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The launch of our new patent pricing tool for Chinese e-commerce giant Alibaba is generating a lot of media interest. It is the first commercial service to be supported by our new technology platform, and we think it represents an important milestone in making IP valuation scalable and affordable. Here’s why.
Among the many discussions about intellectual property valuation I’ve had over the years, one from 2014 has always stuck in my mind. During a session with the Malaysian IP Office, the question of valuation report pricing came up. At which point, MyIPO said: “IP valuation will never really take off until it costs the same amount as valuing a house.”
As anyone who has visited www.inngot.com will readily deduce, our view is that MyIPO’s argument has a lot going for it. Whilst IP valuation is not a “one size fits all” activity, it can be standardised where the assets in question can be identified with precision and the transactional context is well understood.
The Alibaba example, where all the patents under review are being disposed of in liquidation, provides a good example to explain why the house valuation parallel is more appropriate – and achievable – than it may first appear.
Setting a data-driven price
Like most other tangible assets (such as used cars), houses are generally valued on a combination of two elements. The first is the intrinsic properties of the asset. For an immovable like a house, its size and location provide the most important baseline; for a movable like a car, its make, model, specification do the same.
The second is the market appetite to buy and sell similar assets. Here, data can be gathered from (reasonably) transparent markets to draw a price comparison, which can then be adjusted using the particular attributes of the house or car in question.
This, in a nutshell, is how the engine developed for Alibaba works. The intrinsic properties of the patents and utility models that are available for sale are determined and analysed, and the field of technology to which the assets relate is used as the transactional baseline. Both are mapped against the profile of previous sold and unsold patent lots from data gathered across multiple Chinese auction platforms to work out a minimum amount that the IP rights should fetch, based on factual precedent.
In the end, of course, the market decides what each auction lot is worth (and whether to bid for it). With the benefit of a highly affordable valuation report, however, sellers can make a more informed decision about where to pitch their reserve pricing. That way, they don’t risk selling at under-value if bidding happens to be less competitive than normal on the day.
Dealing with difference
I recognise the obvious objection that no two patents are the same (this is, by definition, true). However, it’s also the case that no two houses or cars are exactly alike (certainly not once they’ve been around for a while; a 10,000 mile car and a 100,000 mile car are rather different ownership propositions). Nevertheless, there are usually enough reference points to make an informed estimate of what price they will fetch at a given point in time, were they to be put on the market. The more sales that can be tapped into, the more accurate the engine becomes.
Equally, there will be external factors that influence what a patent is worth, such as the revenues and profits associated with its use and its potential for enforcement. But external influence is not a complication unique to IP assets.
When a school gets an ‘outstanding’ report, all the houses in its catchment area get an uplift. When a car manufacturer gets embroiled in an emissions scandal, all affected vehicles wearing its badge take a hit. Some of these factors are predictable, while others are not, but it is fair to say that these external factors are a lot less influential where the assets are sold in liquidation.
Dealing with transparency – or the lack of it
Unusually, our Alibaba service has been able to tap into relatively transparent markets for IP rights. This is normal for houses, but not for IP. The absence of transparent markets for intangible assets is the most frequently-quoted explanation for the lack of confidence in IP value in financial transactions. Increasingly, this looks like an excuse, not a reason.
To explain why, it’s worth taking a moment to consider why IP markets are not (normally) transparent. Intangible assets like IP deliver value in particular commercial contexts. They are often so integral to a firm’s activities that most companies will not want to sell them (because they underpin market differentiation and create barriers to entry and freedom to operate). It’s a very big ask to establish an efficient sale and purchase market when supply of the best assets is always likely to be ‘throttled’ in this way.
This is precisely the reason why IP-based finance is so important: it enables companies to leverage the value of the assets they own without having to sell them. It also enables lenders to harness assets that are core to business value, not peripheral. And even when transparent reference points like Alibaba sales are unavailable (because we are dealing with ‘going’ concerns rather than ‘gone’ ones), there is plenty of evidence that intangible value exists, and that other people are prepared to pay for it.
Licensing data is one important source, but IP value is also evident from other transactions – in good times and in bad. The obvious example in good times is tech company M&A pricing, which is principally driven by the value associated with scalable intangibles and the people that create them. Logic dictates it has to be – these companies simply don’t own anything else.
We also see that in less good times, when firms get rescued, re-structures are not driven by their factory buildings or machinery (which are generally owned by someone else anyway), but by intangibles like their brands, databases and know-how.
Changing times
In the past, IP and intangibles have tended to be poor relations to tangibles (‘Cinderella’ assets). The prices achieved by the best patent lots offered via Alibaba show that liquidators ignore them at their peril.
With proper application of data science, these points of comparison provide insights that can be applied – carefully and responsibly – to prospective transactions, in order to leverage the assets that really drive future business value. IP-based finance is, for us, the biggest opportunity; however, since lending is generally done on small margins, there is an inescapable need for valuation to be low if this form of finance is to work affordably at scale.
Coupled with everything we can learn from ‘pure’ IP sales under the worst possible circumstances (namely liquidation), these market comparators provide the insights our new platform is bringing to bear – for about the same price as valuing a house.
