How did you get over the trust and confidence issues required to share that data more broadly inside your business?

Red Hat, as a technology company, understands the value of technology, understands the value of good data and understands the power of artificial intelligence.

We also had quite a bit of our own historical data and manual analysis that we could compare against the Cipher results.  So it was fairly easy to get comfortable with the results as the Cipher results lined up pretty well with our own.  Cipher also provided insights into things that we weren’t aware of.

You referenced there that you got some insights from Cipher and the optimization model that maybe you hadn’t been able to access before. Can you talk about that?

In our own manual analysis, we did some exhaustive research on 100+ companies to see what patents they had, their revenue, and their litigation history – all those sorts of data points you need to understand the landscape. But it’s impossible to research every company on the planet, and it’s hard to know whether you’re missing anybody that you should be aware of.

Sure enough, in our Cipher analysis, there were two or three or four companies that weren’t on our radar, and we are now conducting more in-depth research and analysis to understand how those companies might or might not be a risk.  We wouldn’t have known about them if it wasn’t for Cipher.

Which other technologies do you see as being disruptive?

Developments in human-machine interfaces. When we talk about autonomy, the reality is that there will be more combinations of human-machine interfaces. The barriers to entry are very relevant in that regard. We know that companies like Amazon are working in this field, so with respect to the movement from traditional to non-traditional players, it’s really important that we understand what the landscape is and what IP rights are out there, not just for the traditional players, but also for the non-traditional players.

Additive layer manufacturing (ALM) is also a key area. We are active in that area, and there are a lot of other people who have done significant work in ALM. There are other areas, such as energy storage and management.

Again, if you look at our operations across the enterprise, one of the challenges we have is leveraging that capability across the enterprise in the most effective way and ensuring that we don’t have duplication of effort and investment. It’s remarkable what we do in terms of the world-leading capabilities for governments and our commercial customers.

How have these changes in disruptive technologies fed into a change in your patenting strategy?

We have always been able to articulate our patenting strategy over the years in terms of understanding the key technology areas that we should focus on and biasing our patenting towards those areas. The patenting strategy has, of course, a geographical dimension as well as a technological dimension.

We are building our portfolio within the constraints of our budget, but we also prune where we decide there is no longer any value. Active portfolio management is a critical element of this.

To have a coherent patenting strategy, you have to be clear about the business technology strategies. One of the ongoing debates is how many patents should we be filing. What is the right portfolio size for our organization? We have to create the right portfolio for our business and use it to drive business value. That is the underlying requirement. There is no point if we do not drive business value using our intellectual property portfolio.

So, the notion that we must have 50 patents filed yearly or 150 or 200 is a red herring. I would argue it is all about business value, and it’s about articulating that business value. How we measure that value is a separate question. It may be licensing or leveraging the patents in campaigns to help with the business. It might be enabling a freedom-to-operate strategy. We can use our intellectual property for business advantage in all sorts of ways.

What’s your view of the importance of communicating IP issues to the Board?

It’s extremely important to communicate with all levels of the organization. It’s impossible to achieve optimal IP management or maximize returns for the business from IP without engaging at the top and grassroots levels. To do that, you need an endorsement from the top, which we have.

It’s important not to obfuscate or make things sound more complicated than they really are. Cut to the chase, bring it to life with real examples, and tailor it according to the business needs, and that’s what we do. We have the dialogue, learn from our business colleagues, and hopefully, they learn from us. But it’s important to have a culture of continuous improvement because unless we do that, we can’t move forwards. Communication is key. Visuals are powerful. We have dashboards presented to the Board every month. This draws people in, and they question and probe. It’s all about engagement and having a discussion.

If you don’t have the dialogue, you can’t achieve your objectives. You need to be part of the strategic dialogue. In the past, IP people have often been isolated. They are often viewed as being part of an esoteric function that doesn’t have much to offer to the broader construct. That couldn’t be further from the truth. We also have a strong team with a commercial focus, and all these things come together. Developing those soft skills is important, and communication is a key part of that.

In summary, whether you are communicating with the board or whether you communicate with an inventor or a business development manager, use plain language and develop a common language. Let’s ensure we all speak the same language and get the basics right.

How has Cipher’s AI speed for patent analysis helped meet these challenges?

Cipher classification looks at the IP data through a different lens than the more traditional search engines. For example, we can build classifiers that are looking at a scope of technology rather than doing your more classic Boolean keyword searching that may miss or pick up some stuff completely unrelated to the areas we want to look at. Looking at the landscape through a business opportunity lens gives us a different aspect than more conventional search engines can do.

What’s your experience of working with classifiers compared to, say, Boolean?

We can build a classifier (using Cipher’s AI speed) that sits across all the other codes already embedded in the patent system. Maybe you see those as verticals. We can build a horizontal filter that sits across all of those, giving us another dimension to assemble data from the vast amounts of patent data out there.

How have you found engaging with the LexisNexis team?

The LexisNexis team has been an excellent support to us at Centrica in building our classifiers and understanding our business to get the results that we are looking for, which would not be available from a more classical approach. They take the time to understand our technology. They probe what it is we’re trying to achieve as a business and apply that to a classifier. It’s an intricate process building the classifier, and they will refine a classifier until it works for us as a business and enables us to get the results that are going to be the most useful – that, obviously, requires our input from the business side and their expertise with the technology classification.

The value of the system is being able to cut across the silos that traditional patent classification codes have used. It enables us to take a new look at the data through a business lens, a commercial lens, as opposed to simply a patent lens.

How would you explain the value of Cipher to other members of the IP community?

This has been a very interesting learning curve for me to understand how AI works and how it accelerates the process. It helps us to get to an answer quicker. It is not looking for specific keywords but looking for themes and concepts. And because questions are sort of blurry at the edge, I find the approach very interesting. Because where data might have been cut out in a more traditional search, that blurry edge can be quite informative. It’s that slightly blurry edge that is the tasty bit. It’s almost like going from Newtonian mechanics to the new world of quantum mechanics back at the turn of the last century. And it’s bringing that new dimension around the understanding of the universe.

Cipher gives us AI speed for patent analysis, enabling us to look at huge and vast amounts of patent data through a different lens in a much quicker time than possible, without the use of artificial intelligence, with just using normal searching techniques. The AI adds that extra dimension of speed – for us, that’s critical.

“Instead of waiting for inventors with good ideas to bring them to our patent attorneys, we sent our patent attorneys out to talk to researchers and developers to better understand how what they were working on might contribute value to our businesses,” says Weibel.

According to Weibel, it took time, but Siemens’ patent attorneys rose to the challenge. The company’s innovation and IP activities are now aligned behind a value-driven IP strategy and the IP group is proactively involved in the company’s innovation process.

Integrating innovation and IP strategies was just the beginning. Another essential element of the shift to quality over quantity was selecting a metric for determining whether the change in strategy was successful. In other words, the company needed a way to prove whether the quality of its patents was improving over time.

For this, Weibel turned to PatentSight, a LexisNexis company that provides business intelligence software, analytics tools, and insights into the strength, quality, and value of patent portfolios. PatentSight is known for its Patent Asset Index^TM, an objective measure of global technological strength and innovation. The measure takes into account both the number of patent-protected inventions and their quality, or value. The method allows the identification and profiling of patent gems businesses can leverage to create value from innovations. The Patent Asset Index is defined as the aggregated Competitive Impact of all patents in a portfolio. It can be calculated for the overall portfolio of a company, patents related to a certain technology, and any other group of patents based on selected criteria.

“PatentSight is quite a good match for Siemens,” says Weibel. “The tool came out of a university and has an academic objective, not just a commercial one. It allows us to track patent quality over time compared to our competition, taking changes such as acquisitions and divestitures into account. And the indices used to measure quality take into consideration differences in markets such as the U.S., Germany, and China.”

The foundation of the Patent Asset Index is excellent data quality, which the company achieves by maintaining a proprietary global patent database. To populate the database, PatentSight compiles patent data from more than 95 authorities worldwide, including more than 100 million patent documents, about 700 million drawings and illustrations, and nearly 100 million PDFs that are searchable and quickly downloadable.

To ensure the data is accurate and reliable, a highly skilled team of experts continually tracks factors that can affect the ownership of patents—and therefore who holds commercial power over them—including corporate structures, mergers and acquisitions, company name changes, patent transactions, and others. The team also checks for the validity and remaining lifetimes of patents. This ensures that analyses focus only on active patents, pending patent applications, and valid patents.

Patent quality captures the attention of the managing board

The benefits to Siemens of a patent strategy focused on quality over quantity, supported by PatentSight, are many. For starters, Siemens now realizes a better return on investment for its patents. For example, even though the company still files roughly the same number of patents each year, the quality of its patent portfolios is higher and continually improving.

Moreover, and of even greater importance, according to Weibel, patents now play a much larger role in the strategic development of the business. For example, the IP team can now make recommendations on where the company should invest more in research and development to create new opportunities such as acquiring new customers or new joint venture partners or to improve its competitive advantage in key regions or markets.

Not surprisingly, the transformation of patents from a necessary cost with little perceived return on investment to a strategic tool for creating business value and competitive advantage, has caught the attention of the Siemens managing board. After Weibel’s presentation reporting initial results of the shift to a value-based IP strategy, he’s now invited back to present to the managing board once or twice a year.

says Weibel. “I was lucky that the managing board trusted me and the PatentSight tool when I told them we could harvest more valuable inventions and create broader and more important patents by changing our strategy and measuring quality improvement compared to our competitors.” Adds Weibel, with a smile, “Of course, now the board expects to see quality improvement every time.”

Watch the entire interview with Beat Weibel:

As any IP expert knows, evaluating the strengths and weaknesses of a patent portfolio can be a time-consuming and laborious affair.
Manual processes require legal teams to comb through large amounts of patent filings, prosecutions, and citations to find the information they need.

In the past, such analysis has been enabled by nothing more than a spreadsheet, making it slow, error-prone, and difficult to scale.

Even once the patent analysis has been completed, presenting insights and findings in a way that is easily understandable by the board can be a challenge.

Without expertise in analytics and IP law, the analysis can be opaque and hard to understand.

As a result, IP analysis has traditionally played an under-valued role in due diligence. This is a lost opportunity for firms, as the value of an IP portfolio can make the difference between whether a firm should consider a merger.

C.G. Moore and his team were therefore challenged to deliver their insights to the clients’ IP Council in a way that both the Council and the management board could see value in and easily understand.

The simple workflow enabled by PatentSight allowed C.G. to look at the firms IP data in different ways, ask different questions, and repeatedly test assumptions.

And thanks to PatentSight’s simple to grasp visualizations, the client was able to quickly feedback to C.G. where the analysis needed to go deeper and where it could be reined in.

He was thereby able to hone the data analysis on-the-fly to tailor it more exactly to the clients’ needs:

The result

As a result of PatentSight’s analysis it was clear that IP was the major asset for both the client and the target firm. Consequently , the business was able to make the decision not to proceed with what would have been an unsuitable match.

By providing another view into the risks and benefits of a potential merger, PatentSight can save time and effort, while helping firms allocate resources better and answer the most important questions more thoroughly.

And unlike other solutions on the market, PatentSight is completely transparent. The working of the algorithms and how it reaches its conclusions are open for all to see, so when the platform provides an insight, firms understand exactly how that insight was reached.

This means that lawyers like C.G. can present their conclusions with complete confidence that the analysis stacks up.

PatentSight – A unique approach to IP analytics

Evaluation of technological fit
Objectively evaluate upcoming merger or acquisition targets based on the quality of their technologies, potential risks and technological suitability. The Patent Asset Index™ helps in assessing patent quality and reveals the true strength of the players in technology fields, enabling you to identify the key patents that require explicit attention.

Easy-to-grasp visualizations
PatentSight Business Intelligence helps you effectively communicate your findings with powerful insights and visualizations, enabling you to turn your patent department into a strategic consulting unit.

Transparent approach
The PatentSight methodology and KPIs are entirely transparent. How the algorithm works and how it reaches conclusions is open for all to see, so when the platform provides an insight, firms understand exactly how that insight was reached. The methodology has been published and the base assumptions are known, giving users full transparency.

C.G. Moore is now a complete convert to PatentSight. In part, this is down to the sheer usability of the platform and the breadth of analysis it enables:

Watch the entire interview with C.G. Moore:

Download the case study:

In a business environment where competition is increasingly intense, firms like Han Santos are under pressure to deliver answers to their clients that are detailed and analytical but that also land on their clients’ desks extremely rapidly.

“When the amounts of money we’re talking about are being thrown around, there’s usually stress on the part of the client,” says Santos. “The longer they wait for an answer, the more stressed they are.” This, he adds, does not mean firms can allow standards to slip or their approaches to become less rigorous.

Given this high-stakes business environment, the firm needed a way to rapidly deliver what Richard Dodson calls a “first cut”—that is, identifying enough high-value, impactful patents to hand over a reasonably representative sample set to a smaller team of attorneys for analysis.