By Prof. Sean Tu (WVU) with Chris Holt (VP at LexisNexis IP)
Beforehand, I revealed a analyze which established out to figure out how examiners issued patent apps. This authentic analyze concentrated only on issued patents, and coded around 1.5 million patents issued January 2001-July 2011. The main limitation on this analyze was that it concentrated only on allowed patents. Accordingly it suffered from a “denominator” challenge. Specifically, it was tricky to figure out how examiners really behaved without having being aware of how many pending apps they experienced in their docket, as effectively as how many apps went abandoned.
6 many years afterwards, I have followed up on this analyze by collecting information and facts concerning not only the examiners’ issued patents, but their abandoned patents as effectively as the total range of office environment actions issued by each individual examiner with an lively docket as of June 2017. Utilizing LexisNexis PatentAdvisor, we ended up able to pull the dockets of all lively examiners (each individual examiner with a pending application as of June 8, 2017). Accordingly, this analyze captures 8,537,660 office environment actions, 2,812,177 granted patents and 1,255,552 abandonments from 9,535 examiners which include from January 1, 2001 to June 8, 2017.
This new dataset is both equally additional detailed and additional narrow in comparison to my former analyze. Nonetheless, I consider, this information and facts is additional handy to practitioners nowadays mainly because it displays what is heading on at the office environment at this second in time. It excludes former examiners who have retired or are no lengthier at the PTO. These data exclude examiners with any pending instruction academy instances (Technological innovation Heart 4000) in their lively docket. Accordingly, these data filter out the most junior examiners.
From this dataset, we develop two new examiner metrics the: (1) Office Steps for every Grant Ratio (OGR) and (2) Office Motion for every Disposal Ratio (ODR). The OGR rating only divides the examiner’s total range of Office Steps by the range of issued patents. The ODR rating divides the examiner’s total range of Office Steps by the sum of the range of issued patents and abandonments. From these two scores, we can figure out if examiners are investing their time crafting a good deal of Office Steps or granting patents.
As revealed in Figure 1, in general, there is a vast range of OGR scores across the United States Patent & Trademark Office (USPTO), normally ranging from around .2 to 23. Moreover, in general, most examiners have an OGR of 3. or down below. Examiners with instruction academy instances (Technological innovation Heart 4000) have been filtered from these data.
As revealed in Figure 2, these OGR scores approximately correlate to allowance prices, but there are a major range of examiners that do not have an allowance rate that corresponds with OGR scores. Predictably, these examiners with a lower OGR have a higher allowance rate (these examiners who grant patents within just 1 Office Motion will almost always grant additional patents). In contrast, examiners with a higher OGR rating have a lower allowance rate, that is, these examiners who publish many office environment actions in advance of allowance will have lower allowance rate. Accordingly, at the periphery, allowance rate and OGR correlates reasonably effectively. This romance involving OGR and allowance rate, nonetheless, is not beautifully linear, and this is primarily correct for these examiners with an OGR rating involving 2. and 4.9.
Moreover, there are additional examiners with higher OGR scores in Technological innovation Facilities 1600 and 1700, which may perhaps mirror the complicated nature associated with biotechnology and chemical patents. Specifically, of the examiners that have an OGR rating of 10 or additional, 17.6% and 12.8% arrive from 1700 and 1600, respectively. In contrast, there are a higher range of examiners with lower OGR scores in Technological innovation Heart 2800, which corresponds to Semiconductors, Electrical and Optical Devices and Elements. Specifically, 64% of examiners with an OGR rating of lower than 1. arrive from Technological innovation Heart 2800.
Apparently, when damaged down into Workgroups, this analyze finds that there can be huge variation in OGR scores. For case in point, Figure 3 displays that in Technological innovation Heart 1700 (Chemical and Elements Engineering), Workgroup 1780 (Food items, Miscellaneous Posts, Inventory Substance) has a disproportionate range of examiners with higher OGR scores when in comparison with other Workgroups within just 1700. In contrast, Workgroup 1750 (Photo voltaic Cells and Electrochemistry) has a disproportionately higher range of examiners with lower OGR scores when in comparison with other Workgroups within just 1700. Likewise, in Technological innovation Heart 3600, Workgroups 3620 and 3680 have many examiners with higher OGR scores, which is unsurprising given that both equally Workgroups encompass “Data Processing: Economical, Business Practice, Administration, or Value/Selling price Determination” or business procedures type apps.
This paper confirms many of the conclusions from my former analyze. Specifically, junior examiners have a significantly lower allowance rate and a significantly higher OGR rating than their additional skilled counterparts. This is unsurprising given that junior examiners will have written only a couple Office Steps (generally a lot less than 500) and have only allowed a couple instances. Nonetheless, this analyze also goes significantly even further than my former analyze. By on the lookout at allowances and abandonments as a functionality of Office Steps written, we can get an plan of the common rate of patenting at the patent office environment and how these prices differs amongst diverse engineering centers, workgroups and artwork units. This analyze displays how examiners commit their time, either crafting office environment actions or letting instances.
This analyze focuses on in general patent office environment traits as effectively as traits at the engineering centre and workgroup levels. PatentAdvisor’s “Examiner Time Allocation” metric can also be utilised to forecast the time and cost demanded to get hold of a patent and is based on every single distinct examiner’s entire body of function.
As with my former analyze, I note that there is no “ideal” patent allowance rate. It is probable that both equally populations of examiners with lower and higher OGR scores are accomplishing an superb job of rejecting “bad” patents and letting “good” patents. This analyze provides perception into how “average” examiners behave in a individual engineering team. One particular argument may perhaps be that examiners who are two or a few typical deviations from this “average” must be scrutinized at a higher diploma.
A full draft of “Office Steps for every Grant Ratio (OGR): A New Metric for Patent Examiner Activity” is readily available on SSRN at: https://papers.ssrn.com/sol3/papers.cfm?summary_id=3100326.