Patent Data Application – Series I

Law Practice planning through patent data analysis

This new series aims to find possible role of patents in decision support and business development. In this post, I am trying to list some possible applications of patent data in business planning for small and medium sized law firms.

Law firms are like any commercial entity which need cash, clients, Intangible assets, competitive edge and right business planning to stay profitable. Patent data are wealth of information that could be leveraged to find invisibles and data for strategic decision. 

In my view, the patent data can be used for:

Business Planning:

Practice location planning: Many PTOs around the world provide bibliographic data which could be used to map inventor, assignee, technology area, etc. A law firm expanding their practice and planning new offices in a country could use these data to plan offices, resources, and predict financial benefits based on past filings.

Resource Planning: Patents are indicators of technological advancements. An emerging law firm may want to plan its resource based on market demands and technological advancements in certain geographic region. A patent based trend analysis can provide interesting insights towards legal and technical resource requirements in foreseeable future.

Business Development:

Targeting New Clients: Patent data could give valuable insights about target companies. It may help the BD officers to target right in-house attorneys, assess technical areas of filings, profile target company, etc.

Finding Share of Wallet: Data analysis could help medium sized law firms in analyzing whether the top clients are using competitor law firms for their filings. This could help in gauging effectiveness of service, client loyalty, and possible business negotiation areas.

Building new partnerships: Companies file patents at various geographies. Patent data could help small and medium sized law firms find possible overseas partners who can cross refer each other in case of patent family extensions. This analysis could be done looking at various angles.

Competitive Benchmarking & Intelligence

Benchmarking Pendency: This analysis could help a law firm in making a better business pitch. A law firm with lower pendency may help in winning more accounts. Also, this analysis could be extended to see if patent filed by competition have seen significant change in claims during prosecution.

Claim Strength analysis: A semi-automated analysis to benchmark competition on claim strength.  There are various proven scoring mechanisms that could also be used to make better business case.

Resource mapping: Various countries allow law firms to put information about their practice areas and resources or various patent offices provide attorney data. This data could valuable source of information in order to map resources and law firms. This analysis is best done when complemented with primary and secondary research data.

Effective Prosecution:

Examiner relationship network: Law firms can conduct examiner relationship network to understand how examiners world together in various technology areas. Also, a technology specific network may also provide leads to HR department.

Technology area and type of rejections: A law firm specializing in niche areas or emerging technology areas may want to understand common prosecution hurdles. This may help them in better planning while drafting applications. This analysis could be combined with examiner analysis to identify any pattern.

Patent application scoring: Law firms handling clients with large volume of pending application can use proven techniques to prioritize efforts. The scoring can be done on various parameters.

Challenges:

Underlying Data: The above mentioned analyses are data intensive and require correct data for any meaningful result.

Automation: Based on my experiences with PTO data, I think data provided by patent offices around the world require lot of normalization. They are in no way ready to use for such data intensive analysis. Automation is essential for such analysis. Automation can be used for range of activities such as pulling right data from websites, normalizing & cleaning crude data.

Data handling: These analyses may involve data which may run in hundreds of thousands of records. These analyses also require correct understanding of the data. A single data handling mistake can change the face of entire analysis.

Risk of misinterpretation: “Little knowledge could be dangerous” this is true for these kinds of analysis. The end user and analyst must question the output and check the sanity of the results.

Conclusion:

These are only some ideas on patents and its application in this context. These are based on my experiences and similar consulting projects.  There could be other numerous applications of patent data that could help law firms.

These analyses are certainly worth spending time and money. These analyses could help a law firm in not only expanding its practice but also for regular health check. However, with a caveat that external factor should be considered while taking any action. These analyses can provide actionable intelligence but cannot replace human judgment and creativity. 

Patent Landscapes: Myth Series – II

How to create patent landscapes intelligently 

In my previous posts in this series, I tried to expose the myths related to the usage of patent landscape studies. In this post, I will explore prevalent myths related to the execution of landscape studies. This post can be useful to analysts and managers with responsibilities to conduct and/or commission patent landscape studies.

Download entire Article (Click Here)

Please download entire article from above link. The article discusses realities and action steps on below mentioned Myths.

Myth 6: Any patent analysis with charts is landscaping

Reality: Contrary to popular belief, any patent analysis with charts does not constitute a patent landscape. One chart can speak a thousand words, but mere inclusion of charts does not suffice a thorough analysis. A chart is a nice way of representation of the analysis; however, mere inclusion of chart without any specific objective may not qualify a study for a landscape. Unlike other patent analysis studies, patent landscapes have broader business perspectives and can be used by a diverse set of audience. A competitive patent intelligence cannot be deemed to be complete if it does not relate hard market facts with patent trends. There is a very thin line demarcating patent intelligence and patent mining from patent landscape projects.


Action Step: Landscape insights can cater to a vast and diverse set of audiences, such as strategists, technology managers, and attorneys. On the other hand, other patent analysis studies such as FTO and Patentability assessment have very narrow and specific objectives and are often targeted to a particular set of audience. Such analysis with very specific objective and directed to a particular set of audience cannot be termed as landscape report. Patent landscapes should be created with broad strategic objectives in mind. To create a high impact patent landscape report, analysts should look into ancillary data to complement the patent analysis. Landscape charts should complement the study by representing the analysis and the findings of the study


Myth7: An endless presentation with lots charts will please the end user

Reality: Bibliographic data of subject patents is the key to understand technology trends. There are more than thirty quantitative parameters that could be used to address a wide variety of business objectives. These parameters could then be co-related to create an endless list of analysis charts. However, one must evaluate the relevance of each and every chart presented in the analysis.


Action Step: Each chart should address at least one predefined objective of the study. One chart with an insightful message is better than a hundred charts without any objectives. It may not be useful or even feasible for the end user to go through hundreds of charts to find answers to his key questions. The analysis should be concise and solution oriented. An endless presentation with lots of useless charts can ultimately confuse the end user

Myth8: Automated patent analysis can provide usable insights


Reality:There are lots of automated and “cool” patent analytics tool available in the market. In my view, they are really useful when the researcher is looking for a general overview on a certain technology. However, they may not be equally suitable for making key strategic moves


Action Step:Normally, automated tools rely on artificial intelligence to explore the area of interest. They may provide useful insights on the subject field. However, artificial intelligence, no matter how precise it claims to be, cannot replace human judgment and intelligence in presenting a meaningful analysis.


Myth 9: Organization of underlying data is not important


Reality: Landscapes do not provide magical answers to the questions instantly and definitively. Organization of data and in-depth analysis of extracted data is the key to conduct a meaningful landscape study. In certain cases, the underlying data is overlooked and not organized properly, leading to flawed inferences. For effective usage of landscape reports, it is essential that end users refer to the underlying data to validate the findings.


Action Step: A landscape report should be accompanied with user friendly and well organized reference data. End users must thoroughly understand the criteria and/or assumptions for data organization and data analysis. If patents were categorized in certain categories, tandem to address the objective, it must be understood clearly. It is also important to understand the factors considered while normalizing key bibliographic data such as assignee and inventors.

Myth 10: Patent landscape is an hourly based activity

Reality: Patent landscapes are generally planned by estimating the number of effort hours rather than by gauging the overall objective of the study. In certain cases, to fit the study within the time frame of planned hours, efforts in technical analysis are reduced or search criterion is restricted. This approach may be counterproductive for the study and may not provide optimum returns on investments.

Action Step:Landscape studies should be objective driven and must be constantly monitored and questioned to track the progress of the study. Patent landscape studies tend to deviate by size of data or by complexity of the technology. However, an adept analyst should be careful and aware of such deviations and situations while planning and executing a landscape study

I hope you will like the article. Please feel free to post your comments and views on these myths.