My previous blogpost (Corporate IP Practitioner's need for flexibility and transparency ) had mentioned that a combination of a patent analysis platform such as Patent iNSIGHT Pro with a patent database can make a powerful and yet cost-effective solution to your needs for flexibility and transparency while accelerating activities that usually eat up most of your time. Let me elaborate on that here.
With the current downturn in economy, chances are that you would be dealing with IP or R&D budgets cuts and your key concern today is to ensure that Intellectual Property research and analytics activities continue to deliver greater value to the management, the R&D and Licensing/Business Development while addressing the increasing needs posted by M&A, Litigation and Open innovation during these cuts.
Due to the variety of Intellectual Property research tools and databases in the market, its difficult to understand what tools would fit your need. Most experienced researchers say that since each tool has been designed from a different perspective, there isn’t one database or tool that can help address all your needs. So when trying to optimize your IP tools expenditure the question that arises is: Which tool or tools meet most of your needs ?
Now while your top-level analysis projects may be Infringement analysis, Freedom-to-Operate, White-Space & Gap Analysis, Portfolio mapping or Competitive Landscaping, they all boil down to unique IP procedural needs. Here is a quick IP research and analysis process need checklist that you can use to map out your needs:
If you have checked more than four of the items above then your needs extend beyond patent searching, and you have three main options available in the market today:
Solution 1: An offline analysis solution (such as Patent iNSIGHT Pro) with capability to automatically integrate data from free online sources and commercial sources
Solution 2: An integrated analytics driven database
Solution 3: A database + offline analysis solution
Solution 1 - An Offline analysis solution
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Pros: Flexibility, Comprehensiveness, Customizability, Cost Effective |
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Pros: Quick Analytics; Pre-calculated metrics can be helpful on occasions (esp. for valuation studies) |
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Pros: Quick Analytics, Cost Effective, Coverage, Flexibility, Comprehensiveness, Customizability |
And finally the cost…
Per prevailing market rates for IP products and databases Option 1 can cost you between 2500-8000 USD depending upon product and its capabilities. Option 2 can start from 12000 USD and can go upto 50000 USD while option three gives you maximum capabilities and still costs you between 8000-12000 USD again depending upon the type of database and analysis tool.
To sum up, doing a thorough research on the possibilities and capabilities of different solutions and understanding their price-points can help you increase the depth, quality and efficiency of your IP operations and yet reduce your overall IP tools cost.
Corporate IP practitioners, both managers and analysts have IP needs that are different from external consultants and IP Analysis service providers.
Chances are if you are corporate IP practitioner, when you initiate IP research for a new product/technology area, mapping intellectual-property is just one aspect of analyzing IP and a lot of your day to day IP research work besides patent searching would involve:
So, one of the key aspects that you should consider when considering an IP solution is your need for flexibility with the data within the solution. Our experience has been that most corporate IP professionals cannot have enough of “flexibility” when it comes to patent data and usually work on the leading edge of what one can do with the data. Managing the overall process of reporting, screening, and analyzing requires a lot of flexibility in manipulating, categorizing, grouping and reporting patent data and this can significantly burden corporate IP managers.
Transparency in analysis is also very important. “I could get thrown out of my management meeting if I don’t have the exact logic to back the analysis output” says one user. Its important for your analysis solution to provide transparency at each stage of the process. Most advanced users for Patent iNSIGHT Pro have questioned our charts and visualizations or even algorithmically calculated fields and we have helped them understand the full logic behind each. While there isn’t any exact statistic I could locate, based on what most researchers say it appears that very few people base decisions on patent maps that aren’t backed by a full understanding of the logic (and in many cases screening of patent content) behind the map.
A combination of a patent analysis platform such as Patent iNSIGHT Pro with a patent database can make a powerful and yet cost-effective solution to your needs for flexibility and transparency while accelerating activities that usually eat up most of your time. Without the right set of tools you can be spending weeks in achieving what would otherwise take a few days or lesser.
As a technology driven company, your business either revolves around a core technology in case of a startup or around multiple technologies and products for a large corporation and chances are you would be already accessing patent information from a patent database. However, if you are serious about IP and its role in your technology strategy you need patent mining and technology landscaping over patents not just restricted to your company’s patent portfolio but over all patents related (both directly and indirectly) to technology space you are in.
The success of in-house patent mining activity largely depends on - what you analyze, how you analyze and how you communicate the analysis to those who need it. A fundamental activity that provides a base for all of this is having a well maintained technology portfolio. Lets call it a “techfolio”. Formally defined, a techfolio would be a constantly updated set of technology records- patents and journals stored in a platform which makes it easy to analyze them in many different ways when required.
How to create and maintain a techfolio? The overall process is not as difficult as it may appear. The steps to create and maintain a techfolio can be as simple as:
Start with a good patent and journal search
Perform a state-of-the art search for the particular technology over patents and journals in the technology space. If you are an R&D professional without much exposure in patent searching, it is advisable to involve a professional searcher for this step.
Integrate your results in a common analysis medium
The analysis platform where you integrate your results plays an important else the process may become cumbersome and frustrating. Too often the underlying analysis and storage platform or medium is Microsoft Excel, raw SQL database or perhaps a generic text mining solution. Since these are not specifically designed to suit techniques for technology analysis, you either end up spending too much time writing Excel Macros, SQL queries and doing all those things which make you say “there has to be a better way!”. Generic text analysis solutions that do not understand patents and its special characteristics such as Priorities, Families, Claim structure, Legal Status and other unique bibliographic fields would perhaps do more harm than good.
Setup alerts on your search strategy and update your techfolio from time to time
Constantly updating a techfolio can become cumbersome and repetitive but solution providers can help you automate alert integration and thereby making it easy for you to keep the techfolio up-to-date.
A well maintained techfolio can save a lot of time by avoiding repeat search work for each internal project. You can mine (categorize, slice-n-dice) techfolios for different reasons at all stages of your product/technology development and commercialization and apply those insights for R&D strategy, licensing, M&A and business development.
The trend of keeping R&D professionals from being exposed to patent information on a need-only basis is reducing as companies realize that product innovation today requires more than just the strategy of applying innovative thinking.
Till date, popular reasons for having research teams to not look at patent data have been patents research can - bias the innovative-thinking of inventors, reduce possbility of a "willful infringement" being proven in the event there is a future infringement case and finally, result in increased number of prior art reported in new patent applications.
More and more senior R&D professionals such as Technology Managers and Product Heads are turning to patents to refine their R&D strategies. They want to make sure that the teams are not wasting research time re-inventing the wheel and if research is to hit a patent wall eventually then its better to research alternative approaches from day one. Open Innovation is also to be driving this shift as R&D teams collaborate with individual inventors, universities and research institutions and tap external IP for their products. They are inclined to buy (or license) a portfolio of strong patents available from such sources rather than invest into research and generate workaround approaches.
Doing so, allows companies to bring their products faster to market, reduces research dollar wastage, decreases risk of engineering failure and improves quality of new patent applications and overall patent portfolio.
For leveraging IP insights technology managers need more than just search results. They need to create portfolios (either by company or by technology) and analyze them. Patent analysis solutions play a significant role here for R&D Managers allowing them to:
Product innovation requires closer integration of IP Strategy in day-to-day decision making. Decisions such as where to spend R&D dollars, which direction to take existing products into and what research areas to exit are core to any technology driven company and must have IP as one of the key considerations.
Patent analysis solutions such as Patent iNSIGHT Pro can help technology managers gain actionable insights from IP. We are seeing a growing adoption of the solution amongst senior R&D professionals and assume that the trend is reflective of the fact that day-to-day technology decisions are increasingly based on intelligence from patent data.
Amongst various analyses performed on patents, the area where specialized software helps immensely is text-mining and two of the most popular text mining techniques used over patent data are:
- Text segmentation / Tokenization
- Text Clustering / Topic identification
Text segmentation is a process of analyzing the patent text and identifying smaller meaningful segments from the text. These segments are also called as Tokens or keywords. Various analyses can be performed using these tokens; however for large patent sets the number of unique tokens can be very high thereby making it unsuitable for certain types of analyses.
Text clustering helps identify important topics or concepts (clusters) from a set of documents. Clustering of key patent data documents (such as Title, Abstract and Claims) has been used in various Patent Analysis tools and can help bring out the otherwise hidden insights within patents. Analyzing relationships between generated clusters or analyzing relationships between patent classifications and clusters are popular mechanisms used by researchers especially those in a competitive intelligence role.
Classical algorithms used for clustering are K-Means or Bayesian Naïve. Their output is a set of categories (single level or hierarchical), each of which contain a group of patents. The name of the category is usually derived from the text of the patent itself and can also be a combination of multiple terms. Usually advanced algorithms can understand parts-of-speech and merge names accordingly. For instance, “tip of the probe…”, “using a probe tip…”, “with a probe whose tip is used for…”, and “probing the substrate with the tip…” will be merged under “probe tip”.
Algorithms can also differ on their capability to cluster patent under single or multiple topics. For patents it is desirable to have algorithms that place a patent under more than one topic since an attempt make a best-match for the patent under a single topic may lead to errors in interpretation.
One of the key challenges of clustering algorithms has been to make the overall process transparent for IP Professionals who usually find it hard to accept results of “black-box” clustering engines. Newer clustering algorithms provide the analyst control over most aspects of the clustering process thereby allowing then to fine tune the clustering output and train the algorithm to deliver more relevant results. The analyst can also now specify how deep s/he wants to go and choose to highlight broader or finer (more specific) topics.
Another challenge has been to make it easy for the analyst to influence the choice of the terms being picked up such to avoid picking up meaningless terms or to give importance to a certain class of terms. Apart from just being able to ignore some words (stop-words) it is important to have the power to set advanced filters that decide the choice of the labels used to represent the topic. For instance these can be, whether to ignore or give more importance to - words in ALL Caps, words starting with or containing a number, words containing more than one hyphen (compound names) or just words that are too long or too short. Even a minor change using such filters can have a reasonable effect on the topics that are chosen.
To see patent text clustering in action on patent data and understand its benefits via a sample use case scenario please read the full article here.
White-spaces are gaps in a technology landscape that have potential for attaining exclusivity. Many Technology and IP managers today look at white-space analysis as one of the key methods for strategic product innovation. Using white-space analysis they:
In Patent iNSIGHT Pro you can use a combination of user defined categories and co-ocurrency analysis to conduct detailed white space analysis.
To start with, you should be clear along which lines or dimensions you are looking for gaps. Such as - By Product, ByMarket, By Method of Use, by Capabilities or By Application or Business Area and define the exact categories within the dimension.
The white space analysis activity proceeds in five steps:
1. Conduct a broad search and create a set of patents
2. Generate keywords (terms/tokens) from the claims of patents. Use the stop-word customization and keyword generation feature to generate a comprehensive set of keywords from the claims of the patents.
3. Cleanup keywords and assignees using various tools in the software. The raw lists of keywords and Assignees can be cleaned using multiple tools such as Fuzzy matching or by applying a thesaurus.
4. Categorize (Bucket/Group) patents along the dimensions decided for the analysis. In Patent iNSIGHT Pro we call them user defined categories or UDC for short. Depending on the dimension the method of categorization will differ. For large sets of patents manual categorization will take a lot time and there are ways by which you can automate the process.
5. Look for gaps and patterns by generating the following analysis matrices:
6. Finally, once a white-space is detected, you must conduct a targeted search across patent databases and undertake critical manual review of the patents around it to confirm the existence of a white-space.
I have been asked by many researchers on how an Excel pivot table is different from the co-occurrence matrix that we provide in Patent iNSIGHT Pro since both are primarily used to generate charts and trends between two or three analysis points.
While Efficiency, Ease-of-use, direct integration between unstructured and structures fields, are perhaps obvious reasons, I feel two key capabilities make Patent iNSIGHT Pro co-occurrence analyzer a lot more powerful for the end researcher:

2) Capability to create subsets from the matrix and slice the subset further by a different dimension
Lets say if your question was “In a particular space, which companies were most active at the peak of the technology lifecycle and at that time what countries did they focus on for protecting their inventions?”For this, one would first look at the Assignee-Filing Year spread and see which year(s) saw the peak filing activity. Then only for those patents in the peak years, analyze the coverage (Assignee – Family Countries).
So what you intend to do is pick up a subset of patents from the results of one relationship and apply another relationship to the subset. In Patent iNSIGHT Pro you can select a couple of cells in the Assignee- Filing Year relationship, right-click to group the patents and then jump to the Assignee-Family Coverage relationship for the subgroup all within 4-5 clicks. I will leave it to you on how one could achieve that in Excel.
In sum, if you think of it, both the capabilities appear as must-have if you think of a co-occurence matrix as a powerful analysis tool to manipulate, slice-dice and dig through the patent data and not just as a precursor to generating a chart.
For companies it is critical to detect white-spaces and patent minefields early in the R&D cycle each of which can perhaps generate or save millions of dollars at a later stage. Traditional graphs and charts are good for displaying the results of an analysis activity but not for quickening and improving the analysis process.
An increasingly used mechanism is visual analysis of patents that involves 2-Dimensional spatial patent visualization and leverages the capability of the human visual system to identify patterns and anomalies. The key advantages of visual patent analysis are that you can drastically reduce the time-to-insights and explore IP-congested technology spaces in a swift but efficient fashion.
The ease of use and intuitive nature of visual analysis tools makes it easy for even business and R&D teams to use for their analysis needs. (Usually in organizations, the R&D, the patent information team, the legal team, the marketing cum business strategy team and the licensing team are involved in various parts of the IP strategy driving a product.)
Other important benefits which visual patent analysis provides:
To sum up, visual analysis is a powerful method to address challenges posed by patent information overload.
As an Intellectual Property Professional, it is important that your strategy is clear before the patent drafter begins to write the claims. There are many claims construction approaches to attaining exclusivity for your innovation either by a broad claim, a series of narrow claims or a combination of both. While your exact strategy makes a lot of difference to the way claims are constructed, an important consideration is the choice of words.
The choice of words that you make will aid not only in patentability of the applications but also, at a later stage, in freedom-to-operate and infringement. Experienced drafters know that it is important to avoid commonly used words in the domain of the invention.
One way that you can prepare a claims wording strategy is to create a set of closest prior art and using a text mining software, segment (tokenize) the claims. In case of patent drafting, it is best that you do not apply any taxonomy or thesaurus to fuse generated segments (or keywords) since you would like to see all popular variations.
For organizations, its advantageous to view these statistics in context of other companies in the same domain (using a Assignee-Keyword matrix). Interpretation made from these matrixes can help not only in the choice of words but also in your overall patenting strategy for your product.
For instance I segmented the claims and created a similar matrix in a search set for a drug (citalopram) in Patent iNSIGHT Pro Co-occurance Analyzer and exported that into a Patent Assignee-Keyword Matrix in Excel. While many different interpretations can be made from such a matrix, if your interest is to work around key claims then the spread of assignees around the keywords can greatly help your choice of words for the claims.
The matrix also helps in competitive intelligence. For instance a look at all the claim segments containing the words "disorder", "phobia" or "syndrome" gives a clear indication of the applications areas that are being targeted by the companies.
So, while technology landscaping requires clustering the keyword segments into topics using various clustering algorithms, claims keyword analysis has many advantages for creating a patenting strategy.