Reducing USPTO’s backlog to 300,000 cases. 3.3 patents per 10,000 Chinese inhabitants. Goals in the IP world are often presented in the form of numerical targets.
This is not surprising and is in fact a good thing. Though not exactly a new development, the recent successes of companies like Google and internet stars like Nate Silver have raised awareness of the importance of quantitative data and how such information, used and manipulated in the right way, can lend important insights.
|Nate Silver succesfully predicted the 2008 and 2012 US presidential elections using rigourous data analysis|
In the increasingly complicated world of IP policy, the use of numbers and data to understand the effects of laws is much welcomed. For example, researchers looking at issues such as patent quality in China have made their cases looking at measurable factors such as how often Chinese patents are cited or how likely they are to be maintained. These studies are likely more useful, though less dramatic, than an anecdote about a company giving up on the Chinese market because of concerns about infringing on a junk patent, though as any lawyer who tries cases before a jury will tell you, a good story can often win the day.
Law and policy is ultimately about incentives, and the use of questionable numerical targets can sometimes induce the wrong behaviour. For example, the USPTO utilises a count system which awards examiners for taking various actions. Previously, the system gave examiners points and ultimately extra compensation for each new case they take, including requests for continued examination (RCEs). Some argued that this encouraged overzealous initial rejections of patents. When David Kappos took over as USPTO director in 2009, one of his first tasks was to revise this system , which among other changes reduced the number of points granted for RCEs.
China’s use of numerical goals in formulating IP policy has also been much discussed and criticised. Though SIPO appears to be focusing more on encouraging quality patents now that China has reached its goal of being the world’s biggest patent filer, some point out that there is still room for improvement. For example, Anna Mae Koo of Vivien Chan & Co tells Managing IP that there is pressure for Chinese courts to split up cases because judges are measured by how many cases they try. Thus, if a brand owner brings suit for both trade mark infringement and unfair competition, the matter may be handled as two separate cases, increasing both time and cost to the parties.
Similarly, she explains that targets for adjudicators at the Trademark Review Adjudication Board (TRAB) mean that they must render on average 10 decisions a day. Though judges around the world are no doubt familiar with having an overburdened docket, this inevitably limits the amount of time and effort that they can spend on each individual case.
This issue is by no means limited to intellectual property; all around the world, debates are raging over how to properly measure everything from school achievement to the usefulness of austerity measures. That said, in the myriad of IP-related policy discussions, such as patent quality and how to (or even whether governments should) stop patent trolls, what are some of the best and worst forms of data to measure progress and formulate policy?