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How To Represent Relevant Business Data About Competing Patent Applicants

How To Represent Relevant Business Data About Competing Patent Applicants






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    How To Represent Relevant Business Data About Competing Patent Applicants How To Represent Relevant Business Data About Competing Patent Applicants Presentation Transcript

    • Competing Patent Applicants’ Business Relevant Data Representation Nissrine El Marchoum
    • 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
    • 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.
    • 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)
    • 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
    • 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
    • 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
    • Business-Relevant Data About Applicants 1. Country of Applicants 2. Commercial Potential 3. Monopoly Power 4. Patent Portfolio 5. Competitor Monitoring
    • 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)?
    • 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
    • 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.
    • 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
    • 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.
    • Important Patenting Indicators for Competitor Monitoring Patent information for strategic technology management, Ernst, H. 2003
    • Data Representation: A concept  Back Office  Cloud Computing Technology  Consider Cost  Use Data Mining Algorithms
    • Data Search & Representation Process Filter Search Display Results
    • 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…
    • Data Search & Display Process Explained  Display of Results
    • 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
    • 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 http://www.epo.org/service-support/glossary.html.  Ernst, H. (2003). Patent information for strategic technology management. World Patent Information, 25(2003), 233-242. Retrieved from http://www.journals.elsevier.com/worldpatent-information .European Patent Office. (2012). Glossary. Retrieved June 10, 2013, from: http://www.epo.org/service- support/glossary.html#p.  European Patent Office. (2013). European patents and the grant procedure. Retrieved from http://www.epo.org/service-support/publications/procedure/european-patents.html.  Hsieh, C. (2012, 11 13). Patent value assessment and commercialization strategy. Retrieved from http://www.sciencedirect.com/science/article/pii/S0040162512002405.  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 http://www.jstor.org/discover/10.2307/1912835?uid=2&uid=4&sid=21102433476691.  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 http://users.ox.ac.uk/~mast0140/EJWP0599.pdf.  Webster, E., & H.Jensen, P. (2011). Do Patents Matter For Commercialization?. Journal of Law And Economics, 54(2), 431-453. Retrieved from http://www.jstor.org/discover/10.1086/658487?uid=2&uid=4&sid=21102433428181.
    • Thank You 