In 2009 Patrick Sullivan and Alexander Wurzer published a comprehensive list of 10 common myths about the value and the valuation of intangibles in the IAM magazine (if you do not have access to the IAM magazine’s paid content, read Joff Wild’s blog piece about this article). In this blog series we investigate what we can learn for data valuation from this demystification of the value of intangibles. In the first post of the series we started to re-think the myths about price and value of data assets. In the second post we demystified the differences between costs and value of data assets. After these basic thoughts, we start to investigate the concept of valuation. Valuation is the art of determining the value of an intangible asset like a data asset. For the value of tangible assets, the balance sheet and the fair market values are very good information sources. But does this hold true for data assets as well?
In 2009 Patrick Sullivan and Alexander Wurzer published a comprehensive list of 10 common myths about the value and the valuation of intangibles in the IAM magazine (if you do not have access to the IAM magazine’s paid content, read Joff Wild’s blog piece about this article). In this blog series we investigate what we can learn for data valuation from this demystification of the value of intangibles. In the first post of the series we started to re-think the the myths about price and value of data assets. It became evident that within the dataeconomy the price and worth of data collections or data items can be very different. In the next step we now demystify the differences between costs and value – is there any correlation between production costs and commercial value of data assets? And what does this mean for data valuation?
In 2009 Patrick Sullivan and Alexander Wurzer published a comprehensive list of 10 common myths about the value and the valuation of intangibles in the IAM magazine (if you do not have access to the IAM magazine’s paid content, read Joff Wild’s blog piece about this article). The authors have a strong background in the patent commercialisation domain. For sure, data collections are different from patent portfolios. But both are (the ultimate?) intangible assets, in both domains valuation is a unsolved challenge. So what can we learn for data valuation from this demystification of the value of intangibles? In this blog piece we start with the first two myths – which help to understand the differences between worth and price of a data item or collection in a data economy.
IPR, and especially patents, play an important role in the high-tech economy. While their original purpose is incentivizing investments into innovations, they are considered by the companies more and more as important intangible assets. These assets are used strategically, in example by blocking competitors to follow specific technological pathways. Besides that, IPR assets gain more momentum as literals in IP finance. In parallel to the increasing economic importance of IPRs, a whole ecosystem of IPR interest groups (lobbyists) has been emerged. By analysing all the IPR interest groups we have already tracked in the IP Industry Base, we were surprised by the diversity of interests they serve and started to segment this field of lobbyists. The result is this (incomplete) tracke of IPR interest groups.
We experience the rise of the knowledge economy and an emerging importance of big data technologies for value creation. Companies start to understand the economic value of creating proper data collections feeding their own products and processes with a unique competitive edge. They realize that the compilation of proprietary, large-scale data collections will become very important investment projects in future. They will learn to consider data collections as a new kind of asset, enabling them to extract new value through new and better products and services.
With the IP Industry Base we are dedicated to create more transparency on the market for IP-related service, like patent attorneys, IP consulting firms or even NPEs. In 2015 we improved the IP Industry Base through more functionality, more data and higher quality of data. Th IP Industry Base changed a lot in the last 12 months. Follow our journey through the year 2015 in this blog post.
Have you ever wondered how much renewable energy sources are already installed in your region? And how much it is compared to the still existing nuclear and fossil power plants?
If yes, our ELMEX tool will give you an answer. The National Regulatory Authority (“Bundesnetzagentur”) does regularly publish a list of all running power plants in Germany, including the information on capacity and dominant energy source. We took this nice open data and fed our book of competitors framework with it. As a result we have now fact sheets for each power plant in Germany in our new system, which we call ELMEX (ELectricity Markets and EXchange Database). The figure shows the fact sheet look for a gas-fired plant in Leipzig. Continue reading How much renewable energy capacity is already installed in your region?
Patent information is a wealth of open data. It is used for a lot of applications in innovation intelligence, like patent landscaping or expert extraction. We wanted to add a new competitive intelligence application into this list.
Each patent does not only disclose the technology itselfs, but also who the inventor (a natural person) and the applicant (usually a company behind the inventor) is. (An example EPO record for a patent is here). The patent does also disclose which patent attorney has worked on it. Connecting these dots allows to mine customer relationships between the technology companies (which act as applicants) and the patent law firms (which act as agent).
Launched in June 2015 ORoPO claims to be a global database of patent owners verified by companies committed to openness and transparency.
We need more smart data in the field of technology markets. Therefore we appreciate initiatives like ORoPO very much. As soon as open data on patent ownership is available, we will try to integrate it into our IP Industry Base. Follow here our regular updates on ORoPO.
Recently we stumbled again across the GeoTemCo project from our esteemed colleagues at the image and signal processing department at the University of Leipzig. GeoTempCo is described as a web-based application which can easily be utilized to visualize data under geospatial, temporal and topical aspects. The main use case of GeoTemCo is the comparative analysis of several datasets. The tool is open-source and easy to set-up, hence we decided to play a bit with our data about the IP service industry.