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?
Myth#3 – Value is equal to the cost of creating a data asset
The costs of developing a new technology and patenting the invention are high and manifold. R&D expenditures are significant costs within innovative companies, all additional for creating, protecting and enforcing intangible assets like patents are high as well. Interestingly literature shows, that in the field of patents the development costs of these intangible assets are uncorrelated with the future economic benefit.
Although there is to our best knowledge no empirical evidence for the same effect in the dataeconomy, we assert that similar effects will hold true for data assets. According to Sullivan and Wurzer, IP practitioners have observed, that the most valuable patents are those that can be exploited in multiple ways, and not those with the highest development costs.
As already discussed in the first part of this blog series, the effect and potential of multiple income streams is of special relevance in the commercialisation of data asset as well. Hence, we argue that it will not be the production cost of a data asset which determines its value, but it will be the exclusivity and the potential for creating various income streams which will make it valuable. There might be examples, that this potential can only be generated through high production costs, but in the average case we foresee no correlation between production costs and value of data assets.
Myth#4 – each Data Asset should have only one official value
Within commodity markets an item, like a barrel of Brent oil, has a market price which in the same time determines the value of it. This close correlation between price and value is due to the fact, that each commodity item can easily be replaced by another from another vendor.
As the previous discussion about value, worth, price and costs revealed, this does not hold true for highly diversified, intangible assets like data. A single data asset might have different values at the same time. And all of them are valid, because it depends on the perspective and who owns the data asset.
The value of data assets highly depend on the ability of the data owner to generate value out of it. The potential of an organisation for value extraction is tied to the organisational resources, capacities and contexts. Because each organisation is different, the value of a single data asset will vary within each organisation.
This will make the data valuation – which we will discuss in the following parts of this blog series – complicated. But on the other hand it reveals great value creation opportunities through the transfer of data assets from one organisation to another organisation with better framework conditions. This opens the way to a market for data assets. But it will require smoothly functioning intermediaries being able to spot and exploit these spreads in valuation.
All posts of this series: