What have we learnt over 2000 years that can help us improve our understanding of patent portfolios?
Strategic Patent Intelligence
Strategic Patent Intelligence
Know your enemy and know yourself; in a hundred battles, you will never be defeated. Sun Tzu
Patent teams in a post-Covid world are being challenged to evaluate and communicate their patent strategy and many are under significant budget pressure. This is where Cipher, a fresh approach to strategic patent intelligence (SPI) can help meet that challenge head on. In so doing patent teams can establish a clear competitive advantage and be well positioned for the economic recovery.
Competitive Intelligence as an early warning system
Many businesses are just waking up to the importance of competitive intelligence (CI) relating to patents. There again, business CI only really began in the 1980s with Michael Porter’s publication of Competitive-Strategy: Techniques for Analyzing Industries and Competitors – widely regarded as the foundation of modern competitive intelligence and voted into the top ten most influential management books of the 20th century.
Over the last 40 years competitive intelligence (CI) has become ubiquitous, and all companies include this as a critical input into business strategy. However, in the patent world, it is has taken a lot longer for CI to be embedded and in a recent survey around 30% of companies reported that awareness of patents did not extend very far beyond the legal department (Source: Cipher Report on Portfolio Optimisation).
This is a call to arms. All companies need to harness the intelligence locked inside patents to help reduce the risk posed by other people’s and to benefit from what patents can tell you about the products, technologies and plans of those the million+ companies investing in the protection of innovation.
Patent analytics in support of strategic decision making
Competitive intelligence can be defined as the business function responsible for the early identification of risks and opportunities in the market before they become obvious. For strategic patent intelligence this includes:
- Benchmarking: being able to understand and communicate the importance of your patent portfolio by reference to organisations owning patents in the same areas,
- Budgeting: an objective and repeatable way of communicating the investment in patents by reference to current and future business strategy (explored in Beyond Portfolio Optimisation),
- Technology Trends: monitoring the global landscape for movement towards or away from specific technology areas,
- Litigation Risk: communicating whether and how your patents mitigate the risk posed by third party owners (over 75% say this is true, without necessarily being able to provide the evidence in support).
What’s common to all intelligence functions is an established process for information gathering, converting it into intelligence and then using it in decision making. Let’s apply these basics to patents.
Table stakes – having the right data
It has long been accepted that information is an essential prerequisite for CI, but stops along way short of being actionable intelligence. For patents the table stakes are having a database of all 100m patents globally. Thanks to aggregators such as IFI Claims, this is now straightforward. But as a cursory glance at Google Patents (a great UI over IFI Claims) reveals, it will not help you make any of the strategic decisions referred to above.
The other entry level requirement is knowing who owns the patents. You’d expect this to be trivial but establishing what patents are owned by a company is hard, largely attributable to inaccuracies on the national patent registers, failure of owners to record assignment and the complexities of rolling up subsidiaries to a group view (the so-call patent corporate tree issue). Refer to Who Owns the World’s Patents? for a fuller discussion.
Patent to technology mapping
On the assumption that you have the world’s patent data searchable by owner, what you need to know is which patents relate to the technologies that are important to your business. This is where the fun starts. Figuring out what technology a patent protects is not hard. Simply read the document and in less than 5 minutes you’ll get the general idea. The problem is scale – a set of 1000 patents would take a human over 2 weeks to review.
The reality is much harder than this, as for most CI tasks you have to search for the relevant patents amongst the 45m active patents and applications (and twice that number if you include all patents, e.g. those that have expired).
Enter classification. What you need for SPI is the ability to map patents to technologies. You’d think this would be easy but it’s not. There are 2 primary reasons for this:
- The patent system was set up before CI was a thing: codes weren’t introduced by patent offices until 1968, and for the purpose of helping patent examiners decide whether a specific invention was new. In addition, patent attorneys are not paid to help you find the patent but are excellent at obfuscation – so forget using keywords.
- Everyone has their own unique taxonomy: all companies have their own unique way of classifying their patents against business units, technologies and products. This means that there is no prospect of a patent office classification system ever being able to help you see patents through your technology lens.
This is where machine learning algorithms have come into their own. Cipher is now able to train its algorithms to automatically classify patents by reference the particular technology scopes defined by the business.
Nearly there – with clean patent data and customised patent to technology mapping, all you need is to integrate SPI into the decision-making process.
Strategic patent intelligence
SPI is patent analytics optimised to deliver against a specific business objective. Let’s take benchmarking as an example. No-one conducts a portfolio benchmarking study for fun. We call the identification of the end-point Cipher’s so-what? For benchmarking the so-what might be:
- Portfolio Optimisation: identification of areas of under- or over-stocking, to provide the evidence in support of future filing or pruning strategies,
- Budget Management: estimating the future budget requirements, in the light of patent activity of competitors and new entrants,
- Litigation risk analysis: figuring out where the business is exposed to liability in the event of an in-bound patent assertion.
While all of these tasks require clean patent data, mapped to technologies of interest, the analytics and workflows will be very different, for example:
- Additional datasets: for budgeting, you need cost data and for in-bound assertion you likely need global litigation data (including NPE activity). Cipher integrates many of these additional datasets.
- Business inputs: the most common observation from teams using SPI for strategic decisions is that “patent data is not enough”. There will be many circumstances where business inputs are required, most commonly revenue data. As we have said in many of our recent publications, everything is relative e.g. you don’t need the same number of patents as a company 3x your size (but without revenue data, how would you know how to scale the comparables?).
SPI for evidence-based decisions
We started by accepting that to fulfil the requirements of CI, the intelligence must be both useful and used for decision making. When we founded Cipher in 2013 one of the most common complaints about patent analytics is that it was not actionable. Typically because it always seemed too abstract or inaccurate (or both). Here’s what we have learnt over the period:
- Focus on your audience: provide the evidence that supports your recommendation. There are no bonus points for swamping your dashboard or report with unnecessary detail.
- Learn their language: the CTO and CFO in your organisation have different responsibilities and priorities. CFOs can learn to accept that patents reduce risk, while CTOs may be more focussed on the activities of competitors and new entrants.
- Be consistent: Cipher has not only reduced the manual effort required to produce benchmark data, but also introduced objectivity and repeatability. For a CI function to be appreciated it has to build in a narrative over time. There is no such thing as “one and done” in the world of CI.
SPI is the link between the ownership of patents and the “so what?“. SPI is about increasing efficiency of patent teams and being able to quickly respond to the needs of the business. SPI is about communicating intelligence about patents in a way that seamlessly integrates with the organisation’s business strategy. Simply put SPI is about gaining competitive advantage.
Failing to prepare is preparing to fail. With modern analytics platforms such as Cipher available to deliver SPI, it is possible for organisations to steal a march on the competition and analyse patent portfolios in a highly commercial, timely and repeatable manner. In the recovery period from the Covid pandemic, this has never been more essential.
To find out more about Competitive Intelligence, download our recent webinar on Competitive Intelligence – how can benchmarking data enhance your patenting strategy?. We are keen to carry out a study on Benchmarking Metrics and we would appreciate hearing your views, please get in touch.
Written by Nigel Swycher, CEO, Cipher