Patent Evaluation

PATENT DUE DILIGENCE

During 2008, upwards of 1/3 of investment-related legal expenses were allocated to IP due diligence.


	Understand the business, technology and legal quality of your patent to its involvement in a proceeding or business process
	Decode the attributes of your competitor’s patent
	View the strength of your patent based on nearly 30 evaluation points
	View the patent’s position in its technological landscape
	View potential licensees and generate additional revenue

Determining patent quality and value is one of the most pursued endeavors by portfolio managers, technology investors, M&A teams, litigators, R&D executives, and CFOs. The complexities surrounding methods of calculating patent value must consider time dependant metrics such as remaining patent life, market size, general health of the economy, and patent quality.

Patent quality is the basis for almost all substantive decisions based on patent value, whether to assess the commercial or enforcement qualities of a single patent in a licensing negotiation, or analyzing large scale patent collections to maximize portfolio asset value.

At any given time, a patent portfolio will contain a large number of patents of nominal quality, and on one end, a smaller number of exceedingly high quality patents, and on the other end, a smaller number of exceedingly low quality patents.

In any given infringement litigation or licensing proceeding, the patent of interest will be either low quality, high quality, or of a nominal quality. In the above instances, management or court decisions will directly correlate to a financial loss or gain. Understanding the business, technology or legal quality of a patent prior to the decision to involve a particular patent in a proceeding or business process can profoundly affect the outcome, and its financial impacts.

Patent Evaluation, PFI^TM

PFI provides a quantitative analysis of patent quality to aid in fast, high resolution identification of high / low quality patents to support management decisions – objective, transparent, repeatable.

A single score patent rating system is incapable of providing the transparency of the many components of a patent that contribute to qualitative value. Without fully understanding specific attributes of a patent, no reasonable licensing, investment, business or litigation decision could be rendered.

PFI Reports compute and score 20 separate data fields specific to (a) legal quality; (b) commercial quality; and (c) technology quality.²

PFI uses the peer-reviewed results and conclusions of more than 20 PROVEN empirical studies on statistical patent quality analysis by noted economists, academians and scientists.³

All studies and papers on patent analysis shows that at least one Patent Of Interest is needed, and at least one Homogeneous Control Group of patents. This group of most closely related patents can only be generated through semantic technology. Using our Latent Semantic Analysis search technology, the system automatically creates a patent search query using the claims text of the target patent. It finds the 100 patents most closely related to the target patent, the ”technology sphere”.

Technology spheres are dynamic. As more patents are in any given technology area, the scope of each patent necessarily becomes narrower. Over time, the increment value of each additional patent becomes increasingly small, however, the pioneering patents that created the technology sphere can become increasingly valuable.

Patent quality indicators are also time dependant. As just one example, a patent that remains un-cited for years with highly competitive technology sphere may prove to be very low quality, and not warrant the continued investment of patent maintenance fees.

The PFI analysis process is fully transparent.

Comprehensive and detailed papers describe the process for computing and evaluating every one of the more than 20 discrete data fields scored by the PFI system. And because patents are complex, our Portfolio Management Solution DSS leaves it to the IP managers to decide what specific factors should be evaluated, and how they should be weighted to support any given portfolio analysis – such as patent evaluation for triage or portfolio pruning, assertion, or other business objectives. So, IP managers can independently change the impact of each factor relative to the most pressing business objective.

The PFI system uses PatentCafe’s LSA search technology to identify the “most closely related patents” for qualitative analysis – including patents that could be judged to be “obvious” under KSR. It’s the only patent scoring system currently available that directly ties quality evaluation to the impact of KSR, one of the most important IP decisions by the US Supreme Court.¹

Patent Factor Index:
1.Only Listed Patents:299 EUR
2.Buy 10 for 2,499 EUR: 249.90 EUR 17% Off

For more information please contact us

You can order Objective Statistical Evaluations of the strength of your patents here. You will receive a consolidated quality report via email. Your report data remains confidential and objective. The reports are computer generated using complex algorithms, and do not involve human analysis.

References

¹ Patent Quality Impact Following KSR v. Teleflex

The Supreme Court Decision in KSR v. Teleflex (“KSR”) changed the long-standing definition of “obviousness”. After KSR, the courts read the “broadest interpretation of the claims” to assess “prior art” that could lead to validity. The US Patent and Trademark Office (USPTO) implemented new Examination Guidelines for Determining Obviousness. The quality, and correspondingly at some level, the value of a patent estate changed. Specifically, KSR changed the definition of what may constitute prior art – and what prior art that previously would not challenge patent validity, now does.

Because patents granted under the old standard are now vulnerable to challenge, companies with large intellectual-property portfolios will have to reassess the value of their patents. Companies could be held liable under Sarbanes-Oxley if they fail to look at the record of each patent to determine its vulnerability.

Making it easier to challenge patents will diminish the value of many existing patents, and that may require corporations to notify shareholders of reduced assets in their intellectual-property holdings.

² In order to shape a “real world” perspective on understanding patent quality, and hence, its potential value, our technology combines various interrelated indices to score your patent using the following criteria:

Enforceability
Total Relevancy Strength
Novelty
Claim Scope Breadth
Validity Confidence (Un-Cited Earlier Filed Art)
Validity Confidence (Un-Cited Concurrent Art)
Sustainability In Opposition
Litigation Avoidance
Forward Citation Value Contribution
Backward Citation Value Contribution
Enforcement Licensing Potential
Partnering Licensing Potential (Cross-Classification)
Crowdedness (Potential Licensees)
Divestiture Licensing Premium (Patent Group)
Patent Group Competitive Position
In-License Opportunity
Technology Advancement
Technical Sophistication
Combinatorial Accession
Technology Cogency

³ PFI Reports incorporate the conclusions drawn from a number of statistical studies performed on large patent data collections. These references are provided for those interested in further study.

Allison, John R., and Tiller, Emerson H. Internet Business Method Patents. McCombs School of Business, University of Texas at Austin: http://utopia.utexas.edu/articles/tbr/business_patents.html
Criscuolo, Paola, Genua, Aldo and Verspagen, Bart. (2004). An analysis of the source of EPO citations: applicant vs. patent examiner citations. Applied Econometrics Association [AEA].
Criscuolo, Paola. (2003). Reverse Technology Transfer: A Patent Citation Analysis of the European Chemical and Pharmaceutical sectors. Maastricht Economic Research Institute on Innovation and Technology [MERIT] and Science and Technology Policy Research [SPRU].
Fleming, Lee And Sorenson, Olav. (2004) Science As A Map In Technological Search. Strategic Management Journal, 25: 909–928.
Gibbs, Andy. (1996) Ironman Inventing, The Invention Business Game. Computer Modeling System and Method for Adaptive Relational Testing [SMART] of Innovation. Reg. TX 4-686-712.
Griliches, Z. (1981). Market value, R&D, and patents. Economic Letters 7, 183–187.
Hall, Bronwyn H., Jaffe, Adam B. and Trajtenberg, Manuel. (2004). Market value and patent citations. JEL Classification: O31, O38 – 2004.
Ikovenko, Sergei, Invention Machine Corp. Trends of Engineering System Evolution. Innovazione, 2003.
Jaffe, A., and Trajtenberg, M. (2000). Market Value and Patent Citations: A First Look. Working Paper No. 7741. National Bureau of Economic Research [NBER].
Lanjouw, Jean O. and Schankerman, Mark (1998). Stylized Facts Of Patent Litigation: Value, Scope And Ownership. Department of Economics, London School of Economics and Political Science.
Lanjouw, Jean O. and Schankerman, Mark (Revised March 2000) Characteristics of Patent Litigation: A Window on Competition.
Landauer, T. K. & Dumais, S. T. (1997). A solution to Plato’s problem: The Latent Semantic Analysis theory of the acquisition, induction, and representation of knowledge. Psychological Review, 104, 211-140
Mann, Darrell. (1999) Using S-Curves and Trends of Evolution in R&D Strategy Planning. Department Of Mechanical Engineering, University Of Bath.
Marco, Alan C. The Option Value of Patent Litigation: Theory and Evidence, 2003
Petrov, Vladimir. (2002). Laws of Dialectics in Technology Evolution. The TRIZ Institute.
Razgaitis, Richard. Valuation and Pricing of Technology Based Intellectual Property. Wiley, 2003.
Reitzig, Markus. (2003). What Do Patent Indicators Really Measure? Testing Current Theory on Value Drivers of Innovations Within a Structural Two-Stage Discrete Choice Simultaneous Equation Model.
Reitzig, Markus. (Version: December 2003) What Do Patent Indicators Really Measure? – A Structural Test of ‘Novelty’ and ‘Inventive Step’ as Determinants of Patent Profitability.
M. Trajtenberg, A. Jaffe and B. Hall (2000), The NBER/Case Western Patents Data File: A Guided Tour
Varian, Hal R. (2003) IBM Symposium on the Coevolution of Technology - Business Innovations Innovation, Components and Complements. October 5, 2003.