How To Represent Relevant Business Data About Competing Patent Applicants


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How To Represent Relevant Business Data About Competing Patent Applicants

  1. 1. Competing Patent Applicants’ Business Relevant Data Representation Nissrine El Marchoum
  2. 2. Outline  Background  Patent Application & Evaluation  Business-Relevant Competing Applicant Data  Stakeholders  Data Sources  Relevant Data  Country of Applicants  Commercial Potential  Monopoly Power  Patent Portfolio  Competitor Monitoring  Competing Applicants’ Data Representation  Back Office  Data Search Representation  Data Representation  Conclusion
  3. 3. Background: Definitions  A Patent: the right granted to an inventor -for a specific period of time- that forbids any other party from making, using or selling his invention without his permission (EPO).  A patent is a negative right  Patent Applicant: entity who requests the ownership of a patent via a written request.
  4. 4. Background: Motivation & Assumptions  Motivation  Provide visual aids and decision making basis to decision makers  Assumptions  Difference between European patent system and that of other countries rather trivial.  Stakeholders are mainly investors  Discard patent examiners perspective (matter of scope)
  5. 5. Patent Application & Evaluation  Applicants fill patent application documents and provide endorsing documents  Application evaluation takes place  By Patent Examiners  Final Decision communicated to the patent applicant  Grant, Rejection or suspension
  6. 6. Stakeholders of Patent Applicant Information  Patent Examiners are rather interested in the intellectual property aspect of the patent  Business stakeholders:  Firms interested in investing in new technologies/markets  Contribution to background checks on potential partners  Track competition
  7. 7. Patent Applicants’ Data Sources  Not easy.  Patent Databases hold limited information about patent applicants (e.g. name, address, date… etc.)  Use them as a starting point for research  Large Firm Listing Databases (eg. IBISWorld)  Interesting business information.  No direct mapping to the applicants  Best Practice:  Investigate patent business-relevant information  Combine results with data about patent applicants from external data sources
  8. 8. Business-Relevant Data About Applicants 1. Country of Applicants 2. Commercial Potential 3. Monopoly Power 4. Patent Portfolio 5. Competitor Monitoring
  9. 9. 1. Country of Applicant  Use country of competing patent applicants to compare patent systems for a cost-benefit analysis  Patent fees  Flow of returns Is it economically viable to invest in the patents the applicants are holding (or apply for)?
  10. 10. 2. Commercial Potential  Potential: ability or intent to commercialize the subject of the patents at hand  How profitable is the commercialization of the invention/idea?  Applicants holding a patent for fairly long can be a proof of its commercial value
  11. 11. 3. Monopoly Power  Does the fact that competing applicants hold some patents imply that these applicants own the exclusive right to monopolize the concerned inventions?  Frequency of Patent Renewal  Owning a patent and frequently renewing it tells a lot about the patentee.
  12. 12. 4. Patent Portfolio  Approach revolves around what patent applicants & what they intend to do with it.  Patent Portfolio Diversification  Many patents of poor value vs. few patents of high value  Patents in dead fields vs. patents in promising fields  Therefore, stakeholders can infer:  Diversification Strategies  Investment interests  Competitive Potential
  13. 13. 5. Competitor Monitoring  Strategic Management  Track the competing applicants’ pool of patents and react accordingly  Holger Ernst (2003), Beisheim Graduate School:  Use of indicators for monitoring competitors by assessing their patenting strategy  By extension define the key aspects and motivations that drive their investment decisions.
  14. 14. Important Patenting Indicators for Competitor Monitoring Patent information for strategic technology management, Ernst, H. 2003
  15. 15. Data Representation: A concept  Back Office  Cloud Computing Technology  Consider Cost  Use Data Mining Algorithms
  16. 16. Data Search & Representation Process Filter Search Display Results
  17. 17. Data Search & Display Process Explained  Selecting the search filter  By Patent Applicant’s Name  By Country  By Field of Business  By Inventors  Perform Search Algorithms  Build a Model  Clustering, classification, data analytics algorithms…
  18. 18. Data Search & Display Process Explained  Display of Results
  19. 19. Conclusion  Gathering relevant data from a business perspective is not a trivial task  Requires analysis & business background  Already existing DBs do not explicitly hand in the information  Future Work Suggestions  Data Repositories holding patent applicants data
  20. 20. References  Alcácer, J., Gittelman, M., & Sampat, B. (2009). Applicant and examiner citations in u.s. patents: An overview and analysis. Research Policy.  Epo - glossary. (2012, 12 20). Retrieved from  Ernst, H. (2003). Patent information for strategic technology management. World Patent Information, 25(2003), 233-242. Retrieved from .European Patent Office. (2012). Glossary. Retrieved June 10, 2013, from: support/glossary.html#p.  European Patent Office. (2013). European patents and the grant procedure. Retrieved from  Hsieh, C. (2012, 11 13). Patent value assessment and commercialization strategy. Retrieved from  Kelly, E.T., & Shear, T.E. (2003). A Researcher’s Guide to Patents. Plant Physiology, 132,1127-1130.  Lanjouw, J. O., Pakes, A., & Putnam, J. (1998). How to count patents and value intellectual property. The Journal Of Industrial Economics, XLVI(4), 405-432.  Pakes, A. (1986). Patents as options: Some Estimates of the Value of holding European Patent stocks. Econometrica, 54(4), 755-784. Retrieved from  Pitkethly, R. (1997, March). The valuation of patents : A review of patent valuation methods with consideration of option based methods and the potential for further research. Retrieved from  Webster, E., & H.Jensen, P. (2011). Do Patents Matter For Commercialization?. Journal of Law And Economics, 54(2), 431-453. Retrieved from
  21. 21. Thank You 