How data is used is reshaping large parts of the patent market, from portfolio development and maintenance to prosecution and deal making, providing rights holders with a new range of tools to master
As intellectual property has moved up in importance on the corporate value chain, in-house executives at major patent-owning companies have gained access to a wider range of tools with which they can prosecute patents, manage portfolios and do deals, whether licensing agreements or patent acquisitions and sales. The impact of these analytics on the market has been considerable, yet with such vast potential, we may still only be in the early stages of realising their full contribution to the patent system.
To assess how the use of analytics is reshaping the industry and the ways in which it might continue to affect major patent owners, IAM assembled a group of experts in the field, including Vincent Brault and Matt Troyer of Anaqua, Cipher’s Nigel Swycher and MaryAnne Armstrong from Birch, Stewart, Kolasch & Birch, LLP (BSKB). Together, they explore how analytics tools are helping IP owners around the world.
Q: Can you give us a sense of the kind of work that your company handles in the analytics space?
Vincent Brault (VB): Anaqua provides clients with access to AcclaimIP – an exceptionally fast and powerful patent search and analytics platform, which is ideally suited to enhance the entire IP process.
Through AcclaimIP, inventors, attorneys, researchers and executives can leverage public patent information to track competitors, write stronger claims and make more informed filing, licensing and renewal decisions to build superior patent strategies and monetise their patent portfolios. The AcclaimIP platform includes more than 120 million global patent publications and is updated with roughly 125,000 new documents every week, including supporting data such as legal events, maintenance events, family data, application statuses, file wrapper documents and assignment events.
Matt Troyer (MT): Our clients use the AcclaimIP tools to better understand today’s environment, analyse and understand trends, and forecast future conditions. With patent analytics, users are also able to find and visualise patent information, as well as gain unique insights into their portfolio and the market.
Through AQX, Anaqua’s leading-edge software platform, clients can further leverage these analytics to better align their IP portfolio strategy with their business. The solution suite provides real-time patent data and competitive insight into an organisation’s IP portfolio with side-by-side visibility into the business’s private and public data (integrated internal and external analytics for enhanced portfolio management).
MaryAnne Armstrong (MA): At BSKB we do not obtain the analytics directly (ie, we do not directly input the parameters into the software). Instead, we outsource the running of the data and then analyse this once it has been obtained. However, we are integrally involved in developing the paradigm on which our clients run the analytics, depending on their goal and the type of information that they want.
Nigel Swycher (NS): Cipher is a leading provider of strategic patent intelligence. We provide major patent-owning companies with competitive intelligence, analysis of disruptive technologies and the essential data required for patent portfolio development. Cipher is a software-as-a-service platform, which harnesses AI and machine leaning to improve the accuracy and availability of patented technologies.
Q: How have you seen attitudes to patent analytics shift among IP stakeholders?
MA: Patent analytics are being used two-fold. On the front end, patent filers are using analytics in relation to patent examiners and prosecution trends to strategise their portfolio management. IP stakeholders are also using patent analytics to make business decisions based on results regarding competitor IP portfolios (eg, the breadth and strength of their portfolios). What is more, stakeholders can use analytics to measure the strength of their own IP portfolios. When used effectively, patent analytics go beyond the mere number of patents owned by an IP stakeholder and can be used to evaluate the size and force of a patent portfolio.
NS: The major shift correlates to the development of IP strategy. Go back 10 years and the function of the patent portfolio was not understood outside IP teams. Patent searches were the exclusive domain of those working in patent preparation and prosecution. Now, patent analytics feature in licensing, litigation and a plethora of other situations, including patent sales, patent insurance and IP-backed lending. That is a dramatic change – not to mention the fact that IP stakeholders now include chief technology officers, chief financial officers and the executive team more generally.
VB: At first, too much was promised, with analytics tools that were not yet ready to enter the market. There were great concepts such as heatmaps and clustering tools, but they required more finessing to perform in the way that IP stakeholders needed them to. Early adopters did not yet see the value of these products because, unfortunately, they were not mature enough.
However, over the past five years, the patent analytics space has advanced and is now growing at a tremendous rate. IP data can be mined successfully and IP stakeholders can leverage the contextual and actionable data necessary to make better, more informed business decisions. The evolution of sophisticated analytics tools has improved access to IP data and enabled stakeholders to better address the complexity that is inherent within patent data.
As one IP leader previously put it: “I find I am in decision-making overdrive. I have thousands of decisions to make every day and am flying blind, I do not have the right data support to make the right decisions.” Now, these IP stakeholders have the tools to navigate them in the right direction for their business.
Q: What are some of the popular misconceptions about analytics that still exist today?
NS: There is too much talk about AI and not enough focus on what information is required by IP heads and why. We have published extensively on why conventional search is too slow and expensive for the modern age, and how machine learning can be used to accurately map patents to technologies. If the topic is not handled with care, it can sound like humans are being replaced by machines. The reality is that next-generation analytics are purely an efficiency play – automating dull manual tasks that are better performed by machines and enabling experts to concentrate on higher levels of analysis.
VB: One misconception is that IP analytics focus solely on patents, but there are analytics for trademarks as well. For example, Anaqua’s Trademark Management unifies collaboration, workflow, documents, data and analytics in a single platform to deliver differentiated IP management capabilities that help organisations to grow, mitigate risk and increase productivity among teams. This allows users to leverage global curated external data to validate their own portfolios and benchmark themselves against competitors and the market at large, in order to make smarter, data-based IP decisions.
MA: The biggest misconceptions are probably with regard to the value of the analytics – and their accuracy.
Q: Are there any sectors in which you are particularly active? Which industries do you expect to make greater use of analytics in the near future?
VB: Global, fast-moving and disruptive technology industries are where analytics are creating the greatest value and where our clients are the most active. For example, the emergence of new technologies such as autonomous vehicles can bring a sudden abundance of new players into a space.
Because technology changes so fast, you have to rely on technological solutions to identify trends and emerging players in order to stay ahead of the competition. This is why many tech companies naturally gravitate towards patent analytics tools – they have no fear of leveraging cutting-edge tools where they need them the most.
It is also important to remember M&As where intellectual property has been a key component of the value proposition. Analytics are some of the best tools available to control and conduct a pre-emptive analysis and plan around an M&A strategy.
MA: Patent analytics could be of significant use in the pharmaceutical industry to provide an overview of the field before entering into a new project area. Prosecution analytics are also very useful in the pharma space, where fewer applications are filed and there tends to be more value per patent. Analytics help to determine the most effective way to engage a particular examiner.
NS: Cipher has developed a number of industry solutions, including in the automotive, industrial automation, fintech and fast-moving consumer goods arenas, but the approach extends to all sectors where there is global patent activity. There is a significant demand for strategic patent intelligence in the aerospace, chemicals, semiconductor, energy, medtech and pharma sectors, as well as technology more broadly (think Facebook, Apple, Microsoft, Google, Amazon and their peers).
Q: Numerous advances in technology (eg, far more sophisticated analysis of big data sets) have had a huge impact in this field. Are there any that you would pick out as being particularly influential for patent executives at major IP-owning businesses?
NS: Cipher incorporates machine learning and neural networks, but what gets the attention of executives is outcomes – portfolio optimisation, reduced patent risk, increased licensing revenue and better grant rates. Now is a great time to be working in this area. Patents have never been more important, there is a wider amount of data available, AI has improved and let us not forget the Cloud. All this computation consumes huge resources, but the cost of renting this capacity makes what used to be impossible (or not cost effective) possible.
VB: The biggest development has been the convergence of data-rich internal and external analytics, business intelligence tools and end-to-end financial management capabilities all in one smart platform that aligns intellectual property with the business. IP management software that can deliver these multiple data points from various data sources to better support decision makers in their complex IP decisions has been extremely effective.
The integration of public and private data analytics enables IP executives to easily track levels of innovation within their organisation, evaluate the strength of their portfolio, monitor the competitive landscape and identify opportunities to leverage their intellectual property in order to transform the business.
In addition, the ability to automatically classify third-party patents leveraging your own taxonomy is particularly powerful, as it allows you to efficiently compare apples to apples. Clustering tools, heatmaps and AI that detects statistical deviations and trends have also had a huge impact on IP-owning businesses.
Q: What impact are analytics having on patent prosecution?
VB: Analytics provide transparency and automation that drive efficiency, improve visibility and minimise risk. Organisations can gain clarity across patent and trademark offices, applicants and prosecuting attorneys, which provides the predictive analytics necessary for determining the who, what, when and where to validate your patent. For example, external data can be leveraged to better understand a patent landscape or evaluate an outside counsel’s performance before patent prosecution processes.
Moreover, with the help of advanced AI analytics, many patent drafting and filing tools are now automated, which helps to streamline processes and alleviate administrative burdens during patent prosecution. These tools enable users to better manage documents, deadlines and alerts.
MT: For me, a couple of exemplary examples come to mind. One is the introduction of advanced citation and forward rejection data, which has only been available for the past few years. Since many similar inventions are created around the same time by independent inventors, the patents that stem from them are likely to be filed within a similar timeframe as well. Due to publication delays (typically 18 months), two applicants may be unaware of each other’s filings. However, by the time the patents are examined, the applications have usually been published and examiners can cite them as blocking art. With advanced citation and rejection data, patent owners can detect these collisions and respond by modifying claims or filing continuations to cover their competitor’s specific claimed implementation of the invention. It is like an invitation to file a patent in the centre of your competitor’s roadmap.
The second example is prosecution analytics. We can review historical data and display success rates at various stages of prosecution to help patent attorneys determine which strategy is likely to be the most successful with a particular examiner or within a specific art unit. For example, by highlighting historical success rates before modifying claims, setting up an interview or filing an appeal, patent prosecutors can determine which strategy will most likely result in a next-office action grant. By supporting these analytics with recent examples of similar successful (or unsuccessful) patents, patent attorneys can make more informed decisions on how they want to respond to office actions.
From experience, it is not enough for these types of data to simply be made available; rather, they need to be integrated into the patent attorney’s existing workflow so that they are always available when responding to an office action.
MA: Analytics can have a big impact on prosecution because by analysing the data regarding particular examiners and art units, an applicant can decide whether it is worth filing an appeal or continuing with the examiner (eg, by filing a request for continued examination).
NS: This is not our field, but AI is being deployed on both sides of the table: to help accelerate invention and by patent offices to improve examination. It is important to ask where this race will end up.
Q: How can in-house patent counsel make greater use of analytics in the ongoing management of their portfolios?
MA: As discussed earlier, patent analytics can be used on the front end during patent prosecution for data regarding patent examiners and prosecution trends in order to strategise portfolio management. They can also be used to make business decisions based on the results regarding competitor IP portfolios, while stakeholders can similarly use them to measure the strength of their own IP portfolios.
NS: This was the subject of our recent IAM article “How Many Patents are Enough?”. Following an extensive industry consultation, we developed a methodology to support portfolio optimisation that is based on integrating strategic patent intelligence with market and revenue data. The methodology has proved popular with companies looking to minimise threats from competitors and other relevant patent owners. We can also see that the trend is to make greater use of this data for portfolio management and development. Better data means better decisions around all the strategic questions, including whether, what and where to file, and a similar set of questions in relation to the management of existing portfolios.
VB: In-house patent counsel should leverage analytics for enhanced portfolio insight and visibility into the strength and relative market position of their IP assets at both a micro and macro level. With the right analytics tools, counsel should be able to clearly identify which assets lost value, which assets are critical business drivers and why the organisation should keep or prune specific patents based on its key objectives and business needs. Another way to enhance portfolio management is by using analytics for external assessment on the competitive landscape, supplier performance, the technology landscape and market trends.
In addition, in-house law departments should look for new ways to use data to identify trends and patterns that show which outside firms could best supplement the company’s workload and strategic focus. They can also compare current outside counsel’s performance with potential new providers through publicly available data in order to make informed decisions on how to allocate work to third-party organisations. Similarly, law firms can benchmark themselves against other firms and determine how their clients measure them.
Q: How do you go about demonstrating the return on investment (ROI) that the more sophisticated use of analytics can deliver to in-house IP departments, particularly when those departments are often cost centres within their companies?
NS: It is all about ROI, but it is much more subtle than simply reducing patenting costs. In fact, there are few companies that have budget reduction as a strategic objective. The two most common measures are threat reduction (mitigating the risk of paying patent royalties to others) and portfolio optimisation (having evidence that either justifies the current budget or supports the case for increased activity in specific areas). There are often quick efficiency wins such as freeing up internal resources from manual searching or direct cost savings by eliminating the cost associated with requesting the data from external advisers or offshore patent searchers.
MT: Smart use of analytics can help IP departments to:
- develop a competitive advantage by establishing a strong offensive and defensive IP portfolio;
- receive higher issuance rates and a reduced number of office actions by leveraging data-informed decisions before patent prosecution;
- prune and monetise the organisation’s IP portfolio by having internal and external analytics for enhanced insight and comparison; and
- select, evaluate and manage outside counsel – increased clarity into outside counsel performance and service levels can enable fact-based discussions on individual firms versus peer group performance and cost.
MA: ROI should typically be demonstrated by a case study showing the successful use of patent analytics. Timing can also be important (eg, when a client mentions that it would be useful to have information regarding the likelihood of success following a given prosecution strategy with a particular examiner or regarding the scope of its competitors’ patents).
Q: What big trends do you expect to see shaping patent analytics in the next five years?
VB: There are four main trends that we anticipate will shape patent analytics over the next five years:
- Increased automation of analytics will help to decrease the amount of patent research that IP teams conduct.
- The convergence of IP management and IP analytics will provide a framework for IP executives to access and consume an abundance of information in order to make more informed business decisions. In other words, we will have access to one centralised platform where we can easily access actionable intelligence.
- IP analytics tools will be even more business-centric to help organisations align their IP portfolio strategies with their business objectives. By providing new ways to explore operational data and combine this with market data, intellectual property can be used at a higher level throughout the organisation, solve bigger problems, be closer to decision makers and increase value.
- More AI tools will emerge that complement the work of IP users to help give guidance.
MA: One of the most common questions that we hear is whether AI can be incorporated in patent analytics to improve the sophistication of the information that is provided. Over the next five years, this information will likely become both more accurate and more detailed, and tailored to answer specific questions.
NS: Strategic patent intelligence is a rapidly expanding area and it is fantastic to see high levels of investment being deployed by private equity and venture capital into start-ups such as Cipher. It is fair to say that for a market that supports the world’s leading innovators, there has not been a step change for decades. However, with more sectors affected by patents and increasing amounts of data (the push for transparency will lead to improvements in data relating to patent ownership, sales and assignment, licensing and litigation), the stage has now been set. This, combined with advances in AI and machine learning, means that many of the inefficiencies in areas such as IP insurance, lending, trading and valuation will start to be addressed.
While in the short term there is likely to be an increase in patent litigation, this is a terrible way to resolve disputes between large patent owners. Better data will enable more evidence-based outcomes and therefore less combative dispute resolution. No one burns down their house to find out how much it is worth.
The next big thing will be the use of patent data by the financial services sector; the amount of published information accessible to investors is vanishingly small.