Analyzing competitor activities and being well-informed of innovative new technologies is essential to a good Intellectual Property (IP) strategy. A high level of infringement protection and avoiding costly parallel developments are two goals of professional patent monitoring. It is important to ensure that there is no infringement of third-party IP rights while simultaneously monitoring the patent activities of competitors that affect your business. Superior technological insights and identification of trends will support the company's research and development (R&D) activities and strategy. Data quality and actuality are crucial factors required to achieve these ambitious goals but are not the only challenges that need to be overcome.
Global data coverage
Establishing smart monitoring systems starts with the data available. Databases that offer broad global coverage and provide accurate information are the foundation of professional patent monitoring practices. Typical questions include the following:
Are all relevant countries covered?
How comprehensive is the full-text coverage?
How satisfactory is the quality and range of machine translations, and are they searchable?
Besides the accessible databases from patent offices like the European Patent Office (EPO) or German Patent and Trademark Office (DPMA), which are available at no cost, there are many other commercial providers. With a coverage of 120 million patents and over 80 countries, the EPO database is substantial and should meet most information needs. However, some commercial providers can offer even broader coverage, especially regarding data from authorities where it is difficult to source patent content and regarding the amount and quality of searchable machine translations. In addition, many providers charge by data packages, ensuring that you only pay for the data needed. When selecting a commercial database, make sure it minimizes white spots and that the charges are only for the data required.
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Boolean and semantic search capabilities
Broad data coverage is the prerequisite to ensure that no vital patent is missed. Nevertheless, the more information available, the greater the challenge to identify important information. To illustrate the size of the challenge, in 2018, there were 3.3 million patents filed worldwide (World Intellectual Property Indicators (WIPO), 2019). This vast number of patents emphasizes the need to apply robust data filtering to identify relevant hits that can be managed with the given resources.
Besides accessible databases from patent offices worldwide, other commercial providers can offer even broader data coverage. You have to make sure, though, that the commercial database of your choosing minimizes white spots and that you only pay for the data required.
Today's research tools usually provide a comprehensive Boolean search and operators that enable the user to define specific search strings to meet pre-defined information needs. First, the necessary information must be clearly defined in the context of the company's technology and business. Next, the number of non-relevant hits should be reduced by combining the correct bibliographic data, precise keywords and relevant exclusion criteria in the search. Modern artificial intelligence-based research tools like Octimine can support a comprehensive patent search strategy with state-of-the-art semantics and machine learning. However, the design of an optimal search strategy is an ongoing and iterative process and needs to be regularly aligned with the company's information requirements.
Classification and distribution of results
Professional patent monitoring does not end with overcoming the challenges of data coverage and search strings. The optimal search strategy must be aligned to the company's technology clusters, product clusters and organizational set-up, especially regarding R&D. Clustering offers the principle for the classification of new patents and how they are distributed within the company. The correct people need to be provided with the right patent information. Accurate patent classification is usually a challenging and time-consuming task when done manually, but the employment of machine learning technology can save time and, in some cases, increase accuracy.
With good classification practices, the number of hits provided to each of the company's experts is reduced. Their frustration about irrelevant information will be avoided, and they are enabled to give feedback about new hits. Bridging the gap between IP management and experts, especially R&D specialists, is critical for successful patent monitoring. However, many companies are faced with the issue that technological experts avoid getting deeply involved in patent monitoring because of its complexity. Establishing a collaborative software platform where information is easily accessible and can be assessed quickly and intelligently can be part of the solution to making patent work easier and more efficient.
Automation and family-consolidated hit lists
Two important aspects to increase the comfort and efficiency of patent monitoring are a high level of automation and working with consolidated family hit lists, such as the International Patent Documentation families. Most search tools provide the functionality of running fully automated searches and periodically informing users of new hits by a newsletter. The alerts must be as flexible as possible in terms of the users, intervals and content.
A good patent research tool has to be user-friendly and easily accessible by non-experienced users, packed with well-structured menus and a high level of automation.
It is also helpful to work with consolidated family hit lists to identify content. Once a patent family is reviewed and assessed, it is unlikely that the experts need to be informed about every subsequent patent filing or minor status changes. The goal is to see only new and relevant information. A high level of automation with flexible alerts and family-consolidated hit lists will contribute to solving the challenge of managing considerable amounts of data.
To ensure acceptance of patent monitoring activities throughout the company, the usability of a research tool by non-experienced users is extremely important. The menu must be well-structured, and the information must be easily accessible and displayed to highlight the most important data immediately. This sounds obvious but seems to be a challenge for providers, and many available tools still have a rather old-fashioned look and feel.
Finding the right tool(s)
Once information needs are known and the internal workflow to process patent information is established, the right tool(s) to meet the company's requirements must be identified. This is not an easy task since there are numerous tools available, all with specific strengths and weaknesses. Every user is likely to have a personal preference, and compromises will have to be made based on the limitations of tool(s) and resources. Therefore, it is unlikely to find an all-encompassing solution. Nevertheless, "intelligent IP intelligence" will be achieved when the information and workflow needs of the company are captured and build the foundation for the development of the ideal fitting solution. Ultimately, the established patent monitoring practice will find high acceptance throughout the company and overcome the challenges mentioned above.
The authors contribute to this blog in their personal capacity. The views expressed are their own and do not necessarily represent the views of Dennemeyer IP Solutions, Dennemeyer & Associates, or Dennemeyer Consulting.