It's All About the Numbers: SuperCrunchers of Patent Data will Gain Competitive Advantage

A recent book entitled Super Crunchers: Why Thinking-By-Numbers is the New Way to Be Smart (available at http://www.amazon.com/Super-Crunchers-Thinking-Numbers-Smart/dp/0553805401) presents an intriguing perspective of how forward-thinking companies can use the wealth of data available today to obtain an edge against competitors. The book, written by Ian Ayres, an econometrician and law professor at Yale University, posits essentially that he who crunches the available data will come out ahead in this modern world of massive amounts of data. A detailed review of this book from Newsweek is found here: http://www.newsweek.com/id/40860.

The "Super Crunchers" premise applies strongly to the world of patents. Indeed, when leading companies such as P &G, GE and others engage in multi-faceted corporate intelligence programs, it cannot be a controversial to contend that those companies that mine and apply the results of data analysis of both their own patent portfolios and those of competitors will obtain valuable information that can be deployed to make better business decisions.

Moreover, the application of patent data dovetails nicely with the modern world of innovation and product development, which focuses sustainable and disciplined internal processes rather than the traditional methodologies that favored, in large part, intuition. Part of these processes can and should be continued review of your company's patent portfolios, and those of competitors.

Before your company actually integrates patent analytics into your organization to augment the information that you use to make business decisions, you need to ensure that the analytics that you are using actually provide actionable business insights. To constitute actionable business insights—that is, information that can readily be applied to your company's business decisions—patent data must be provided to you in a business relevant format. Moreover, the right data must be extracted from patents. I am now an IP Business Strategist and Consultant (more info here: www.jackiehutter.com). However, I know from my time as a consumer of expensive patent analytics products as an in-house patent counsel, providing the right data is not a given with most patent analytics providers. To the contrary, few patent analytics vendors understand the content and meaning of patent data in a way that allows them to extract data in a business-relevant manner.

As a potential purchaser of patent analytics, it is important to realize that all data present in patents is not equal. Patents actually contain two types of data. A patent document discloses technical information that a company would likely rather be kept as a trade secret. Of course, a company does not disclose confidential information to the public out of altruism. Rather, the only reason that this otherwise confidential information is disclosed to the public is because in exchange for this disclosure, the US government grants exclusive ownership of the claimed invention to the company for a limited time (usually 20 years from the date of filing the patent application).

When your competitor gets a patent, your company is excluded from making, using, selling, offering to sell or import the claimed invention. In short, a patent granted to your competitor keeps your company from doing some commercial act that your company would otherwise be legally entitled to do. The business information relevant to your company therefore is what your competitor seeks to own. As such, when your company seeks to obtain and deploy information from patents, your data analysis should focus not on the entire patent document, but on what the patent's claims say.

So, if your company seeks to join those forward-thinking organizations that have embraced the "Super Crunchers" philosophy and seek to apply it to the world of patent data, you must ensure that your vendor is analyzing the data in patents that you care about, that is, the information in the claims of the patent. If the claims are not the focus of the patent analytics vendor's product, you should pass because the data that you obtain will be suspect when applied to your company's business questions.