosure, it is no wonder that some companies push back against paying. That said, if portfolio theory holds true--and I think it does in most cases--it doesn't matter much if there are 10 or 100 patents, as long as the first few are strong and essential. But that's an argument for another day.

Just how prevalent is this overdeclaration problem? One paper tries to figure that out. Robin Sitzing (Nokia), Pekka Sääskilahti (Compass Lexecon), Jimmy Royer (Analysis Group, Sherbrooke U. Economics), and Marc Van Audenrode (Analysis Group, Laval U. Economics) have posted Over-Declaration of Standard Essential Patents and Determinants of Essentiality to SSRN. Here is the abstract:
Not all Standard Essential Patents (SEPs) are actually essential – a phenomenon called over-declaration. IPR policies of standard-setting organizations require patent holders to declare any patents as SEPs that might be essential, without further SSO review or detailed compulsory declaration information. We analyze actual essentiality of 4G cellular standard SEPs. A declaration against a specific technical specification document of the standard is a strong predictor of essentiality. We also find that citations from and to SEPs declared to the same standard predict essentiality. Our results provide policy guidance and call for recognition of over-declaration in the economics literature.
This is an ambitious study. The authors used data on SEP declared patents (for the ETSI 4G LTE standard, among others) that were independently judged* by technical experts. They then performed regressions to determine whether there were specific factors that had an effect on being "actually" essential. One key finding was that when the patent was declared for a specific standards document, it was much more likely to be deemed essential than if it were declared for the standard generally. My takeaway is that when the specifics are outlined, companies know what their patents cover, but when faced with a broad standard, they will contribute anything they think might be close.

They also found that patents later assigned to NPEs were not more likely to be nonessential. Similarly, while firm size and R&D investment had a statistically significant effect on the likelihood of being actually essential, that effect was so small that it was practically insignificant. Finally, they find that longer claims (which are theoretically narrower) are, in fact, less likely to be essential.

As with other papers, there is a lot of data here that is worth looking at. But the final conclusion is an interesting one, worth carrying over to other papers: the traditional measures that economists use to judge patent value (such as citations) do not predict whether a declared patent will be technically essential. This is growing support for paper findings that question the use of these metrics.

*The authors explain the trustworthiness of their data. I'll leave it to the reader to decide whether it holds up.

Sunday, November 12, 2017

Do Machines, And Women, Need A Different Obviousness Standard?

This blog post addresses two different articles that might at first blush seem to be very different. The first is Ryan Abbott's new article Everything Is Obvious, which explores the implications of machine-generated IP for the nonobviousness standard of patentability. Abbott argues the inventiveness standard should be adjusted to take into account the new reality that inventors are frequently assisted by machines or, in some cases, are machines. The second article is Dan Burk's Diversity Levers, published in 2015 in the Duke Journal of Gender Law & Policy. In the article, Burk argues the standard for nonobviousness should be adjusted to take into account the unique mindset and institutional situation of female inventors. (To be clear, Burk is not coming at this issue out of the blue. He has previously written about feminism in collision with copyright, arguing that copyright can be used to suppress feminist discourse).

Abbott's thesis is that, in comparison to machines, humans are all a little less skilled, so a human-based obviousness standard will necessarily lead to too many patents if machines are commonly employed. Burk's point is that, in comparison to men, women are typically more risk-adverse, so a male-based obviousness standard will necessarily lead to too few female-invented patents.

Tuesday, November 7, 2017

Tracking the Sale of Patent Portfolios

Finding out about patent sales and prices is notoriously difficult, yet critically important for patent valuation. Brian Love (Santa Clara Law), Kent Richardson, Erik Oliver, and Michael Costa (Richardson Oliver Law Group) have helped us all out by posting An Empirical Look at the "Brokered" Patent Market to SSRN. Here is the abstract:
We study five years of data on patents listed and sold in the quasi-public “brokered” market. Our data covers almost 39,000 assets, an estimated 80 percent of all patents and applications offered for sale by patent brokers between 2012 and 2016. We provide statistics on the size and composition of the brokered market, including the types of buyers and sellers who participate in the market, the types of patents listed and sold on the market, and how market conditions have changed over time. We conclude with an analysis of what our data can tell us about how to accurately value technology, the costs and benefits of patent monetization, and the brokered market’s ability to measure the impact of changes to patent law.
The article provides some really useful data about brokered patent portfolios - that is, groups of patents sold by brokers rather than "secretly." While brokered transactions are also confidential, their public offering makes them more visible than company to company direct transactions.

The information is quite interesting: the number of patents in each portfolio is quite small - most are less than a dozen. The offering prices have dropped over the last five years (shocker). Operating companies sell a lot of these, and PAE's buy them (something I pointed out five years ago in Patent Troll Myths, and which gave rise to the LOT Network framework- in fact, Open Innovation Network is a now a key buyer). There is a lot more data here, and I don't want to preempt the paper by just repeating it all - it's worth a look. I will note that, as the authors point out, this isn't the whole market and they can't accurately capture sale prices, so they use a "spot check" to estimate what they expect them to be.

Having introduced the paper, I do want to ask, like every good academic, "But what about my article?" Here I'll note a couple takeaways from the paper that bear on my own work on this subject, Patent Portfolios as Securities. First, the first portion of that paper was dedicated to the notion that buying and selling portfolios isn't just about patent trolls. I told anecdotes and used some data, so I'm glad to see a broader based survey provide stronger support for that assertion. Second, my argument was that treating portfolios as securities would force more transparency in sales and valuations. This paper's results support this notion in two ways. Itt shows how difficult it is to get any kind of transparency, even when you have brokered transactions. It also shows how easy it would be to jump from a brokered transaction to a more transparent clearinghouse that might provide the type of valuation information that market participants crave. I view this paper as a useful followon to my own, and hope to write more about how it might bear on the treatment of patent portfolios as assets.

Anyone interested in real-world patent market transactions should give this paper a read. It provides a view into the system that we don't often see. I found it really useful.