By Scott Oldach and Nick Stabinsky of Patent Board™Mr. Oldach, Vice President - Advisory Services, leads all the advisory services activities of
The Patent Board. He brings over 30 years of services experience ranging from Strategy Consulting
and Transformational Leadership, to technology innovation and commercialization. Mr. Oldach has
worked in a broad range of industries including Aerospace & Defense, Automotive, Consumer
Products & Electronics, Financial Services, Health Care, Energy, Technology, Telecommunications,
Retail, and Wholesale. Previously he grew consulting activities within IBM Global Services, where he
was one of the founding members of IBM Consulting Group, The MAC Group, Booz Allen and Hamilton
and Arthur Anderson.
Mr. Stabinsky, Managing Consultant – Advisory Services, leads large projects and
opportunities within the Advisory Services group at the Patent Board. He brings expertise in
intellectual property law and management to the team, combined with technical experience in electrical
engineering. He consults in various industries, including Medical Devices & Services,
Telecommunications, Semiconductors, Information Technology, Aerospace and Defense, Consumer
Goods, and Chemicals to U.S., European, and Japanese clients. Mr. Stabinsky previously worked
for a boutique High Vacuum Original Equipment Manufacturer (OEM) where he focused on Services and
Business Development.
What does your patent portfolio say about your enterprise? Does it suggest
that you are the most prolific at creating patents like IBM or Samsung. Does it say that you have
a breakthrough technology that is just starting to be commercialized such as E-Ink. Patent
analytics provide IP professionals a tool that can make their work more efficient and
professional. More importantly patent analytics when used appropriately can anticipate future
firm value and provide key insight into competitor profiles. The analyses do not replace legal or
technology professionals; instead they supplement their work by providing an underlying technology
basis for making business, legal and technology choices that are appropriately in the hands of trained
professionals. This article will highlight the valuable uses of patent analytics and suggest some
inappropriate uses for these tools.
What Are Patent Analytics And What Are The Key Assumptions?
“Patent Analytics” is a broad, term used to define
any metric, indicator, mathematical logic or methodology that adds quantification to the formal but
semantic knowledge in a patent. While patents provide a rich source of knowledge about
technological ideas, the knowledge is represented in words and not numbers. Moreover, the
knowledge is appropriately focused on the innovative idea and not the business value of the
patent. Despite how confusing that may sound, patent analytics is frequently distilled into four
basic approaches that are applied to individual patents or entire patent portfolios. These four
basic methodologies include Bibliometric Analysis, Patent Component Analysis, expert opinion analysis,
and financial modeling.
Bibliometric Analysis focuses on the forward and backward
citations to a patent to statistically identify patents of greater importance, and by proxy, patents of
greater value. There are several key underlying assumptions behind Bibliometric
Analysis. First it is assumed that by citing a patent, the cited patent is recognized as valued prior
art. This was proven in the late 60’s with a research project that showed a patent
receiving more than 50 citations would be seen by practitioners in the field as seminal work.
Moreover, there is an assumption that the patentee and patent examiner have made a fair effort to
identify relevant prior art to a patent. Consequently, a reference from one patent to another
patent is indicative of the value that another person has implicitly placed on the cited patent.
Companies such as the Patent Board, 1790 Analytics, and Patent Café use this type of
analysis.
Patent Component Analysis uses measurement techniques to
analyze specific segments of a patent specification. The indicators include factors such as
technology code, word counts, pendency duration, examiner identification, prosecuting attorney
identification, the number and type of claims, and sometimes the file history of the patent to estimate
the value of a patent. Patent Component Analysis assumes that the value of a patent can be
modeled based on automated quantification and comparison of the components of a patent.
Companies such as Ocean Tomo, and Patent Café use this approach.
Expert Opinion Analysis employs subject matter experts to read
the patents and to reach a determination of the value of the patent. This valuation usually
employs one or more of four key methods: Comparison to similar patent sale or license, future income
modeling, replacement or “design around” modeling, or a probabilistic approach added to
the above. Each of these methods formalize and quantify the judgment of professionals in a
structured manner. The professional applying these tools could come from an accounting,
technology, and / or legal background. This analysis assumes a competent professional with
adequate experience in the technology in question with legal, accounting and market understand to
provide good judgments. Companies such as Taeus use similar approaches.
Financial Modeling requires an existing revenue stream that can
be aligned to a patent or set of patents. If this exists there are strong financial models that can
be used to attach a value to the patent(s). This analysis can be adjusted to reflect future
expectations and potential financial changes that could affect the value of the patent(s). While
this is the most pragmatic way to define the value of a patent, it requires an existing revenue stream
and an ability to align the patents to the revenue stream. The key assumption is that historic
revenue streams are indicative of future revenue with adjustments. Consultancies
such as CRA International specialize in IP valuation.
How Should Patent Analytics Be Used — And How Should They Not Be Used?
Patent Analytics provide powerful insight into individual patents and patent portfolios
when used appropriately. They do not replace management judgment and are typically not the
only, deciding parameter in any decision, but rather an important input that should be considered with
other pressing business, technology, economic and legal factors. In many
instances, where the issue at hand involves just a few patents, the traditional approaches of Expert
Opinion Analysis and Financial Modeling are often most efficient. However, when the top 500
patenting entities hold over 1,768,327 patents combined, with an average portfolio size of 3,530
patents, making informed decisions around large numbers of patents quickly becomes a daunting
task. Technology analysis, competitive intelligence, product planning and M&A are all
situations where automated analytics are at their best --to quickly and efficiently assess large groups of
patents. In each of these situations the metrics can quickly quantify, prioritize, and
identify important patents and groupings of patents. These metrics effectively funnel thousands
of patents down to a manageable number that patent professionals can sink their teeth into.
While the metrics are not exhaustive, they can answer many important questions,
such as: Who has had some of the most influential patents? Which groupings of patents are
likely to be the most impactful? Which patents should be abandoned? Where are a
company’s true technology competencies? Who is performing research in the field?
And, which patents are probably the most licensable? As long as the experienced
professional knows when and how to use them, Patent Analytics save time and cost.
In upcoming issues we will review in greater detail patent analytics and the
assumptions underlying them. We will also feature The Patent Board industry-specific Patent
Scorecard highlighting the following industries that will include Information Technology (May),
Electronics & Instruments (June), Energy & Environmental (July), Pharmaceuticals (August),
Medical Devices & Services (September), Biotechnology (October), and Telecom &
Communications (November).
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