Data-driven decision-making can greatly help software companies when facing uncertain patent applications and outcomes.
If you work at a software company and you have oversight into your patent portfolio, you’ve likely seen it become harder to obtain patents on your company’s software in the last few years. That is because in July 2014, the U.S. Supreme Court issued a decision titled Alice v. CLS Bank International, in which a particular software patent was found to be ineligible for patenting consideration. The standard by which the determination was made, however, was less than clear. As a result, it is much more difficult to determine in advance whether a software idea will be found eligible for patenting (a threshold question) by the U.S. Patent and Trademark Office (USPTO).
Although the USPTO has been rejecting more software patent applications as ineligible, the general speed of product releases and competition in the software industry means you may have noticed a greater pace of innovation at your company, possibly corresponding to ideas being submitted more frequently by your software development team for patent consideration. What can be done to bridge this gap between innovation and intellectual property protection?
Some companies are filing fewer patent applications, saving money in the short term but leaving potentially patentable software ideas at risk of being copied by others. Other companies are filing about the same number of patent applications, but have devoted their patent budget to software technologies that they feel are more likely to avoid a patent eligibility rejection. Is there a better approach? Yes: using patent analytics to guide decision-making during the patenting process.
Patent analytics is the process of analyzing large amounts of patent office data (e.g., past patent filing and history data from the USPTO), especially in order to evaluate and compare the performance of individual patent examiners or divisions at the USPTO. Patent analytics services are commonly provided by third-party vendors that include data scientists and lawyers on staff. These vendors have developed certain suites of analytic tools for use by both in-house and outside counsel, while also developing specific sets of analytic tools designed for use by one or the other only.
As a relatively new area of patent counseling, patent analytics can be helpful when addressing the gap between selecting software ideas to submit for consideration for patenting and mitigating software patent application rejections at the USPTO. Patent analytics greatly supplement the traditional approach to patent lawyering – namely, lawyers relying solely on their legal skills and experience, including that of their firm colleagues, when counseling clients on how to deal with a patent rejection or a particular patent examiner. This old model became particularly insufficient after the Alice decision, because limited guidance remains available as to what software is considered eligible for patenting.
Analytic tools can be used to tweak a patent application as it is being prepared, in order to target more favorable examining units by the USPTO. For example, certain analytic tools can identify the likelihood of a patent application with a particular patent claim being assigned to different USPTO examination centers. They can go further and suggest alternative patent claim terms in order to avoid examination centers that have lower allowance rates, longer examination times, greater numbers of Office Actions (e.g., rejections), or a higher subject-matter-eligibility rejection frequency. These tools help increase the likelihood that the associated patent application gets assigned to an examination center that has higher allowance rates, shorter examination times, fewer Office Actions, or a lower subject-matter-eligibility rejection frequency. Depending on the type of technology being analyzed, the tools have varying accuracy rates, which tend to be around 70 percent for software patents. It should be kept in mind – a 70 percent chance of increasing your allowance rate and decreasing your number of rejections and potential examination time is better than no chance taken at all.
Armed with an idea of how a newly filed patent application will be treated by the USPTO, you can better budget for the cost and time it will take the patent application to undergo examination at the USPTO. You can also decide to pay for an expedited examination of the application, if you determine, for example, that the patent application is likely to receive sufficiently favorable examination by the USPTO, or to avoid examination centers that have unacceptably long wait times.
After the filing of any patent application, and during its examination, analytic tools can be used to identify your assigned patent examiner’s allowance rate, average number of Office Actions taken, and win rate on appeal. These numbers are particularly helpful when used in comparison with the rest of the examiner’s examination unit (to see if you have a favorable examiner) and when making on-the-fence decisions – should I appeal, should I file a continuation application, etc. For applicants facing a subject-matter-eligibility rejection, analytic tools can be used to identify applications where similarly situated applicants overcame a rejection in front of the same examiner, including reviewing those successful arguments when preparing your own.
The availability of patent analytics could not have come at a better time for software companies. With patents on software being harder to obtain than at any time in recent history, patent analytics provide an important additional data point to help companies make more informed and successful decisions with respect to their software patents.
Ahsan Shaikh is a partner at McDermott Will & Emery. He focuses his practice on strategic patent portfolio management and client counseling in the areas of software, computer hardware, internet technologies and medical devices.
Published July 6, 2018.
