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I have just added the new Ideanomics Dashboard which is an interactive anlytical tool for exploring the relationships between the traditional economy and the idea-economy. Thanks to Google the whole thing animates and you can even sit back and watch the movie if you want. Please take a look and offer any suggestions you have and I will do everything that I can to make it even better by adding more countries and more indicators. I am particularly interested in ideas on what types of indicators we could find data for that speak to the emergent idea economy. Also, I am interested in hearing your thoughts on other “dashboards” that we could add that you would find interesting and useful. It is clearly a work in progress and I am busy readying new data to add as we speak, so come back often to see progress. Enjoy…

I am fascinated by the idea of “Dark Matter”, a substance which is invisible but is thought to constitute the vast majority of mass in the universe. It cannot be measured directly, but its presence can be inferred by the gravitational effects it exerts on everything around it. This strikes me as being a lot like innovation. Although it is now believed to be the most important driving force in economic growth, economists cannot measure it directly. It is observed primarily for how it appears to pull and push virtually everything else. Economists have devised a variety of ways to measure it indirectly which is one reason we spend so much effort analyzing patenting, R&D spending, and a lot of other things. This is why measurement is so important to progress in managing innovation. Until we can directly measure the most important economic aspects of innovation (such as gaining visibility into the markets for ideas, IP, and innovation) it will simply remain “dark matter”. That’s why I say, if you can’t measure IP, you can’t manage IP.

Patents create value for their owners in a variety of different ways. One of the biggest problems with nearly all patent valuation techniques is a failure to be explicit about what kind of value they are attempting to measure. It is essential to have an accurate model of value types in order to identify the source of the information that is needed, and also to formulate the correct approach for interpreting that information.

The Four Kinds of Patent Value

Patents basically allow the rights holder to pursue legal measures to prevent others from practicing the subject matter. This is the reason why many people are quick to point out that patents are only valuable in the way that they act as a blocking mechanism, and this is certainly true. However, although it is very important, it is not accurate to say that the value of a patent is purely a function of its enforceability. In practice, there are different ways to use patents to create value, and people are getting more creative about it all the time.

I group the major ways patents create private economic value into four dimensions.

1. Practicing
   
   The first and most obvious method for realizing economic value from patents is by producing and selling products which embody the patent. This is what is known as “practicing” the patent. Value derives from the producer’s ability to exclude competitors and therefore earn monopoly profits. In practice, this type of value is virtually impossible to measure directly particularly because it is nearly impossible to determine exactly how much value is attributable to the patent’s exclusionary rights versus all other factors such as superior design, branding, timing, market power, other intellectual property, and existing manufacturing efficiencies. Another problem is that the value that a company may ascribe to a patent in this context will not normally be the same as the price at which the patent would transact in the market.
2. Licensing
   
   An alternative to practicing a patent is to license its rights to another entity. Licensing value is realized when the licensee pays royalties and other fees to the licensor. Thus, value is created through royalties on the sales of any products that embody the product and therefore can be viewed as a function of the ultimate value from practicing the patent. This provides at least one way to observe directly the value specifically attributable to the patent in its ultimate application, and therefore addresses the problem with measuring practicing value. Licensing transactions also offer the opportunity to observe prices that occur in the market between willing entities. In practice, these are virtually impossible to observe because patent licenses are always confidential.
3. Litigating
   
   An entity that does not practice or license a patent can sometimes receive value by leveraging the special legal status of patents. Recently, some patent holders (often referred to as “patent trolls”) use patents as an asset in a threatened or real patent infringement suit. In this case, the patent holder does not intend to practice the patent, but seeks value primarily through settlements and court awarded damages. The majority of patent disputes are settled out of court and are confidential. But, even if known, settlements and awards cannot represent the “market” for IP as they do not occur between two willing entities and amounts are distorted by legal rather than commercial considerations.
4. Deterring
   
   “Defensive” patenting is the practice of filing patents for the purpose of providing a basis for counter-infringement claims in patent litigation. In a sense, it is the opposite of litigation value. As patent infringement litigation has accelerated, many companies have filed defensive patents to serve as a deterrant by increasing the cost to opponents of asserting patent rights. Obviously, measuring this kind of value is virtually impossible as its economic benefits are unknown except in rare cases.

One of the purposes of this taxonomy is that it helps us to understand the roles that IP plays in business strategy and therefore helps us to construct more coherent and effective IP management practices. Another benefit, is that it provides a way for better understanding patent valuation. Most patent valuation techniques suffer from a lack of clarity on this point. Because patents can create different kinds of value, we have to be clear which kind we are estimating when we do patent valuations otherwise our results will not be valid. In addition, being clear about the kind of value we are estimating makes it obvious what types of data are relevant. In subsequent posts I will show how this model of patent value is essential to almost everything we do in IP management.

NOTE: This is the third and final part of a three-part series. (Part 1 | Part 2)

In order to understand what information we need to observe to derive useful market pricing information for patents, we need to have a basic understanding of the ways that patents create value. Only then can we understand what types of transactions we are interested in observing and the correct way to interpret their meaning. In addition to this, before examining the value of patents it is essential to be clear as to what kind of value we are talking about.

Private Economic Value

Most patent valuation techniques are hampered by a failure to be sufficiently precise on what kind of value they are attempting to measure. The problem partly arises from the almost universal failure to distinguish between the scientific significance of a patent and its economic value. Even those that have made this distinction have failed to adequately distinguish between the private economic value they generate for their owners/licensees and the public economic returns they create for society. To produce the kind of patent valuation metrics described above, it is essential to have information that measures the private economic value patents create.

IP Market Signals

It is also essential to understand the way different actors in the IP supply chain transmit market signals about the value of patent rights. It is the final market for goods and services that ultimately determines the commercial value of patent rights. Therefore, it is only when the products which embody patents are commercialized and sold to final consumers that economic value is established. This insight allows us to eliminate consideration of both litigation and deterrant value in searching for an optic on the market for IP. From this perspective, it is the “Practicing” value that is the most direct measurement of patent’s ultimate value.

However, this is not the specific type of value that we are most interested in observing. Remember that the need described here is for visibility on the market prices for IP. This is because all of our management tools and instruments rely on access to this particular kind of value. Thus we are most interested in the market-clearing price for patent rights. Only this particular definition of patent value can provide the necessary input to enable the adaptation of existing business skills and mechanisms to the ‘idea economy’.

Since market transactions occur between willing and knowledgeable parties, the market-clearing price for IP will also be influenced by the supplier. When the creator of IP is internal to the same organization that commercializes the final product, it is virtually impossible to observe “market” pricing. Therefore, it is only when patent rights are transacted between entities, as in the case of licensing, that we can accurately observe the sythesis of the influence of all of the actors in the IP supply chain.

Finally, in addition to the influence of the actors, market transactions also compound critical information about broader market forces and other external factors such as macroeconomic fluctuations, changes in regulation, the impact of key litigation, and many other influences that bear on the pricing of the transactions. This underlines the point that the most relevant and valuable IP valuation data are transaction prices between parties, or in other words, licensing transactions. The pricing of these market transactions alone reflect the true fusion all economic factors, and therefore, are the correct target of observation for measuring the market value of patents.

Conclusions

Four key conclusions come from this discussion of patent value:

1. Our ability to manage IP is limited by our inability to reliably measure its value.

2. Licensing value is the only type of patent value that can be measured consistently and reliably.

3. Only licensing transactions offer a valid measurement of the distinct economic value attributable to patent rights.

4. Only licensing transactions provide the opportunity to observe the “fair market value” of IP.

Based on this, the most viable solution is to gain access to observe a large number of licensing transactions as they occur and accumulate revenue over time. As noted above, the challenge is that these transactions are strictly confidential, and this is the reason that previous attempts to access this data have been unsuccessful. The need, therefore, is for a solution that provides a way to observe the market for IP transactions (or at least a statistically significant portion) which does not compromise the confidentiality of the transactions. Second, this data must be analyzed in such a way that the results can be accurately generalized to the larger space of patents. If you would like to learn more about this, my research on “Patent Citations and Licensing Value” examines the extent to which this kind of approach could produce meaningful metrics.

In a previous post, I argued that there are a lot of examples where aggregate market data are useful despite the fact that they often obscure a lot of pricing variability associated with heterogeneous products. In other words, market prices are averages of aggregated data that actually obscure a lot of pricing variation. Nevertheless, these data are extremely useful for management, in making investments, and a lot of other areas. My point is that aggregated IP/patent transaction data would be very useful to a lot of people and organizations. Here is just one interesting example of the value of market data from my own background…

In a former career, I worked as an economist analyzing global trade in fruits and vegetables mostly in support of World Bank and USAID projects to develop agriculture in emerging economies. I worked on several teams that built models which were used to focus hundreds of millions of dollars of investments in agricultural production, packing, transport, and marketing of fresh products throughout the world. Our clients had a very simple need. They needed to know what products to produce, how much, and where to sell them to make the most profit. Naturally what they can produce is constrained by their climate and location. But there were always several different products they could produce effectively and it was critical to know which would be the best investment. The data that are available to build market profitability models aggregate data in ways that obscure huge variations in what are actually very heterogeneous products and markets. For instance, for pricing and volume data we would often have a category like, “Grapes: Fresh”. Just think about the variety of grapes that are offered and the different venues, and formats where you buy them. “Grapes: Fresh” doesn’t really capture much variety. Yet, we were able to use this data very effectively to predict the volume of product that our clients could profitably deliver into every market around the world, in any given week. Any grape expert can tell you that the pricing data we were using obscured the very important reality that it matters a lot what kind of grapes you deliver, and in what format, for determining the price. However, this didn’t prevent us from using this data and combining it with that expert knowledge to be able to answer our client’s most important question.

The same is true for IP. Just because a product is not perfectly heterogeneous does not mean that aggregated/averaged market pricing information is not useful. In many cases, this data is essential in establishing fluid global markets. I am convinced that the same will be true for patents and other intellectual property. Once we can finally observe the market prices for large numbers of transactions (licenses and sales), this data will greatly reduce the “friction” associated with these transactions and a fluid global market in IP will finally emerge.