A Production View on Patent Procurement

By Ian C. Schick, PhD, JD, CEO & Co-founder of Specifio (first posted on blog.specif.io)

When we think of a “production environment”, a law firm patent practice is not usually the first thing that comes to mind. But why not?! Patent practices are highly process-oriented and they certainly involve “manufacturing” work product, primarily in the form of new patent applications and office action responses. This article discusses how, with a production view on patent procurement, exploiting the principles of lean production can be a compelling way to adapt to tough issues presently roiling the patent ecosystem.

The idea of commercial manufacturers providing completely-handcrafted products went out the window, for the most part, during the industrial revolution (the first one). To be sure, examples of prideful handiwork can still be found today, like with Amish woodworking or specialty items like, say, Rolls Royce automobiles. Speaking of cars, Rolls Royce and BMW both had record sales last year. Rolls Royce automobiles are assembled by hand and are of the finest quality. BMW automobiles are also very high quality, but manufactured by employees, automation, and OEMs working in concert. Rolls Royce sold 4,107 vehicles in 2018 (0.082 vehicles per employee), while BMW sold over 2.49 million vehicles (18.5 vehicles per employee). If these car companies were law practices and the cars were patent applications, which one would you want to model your own practice after?

We all know the Rolls-Royce approach to patent procurement–more or less the way it’s been done for the past 100 years. In today’s hyper-competitive patent market, however, having a more BMW-style practice may prove key to prospering (or even to survival in some cases). So what would a BMW-style patent practice look like? More specifically, how can patent practices modernize through lessons learned in traditional production industries–where decades of intense competition has resulted in process optimization evolving into a science?

Some of the most successful patent firms today are leveraging ideas from “lean production” to maximize their competitive edge. Lean production is a convenient framework for thinking about operations and possible improvements. It is a school of thought that originated in the Japanese automotive industry in the 1990’s. The basic idea is to maximize the creation of value for customers while eliminating waste. Here, “value for customers” means any action or process that a customer will be willing to pay for. Parts of the production process that do not add value are considered waste.

Several interrelated concepts are central to the lean production ethos. They include minimizing waste, just-in-time production, kaizen (continuous improvement), and cell production. Each of these is explained below in the context of patent procurement.  

Minimizing waste

Waste in patent procurement can take on many forms. At a high-level, however, waste can be categorized as overprocessing, overproduction, or defects.

Overprocessing

There is a waste of resources if an expensive resource (e.g., an attorney, a patent agent, a paralegal, a secretary, etc.) is used for a task when another resource could complete the task just as well. At first blush, this sounds a lot like the classic mantra of law firm leverage. However, there are things that can be done besides delegating talks to lesser-trained individuals to avoid overprocessing. For example, tasks can be decomposed into subtasks and those subtasks can be examined for further delegation even if the larger task is traditionally handled entirely by the more expensive resource. Also, in some cases, emerging technologies in automation may present alternatives to delegation. Where automation can be utilized instead of human labor, tasks are often performed cheaper, faster, and with less errors. 

Overproduction

In the law practice context, overproduction means generating more work product than is needed to meet a client’s needs. Take patent application preparation, for example. How does a drafter know when a patent application is done? In traditional practices, it’s often done when the budget is exhausted. What if, instead, the drafter stopped working on the application when it (1) provides sufficient backup positions that might actually end up in the claims during prosecution, (2) provides sufficient enablement for the initially-claimed and potentially-claimed embodiments, and (3) conforms to any and all requirements from the client. Law firm clients expect work product that satisfies official and strategic requirements, not a treatise on the field of invention.

In order to cut out overproduction, practice management will need to align their own incentives with those of the practitioners doing the drafting work. One easy change, for fixed-fee projects, is to give practitioners a fixed billable hours credit for completing the project, regardless of whether it came in under the budgeted time. Rather than just hours worked, which encourages overproduction, this ties performance more closely to revenue generated.

Defects

This includes any mistakes that occur in the patent pipeline, whether they be clerical (e.g., errors in filing forms), more substantive (e.g., curable § 112 issues), or procedural (e.g., incurring extension of time and other unforced fees). Defects-type waste can lead to additional cost in the form of penalties and legal fees for curing mistakes. Prosecution can also be delayed while defects are addressed, meaning even more waste.

Adjustments in processes and leveraging technology can effectively reduce defects. For example, getting religious about the “four eyes principle” can have a drastic impact in catching errors, but perhaps at the expense of efficiency. Today, there are many automated patent proofreaders available that, in just seconds, can thoroughly review a patent application or office action response for common errors.

Just-in-time production

In general, the focus of just-in-time production is on reducing inventory waste. That is, products are not stockpiled, but rather produced “just in time” to meet orders. With minimal stockholding, producers can be more flexible. For example, they can switch to make new products without having to get rid of much stock, meaning they can act quicker to add value.

Inventory in the law-practice context is work that has been requested by clients (i.e., “work orders”) but not yet completed. In traditional practices, where a stable headcount means production capacity (i.e., full utilization of all employee resources) is essentially fixed, completion of any overage work (i.e., work orders above and beyond what employees can process at a given time) is delayed until work orders dip below the production capacity of the practice. A goal of this conventional approach is to compensate for the ebb and flow of work coming in so that practitioners keep as close as possible to their individual capacities (e.g., 35-40 billable hours per week). The inherent side effect of the traditional model, however, is the stockpiling of inventory in the form of pending work orders.

To realize just-in-time production in a patent practice, flexible production capacity is required. Practices should be able to handle bursts in work orders without having to delay completion for lack of available resources. This is done by incorporating non-employee resources into patent workflows. Non-employee resources can include automation tools, contract patent professionals, and/or domestic or offshore outsourcing services. These are resources that can effectively be turned “on” and “off” as needed such that overage work is completed on pace with client work orders while keeping employee resources at their production capacity. All of the undulations in work orders are absorbed by non-employee resources, thus sufficient resources are always available to meet production needs but the practice is never punished by having to pay for unused or underutilized resources.

For work orders that come today, when is “just in time” to complete them? For a variety of reasons, conventional wisdom says filing by client deadlines (e.g., a product release), non-statutory deadlines (e.g., three-month deadline for office action responses), or statutory deadlines (e.g., on sale bar) should not be the goal. Instead, with a lean production approach, work should be completed as expeditiously as possible to minimize inventory, i.e., the time between the client requesting the work and the work being finished. With the rapidly expanding range of available non-employee resources, be it automation or outsourcing, it has never been easier to find right-fit services for patent procurement production.

Kaizen (continuous improvement)

This is really process optimization but in an incremental fashion and in a way that involves all members of a patent practice, top to bottom. The philosophy of kaizen relies on a continuous effort to improve production. To be effective, a decentralized organizational structure is required with regular team meetings to identify and implement small, often quite simple, improvements to processes and activities. Discrete steps may be eliminated, combined, automated, outsourced, or made more efficient in other ways. Providing training to practice members to help them be more analytical may boost results. 

Another requirement for effective kaizen is that efficiency among practice members must be incentivized. As with overproduction, the traditional billable-hours model for assessing practitioner performance can be counterproductive for kaizen. Here again, tying compensation to revenue generated may often get closest to aligning the interests of management and other practice members. One way to do this, as mentioned previously, is awarding practitioners the full balance of the hours budget for fixed fee projects even when they come in under.

Cell production

According to lean production thinking, processes should be viewed as a series of separate but interlinked subprocesses. Each subprocess is then delegated to the most efficient resource. Traditionally, in manufacturing, each process is assigned to a “cell” or group of production workers. In patent processes, a cell could be comprised of one or more employee resources, one or more non-employee resources (i.e., automation tools, contract patent professionals, and/or domestic or offshore outsourcing services), or combinations thereof.

Processes large and small can be decomposed and optimized in this way. At one end of the spectrum, the “process at issue” could be an overarching process (e.g., “starting with an idea, procure a patent”). In fact, some leading practices have one group of practitioners who draft new patent applications and a completely separate group of practitioners who prosecute pending applications before the USPTO. As the process at issue becomes more granular, however, the opportunity is enhanced to squeeze out more value and eliminate more waste.

To illustrate, if the process at issue is preparing a patent application, subprocesses may include something like (a) invention download, (b) drafting claims, (c) assembling a first draft of the specification with baseline § 112 support, (d) bolstering the draft specification with strategic additions for future prosecution and litigation, (e) preparing formal drawings, and (f) finalizing the application ahead of filing. An attorney can certainly perform all of these subtasks, like in a Rolls-Royce-style practice, but it involves a significant amount of “overprocessing”, in the lean production sense. A more BMW-style practice would find the most efficient solution to each subprocess in order to maximize the creation of value for customers while eliminating waste.

Conclusion

With changing demographics among practitioners, challenging economics in the patent market, and exciting new technologies designed for patent practices, it is imperative that practices evolve their operations to remain competitive. To some, transitioning an operating patent practice to incorporate the tenets of lean production may sound like repairing a car while driving down the highway. But it can be done, it has been done, and an incremental approach will keep the changes relatively painless.

DISCLAIMER: The views and opinions expressed in this article are those of the author and (1) are not provided in the course of and do not create or constitute an attorney-client relationship, (2) are not intended as a solicitation, (3) are not intended to convey or constitute legal advice, and (4) are not a substitute for obtaining legal advice from a qualified attorney. You should not act upon any such information without first seeking qualified professional counsel on your specific matter. The hiring of an attorney is an important decision that should not be based solely upon Web site communications or advertisements.

What A Maturing Patent Bar Means For The Industry

By Ian C. Schick, PhD, JD, CEO & Co-founder of Specifio (first posted on blog.specif.io)

A seismic shift is occurring in the demographics of the US patent bar that will have a lasting impact on the broader patent ecosystem. Specifically, the average patent practitioner is aging, which, in combination with other market forces, is already precipitating a number of fundamental changes in how patent practices must operate to remain profitable.

Below, I present a histogram of the number of currently active practitioners binned based on their earliest year of registration at the USPTO. For example, if a given practitioner registered first as a patent agent and then again a few years later as a patent attorney, this graph would reflect the year registered as a patent agent. To make this information a little easier to pick apart, we’ve divided the active practitioners into 5-year cohorts.

Before diving into the analysis, I should mention it was performed under the assumption that the underlying data from the USPTO Active Practitioner Roster is at least close to accurate with respect to the active status of practitioners. Also, Cohort #1 represents 4.5 years at the time of writing and will likely grow by another roughly 500 practitioners in the remaining 6 months concluding at the end of 2019. The discussion below, however, considers the numbers as of June 2019.

Not surprisingly, there are major falloffs after 20, 25, and 30 years of practice, which likely coincide with retirement in Cohorts #5, #6, and #7, respectively. The more interesting trend, however, lies with early- and mid-career practitioners.

In a workforce reflecting the typical law firm leverage model, we would expect to see the highest numbers of practitioners in the most recent years of registration. Instead, we see levels that are not even close to the highest. Cohort #2, for example, is 65% larger than Cohort #1. Cohorts #3 and #4 are both over twice the size of Cohort #1. Twice! 

But it doesn’t stop there. Cohort #1 is even smaller than Cohort #5. Stated differently, there are more active practitioners today with 21-25 years of practice experience than there are active practitioners with 1-5 years experience. Indeed, half of all active practitioners have been practicing for 16 or more years, with the average years of practice for all active practitioners at 17 years. This should be shocking for patent owners and patent practice leaders, alike.

“There are more active practitioners today with 21-25 years of practice experience than there are active practitioners with 1-5 years experience.”

All of this begs the question: Why is Cohort #1 so surprisingly small? Is it less STEM students, higher engineering salaries, law school falling out of vogue, bad press from Alice/Mayo, who knows? There are probably many factors at play which certainly deserve a closer look.

In the near term, the demographic shift we’re experiencing as an industry is leading to some very tough issues. For example, average billing rates are rising at an accelerated pace because the average practitioner is becoming more senior in combination with the usual rate increases for inflation.

For patent drafting, higher hourly rates means either lower hours-budgets per app or higher fees per app. The latter seems very unlikely given the ten-year industry trend of stagnant, if not declining, average fees for preparing a patent application. Lower hours-budgets per app is also problematic, in that it can only go so far until the effects on patent quality are unacceptable. Furthermore, to the extent that rising average billing rates are driving reliance on the junior practitioners of Cohort #1 for certain types of work like patent drafting, we can expect to see the shortage of practitioner bandwidth becoming increasingly acute. 

Even more ominous is what lies 5 or 10 years down the road. As mentioned above, retirement trends manifest as falloffs in active practitioner numbers at 20, 25, and 30 years of practice. Assuming average career lengths stay more or less constant, we can expect the retirement trends to hold true with Cohorts #3 and #4. If there is a drastic reduction in numbers in these cohorts, who will be there to replace them? Not Cohorts #1 and #2! 

Now consider the fact that annual filings at the USPTO have been on an ever-increasing trend for the last 30 years. We, as an industry, cannot continue to defy the basic principles of economics forever. This just does not make sense: increasing demand (i.e., annual patent filings), decreasing supply (i.e., practitioner bandwidth), and decreasing costs (i.e., stagnant/decreasing fees).

Let’s assume that market forces will keep patent demand and costs on their current trajectories. That leaves supply, in the form of practitioner bandwidth, as the thing that must change to balance the supply-demand equation. One way to increase practitioner bandwidth would be to simply add significantly more new practitioners to the workforce. That, however, seems unlikely and, even if it did happen, it would do nothing to change the low numbers in Cohorts #1 and #2.

Another option for increasing practitioner bandwidth is to increase practitioner efficiency. With patent drafting, for example, efficiency can be looked at in two ways: dollars per application or hours per application. The dollars-per-app viewpoint is what is driving law firms to leverage outsourcing and insourcing in a quest to find lower-cost ways of generating patent application documents in the traditional manner (i.e., written and reviewed manually).

Patent outsourcing typically means outsourcing drafting work to a domestic alternative legal service provider (ALSP) or offshoring the work to India or elsewhere with low labor costs. The pros to these approaches include reduced costs and flexible bandwidth, but at the expense of quality control and work product consistency. Furthermore, with offshoring, export controls can come into play.

Insourcing involves law firms hiring unlicensed technical writers who effectively ghost-write patent applications under the supervision of patent attorneys and agents. These technical writers command lower salaries compared to licensed practitioners, so their hourly rates are also lower. One of the most challenging aspects of insourcing is often high turnover, which means that hiring and training are continuous activities. Quality control with insourcing is easier than with outsourcing because the work is locally supervised, but it can still be a significant project for an experienced practitioner to review and revise an application written by a neophyte. 

If we think about practitioner efficiency in terms of hours per application instead of dollars per application, then leveraging new technologies starts to make a lot of sense, specifically automation. Luckily, there is a wide variety of automation tools hitting the market. These include automated patent proofreaders, automated patent drafting, and other tools that shave off significant chunks of practitioner time per project. 

“If we think about practitioner efficiency in terms of hours per application instead of dollars per application, then leveraging new technologies starts to make a lot of sense, specifically automation.”

With automation incorporated into the preparation process, the time it takes for a practitioner to complete a patent application can be reduced by several hours. This means that that individual practitioner can process more applications per year and at a lower per-app cost. One law firm leader recently suggested that his firm, by using automation and process optimization, has individual associates generating over 150 unrelated applications per year. That is astounding. That’s about three applications per week per associate compared to one or less applications per week in traditional practices.

While automation also wins on quality control and work product consistency, there are limitations to today’s automation tools. For example, most require at least some adjustments to workflows. And some are not yet available in all patent domains or proficient at highly-complex patent projects. 

The patent bar may be in the midst of a perfect storm in terms of demographic changes and challenging economic realities, but the silver lining appears to be a burgeoning, tech-enabled patent workforce. Legal may be one of the last industries to be disrupted by AI and automation, but, at least in the patent ecosystem, the inflection point seems to be roughly now. As the trends discussed above play out, patent practices that fail to adjust course will struggle to remain profitable.

DISCLAIMER: The views and opinions expressed in this article are those of the author and (1) are not provided in the course of and do not create or constitute an attorney-client relationship, (2) are not intended as a solicitation, (3) are not intended to convey or constitute legal advice, and (4) are not a substitute for obtaining legal advice from a qualified attorney. You should not act upon any such information without first seeking qualified professional counsel on your specific matter. The hiring of an attorney is an important decision that should not be based solely upon Web site communications or advertisements.

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Top 10 Ways PatentTech is Disrupting Patent Procurement

By Ian C. Schick, PhD, JD, CEO & Co-founder of Specifio (first posted on blog.specif.io)

A wave of new technologies is hitting the market with a specific focus on solving problems and inefficiencies in the patent procurement pipeline, from invention conception to patent issuance. This growing subset of LegalTech has come to be known as “PatentTech.” These new solutions are challenging the status quo of patent practice and becoming increasingly mainstream across the spectrum of law firms and in-house patent departments.

Two analogous technology disruptions in service industries include electronic spreadsheets in accounting[1] and computer-aided drafting in architecture[2]. In both cases, these disruptive technologies resulted in “a net positive for the industry with higher quality, higher efficiency, better access to services, and growth in the workforce”[3].

PatentTech solutions are wide-ranging, but generally fit into the following categories: document automation, process automation, and big data insights. Below is a breakdown of the top 10 ways in which PatentTech is changing how patent professionals and patent practices operate.

1. Invention harvesting: Ideation starts the patent process. Traditionally, patent attorneys often hold brainstorming sessions with engineering teams to identify potentially protectable inventions. Once identified, those inventions are assessed for business value, likelihood of eventual protection, and expected cost to pursue protection. This analysis then forms the basis for a comprehensive IP portfolio strategy. At least two companies–Legit.ai and Bright Marbles–are working in this space.

Automating this brainstorming process addresses strategic and practical aspects. Brainstorming automation can be informed by the prior art, specific competitor products, and the patent owner’s portfolio or the portfolios of their competitors, which can make the results highly-targeted based on business strategies. At the same time, automated ideation may offer more thorough mining via systematic and context-based approaches. Since the information gathered is in digital form, brainstorming automation should also force good IP inventory management. From a practical standpoint, being able to automate ideation eases friction with inventor/attorney scheduling and can even be performed asynchronously among inventors.

2. Invention disclosure: Once inventions are identified, the inventor must sufficiently convey the invention to the patent practitioner such that the practitioner can prepare a patent application that would enable one of ordinary skill in the relevant art to make and use the invention. One popular way of doing this includes having inventors complete a standardized invention disclosure form (IDF) covering the topics relevant to preparing and filing a patent application. Some companies, like ClearAccessIP and AppColl, have platformized this step in the patent procurement pipeline. These existing solutions seem focused on form-based approaches but are presented via a user-friendly web-based interface.

Indeed, anything that addresses friction in the disclosure process is a step in the right direction. However, invention disclosure could be one of the best areas of opportunity for future PatentTech solutions. For example, a semi-intelligent chatbot could certainly perform a more-than-cursory invention disclosure meeting that results in a completed, standardized IDF. The practitioner may still need to follow up with the inventor with some specific questions, but automating a majority of the disclosure process with a natural language interface accessible by the inventor anywhere, anytime would take a lot of pain out of the process and likely result in a higher volume of disclosures.

3. Prior art searching: Evaluating the relevant prior art is an important part of informing the decision of whether to file a patent and, if the answer is yes, determining the appropriate language and scope of the claims and specification. The goal of this exercise is to file patent applications with the highest chances of being allowed based on what is known about the prior art. Cutting out low probability applications and minimizing the number of office action cycles results in efficiencies enjoyed by all stakeholders–patent owners, practitioners, and the Patent Office.  

Several young companies, including Legalicity and DorothyAI, are automating patent search using AI. Automating this process, even if it’s just an initial screen of the prior art, can save hours of time for practitioners and professional searchers. In addition to speeding up turnaround on search projects, automation also makes it more feasible to do in-depth prior art analyses on a greater portion of a given portfolio.

4. Application drafting: The most time-consuming project in the patent procurement pipeline is drafting patent applications, which generally takes a skilled practitioner 20+ hours to complete. By segregating the judgment- and creativity-driven parts of patent preparation from the more mechanical aspects, automated drafting lets practitioners focus their talent on the truly high value-added components of the process. With intensifying cost pressure (see our prior post discussing revenue and cost trends in patent procurement), practitioners are turning to auto-drafting as a viable alternative to offshoring their drafting work.

A handful of rudimentary auto-drafting tools have popped up over the past year or so, mostly bespoke solutions developed in-house by drafting outsourcers and even by law firms in at least two cases. Fully- and partially-automated third-party drafting services, however, are now becoming available to the broader market. With Specifio‘s service, attorney-written claims are used to automatically generate a first-draft patent application with baseline 112 support. The idea, then, is for practitioners to bolster and finalize their auto-drafts ahead of filing with additional details and context around the invention.

5. Claim and spec proofreading: Sometimes small mistakes in patent applications can cost thousands of dollars to fix after the application has been filed. If a patent issues with certain errors in the text, it can even render the patent unenforceable or severely limit the scope of protection. As such, careful proofreading of the claims and specification is prudent (if not essential) ahead of filing the application.

While the rules are relatively simple, performing a thorough proofread by hand is tedious, time-consuming, and error-prone. Automated patent-specific proofreaders, like ClaimMaster and PatentOptimizer, have been around for a few years. However, the adoption of proofreaders like these seems to be accelerating. New AI-based proofreaders hitting the market, like BluePencil and PatentBots, are further evidence of how mainstream these tools are becoming.

6. Art unit prediction: Patent examination is still largely a human-driven process. And humans tend to be creatures of habit. As a result, the USPTO art unit to which an application is assigned once it’s filed can greatly affect a number of factors during prosecution, such as time to first action, number of actions before allowance, and, ultimately, the chances of ever being allowed.

In an effort to provide some control of the outcome, companies, like Juristat, provide an art unit prediction service. Coupling these insights with art unit analytics, such as that provided by BigPatentData, practitioners are able to adjust claim language to affect classification to improve prosecution outcomes and provide more realistic expectations to their clients.

7. Docketing: The patent process is a deadline-driven one. Missing deadlines can cost dearly in late fees and, for some deadlines, can cause the application to go abandoned. As such, docketing is one of the most critical aspects of any patent practice. Traditionally, the intake of USPTO correspondence and entry of corresponding deadlines is performed by a team of docketers. Beyond calendaring errors, the stress and monotony of these positions often result in moral issues and costly turnover.

Automation is becoming more and more prevalent in the patent docketing world. BlackhillsIP, for example, uses automation to augment its human docketers, while AltLegal provides a fully-automated solution. Both companies report cost savings and reduction in docketing errors. Building off of docketing, areas of opportunity for future PatentTech solutions include automated client reporting as well as schedule generation and workflow management for practitioners.

8. IDS preparation and management: Information disclosure statements (IDSs)–the mechanism by which patent applicants report known prior art to the Patent Office–make up another very tedious and error prone component of the patent procurement pipeline. Conventionally, this is often managed with spreadsheets, which is a problematic approach for obvious reasons. One of the earliest in the current PatentTech wave, SyncIDS, manages reference citations and relationships and generates ready-to-file USPTO-compliant IDS forms.

9. Prosecution: Preparing written responses to Patent Office rejections is one of the most time-intensive tasks for patent practitioners. With intense budget pressure, practitioners have found ways to maximize efficiency and leverage. Each office action response is unique, but there is definitely a rhythm to generating these documents. Traditionally, response “shells” are often produced by a paralegal or patent secretary. The shells include bibliographic info, claims in their current state of amendment, and an outline of the rejections in the office action. Shells take time and cannot have any errors. But due to the formulaic nature of these documents, shells are also great candidates for automation. Companies like ClaimMaster and TurboPatent offer automated shell generation as well as office action response proofreading.

When it comes to the practitioner’s part of preparing an office action response, examiner statistics are becoming essential. Examiner statistics are available from PatentBots, BigPatentData, and other sources. Practitioners can make data-driven decisions for things like “Should I appeal or file an RCE?” or “Have we successfully argued this particular issue in the past?”. One clear area of opportunity for the prosecution stage is automated claim charting, which could be leveraged during office action response drafting as well as infringement analysis, examination, and other aspects of patent law.

10. Strategic counseling/planning: One of the highest value-added parts of patent practice is strategic counseling to help solve business issues having an IP component. The analysis often considers various business objectives, likelihood of positive outcomes at the Patent Office, and the associated projected costs.

Patent filing strategies can be informed by a mapping between certain products (e.g., a competitor’s) and relevant patent claims (e.g., in an applicant’s portfolio and/or their competitor’s portfolio). Think of it as the opposite of a product clearance analysis where opportunities for patent protection are easier to identify. This is one of the myriad uses of ClearstoneIP’s platform, which also facilitates analyses like clearance/reverse clearance, FTO/reverse FTO, assessing licensing opportunities, enforcement analysis, competitor monitoring, etc.

Big data insights, like from BigPatentData, can help patent practice managers answer questions like “Should we prepare the client for lengthy prosecution?” or “Who at the firm is familiar with this technology?” or “Where is our prosecution practice most/least profitable?”. For in-house counsel, possible insights can inform decisions like “Should we pay for an examiner interview?” or “Which of our firms have handled this particular issue?” or “To which firms should we send more/less work?”.

More and more PatentTech companies are hitting the market and the rate is accelerating. Indeed, the companies mentioned above are just a few examples in the growing numbers of PatentTech. We are beyond a first-movers-only market with each area outlined above becoming increasingly competitive. Only a few years ago, it seemed like automation and big data insights were barely, if at all, on the radar of patent practice leadership. Now, in today’s hyper-competitive market, it’s dominating the conversation.

References:

  1. See Jacob Goldstein, How The Electronic Spreadsheet Revolutionized Business, NPR (Feb. 27, 2015), https://www.npr.org/2015/02/27/389585340/how-the-electronic-spreadsheet-revolutionized-business; also see Lisa Cumming, After VisiCalc Revolutionized Accounting In The 70s, AI Is The Next Big Breakthrough, BLUE J LEGAL (June 22, 2018), available at https://www.bluejlegal.com/blog/single-post/2017/12/05/after-visicalc-revolutionizedaccounting-in-the-70s-ai-is-the-next-big-breakthrough.
  2. See James A. De Lapp, et al., Impacts of CAD On Design Realization, 11 Engineering, Construction and Architectural Management, Issue No. 4 (2004), available at https://doi.org/10.1108/09699980410547630.
  3. The AIPLA/AIPPI/FICPI AI Colloquium Primer, AIPLA/AIPPI/FICPI AI Colloquium 2019 (February 2019), available at https://ficpi.org/_/uploads/files/AIPLA-AIPPI-FICPI_Artificial_Intelligence_Colloquium_Patent_ONLY_Primer.pdf.

DISCLAIMER: The views and opinions expressed in this article are those of the author and (1) are not provided in the course of and do not create or constitute an attorney-client relationship, (2) are not intended as a solicitation, (3) are not intended to convey or constitute legal advice, and (4) are not a substitute for obtaining legal advice from a qualified attorney. You should not act upon any such information without first seeking qualified professional counsel on your specific matter. The hiring of an attorney is an important decision that should not be based solely upon Web site communications or advertisements.

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