Value capture is a topic that always seemed a bit overlooked in business modelling. Traditionally, as Peter Thiel frequently points out, there’s little correlation between value creation and value capture (e.g. one may generate tons of revenue without really profiting from it). Some industries have even established dynamics that clearly separate value creation from capture: think of the film industry, with production companies doing all the creative and operation work on one side, while, on the other hand, distributors and exhibitors take 80–90% of the share of profit, at the end of a movie’s life cycle.
In cryptoland, value capture is even murkier. A post by the Dharma team recently put forth (and got me thinking about) the question whether “any current token designs will reliably accrue value even if their parent products are successful”. There’s a good degree of consensus around the overvaluation of assets in the market; a lot of decent discussions around valuation methodologies aiming to frame the madness; but not much rational talk about the root issue:
do cryptoassets really capture the value of something, at all?
1. What is value?
Value is created through work. Work can be mechanical, creative, or anything in between. In “The Origin of Wealth”, Eric Beinhocker scientifically defines the creation of economic value in three key criteria: work must be (thermodynamically) irreversible; reduce local entropy (within its ecosystem) while increasing global entropy; and produce artefacts or actions that are fit for human purposes (note how blockchain-based work fits perfectly here).
1.1. What is value capture?
P/E rations of top ~100 global internet stocks (in 2014). Wondering about the lack of uniformity? They all capture value differently!
Extending the definition above, the purpose of a business can be seen as that of creating value (through work), selling or trading it to customers, and capturing some of that value as profit.
Value capture is the link between profits and revenue; essentially the “glue” of P/E ratios.
1.2. Approaches towards value capture
data from “Measuring the Moat” (2013), by CreditSuisse.
HBR has a great article by Professor Stefan Michel called Capture More Value. It lays down a framework for innovating of value capture in 15 distinct forms, from changing the price-setting mechanism (e.g. fixed price vs. auctioning) to changing the part of the product/experience on which the price tag is hung on (e.g. coffee packets vs. Nespresso capsules)
Generic patterns can also be extracted by comparing the asset turnover vs. cash flow return on investment (CFROI) of a broad enough range of stocks. Visualisation makes it clear that some businesses capture value through massive scale and thin margins (production advantage), while others rely on large margins (high pricing power towards consumers) and generate return with lower asset turnover.
1.3 Profit pools (value-capture heterogeneity)
Visualising profit pools: the evolution of value capture in the healthcare industry, throughout a decade (source).
A projection exercise that’s relevant to cryptoland is that of dissecting industries in “profit pools” — i.e. to compare the profitability and share of industry revenue across given industry sectors, seeking for those that are more effective in value capture.
In the film industry, for example, as it hypothetically starts to decentralise itself into tokenised services, this would mean breaking down a movie’s journey from producer, to distributor, to festivals, to theaters, to subscription catalogues, to home-video, to cable TV, to advertising-VoD… and tracking who gets the larger pieces of the cake.
It can be interesting to take the question further, by conceiving profit pools within sectors: like splitting advertising-VOD down into transcoding, storage, content management, distribution, permission, and billing services, for example, thus estimating the value accretion potentials of video-related tokens aimed towards specific parts of this pipeline (let’s leave that to another post).
2. On the value of financial assets
An asset’s value is the present value of its (expected) future cash flows.
The value of a traditional security-like financial asset is straightforward to model, and usually translates into the famed discounted cash flow equation. Its subset of variables is widely discussed in the financial literature, and, although most of them turn out to be hard to predict in practice, empirical data surfaces enough correlations for investors and analysts to rejoice in their models.
In the case of security tokens, the model may still apply. In the case of everything else in cryptoland, it doesn’t.
3. What do token valuation frameworks say about value accretion?
There’s still few - albeit exceptionally smart - people studying valuation models for utility tokens. A handy summary follows (note that the exercise of valuation encompasses the matter of value capture, but is broader in nature):
Brendan Bernstein’s “Making Sense of Crypto Asset Valuation Insanity”: the quantity theory of money as a framework for reasoning about crypto.
The overarching but tacit idea here is that these assets function as an exclusive form of payment in exchange for a network’s underlying scarce resource. However, it might not be appropriate to make such conservative assumption, specially when it comes to utility tokens.
In face of the “rise of Stablecoins” as more efficient means of payment, cross-chain interoperability efforts, and even proposals for stuff like paying for gas on Ethereum with ERC20s, it seems unclear that any cryptoasset will be able to fence-off alternative currencies as means of payments within their networks. Instead, we should probably be looking at which tokens will people (or machines) choose to hold or to spend.
4. What does the crypto market say about value accretion mechanisms?
Very likely, it doesn’t give a 💩 yet. In the stage we’re at, while speculation-to-utility ratios still lurk above 90% for most tokens, prices on secondary markets are dictated by the attribution of value to a loose range of aspects, not directly related to value capture (since there’s little value being captured outside of Bitcoin, Ethereum and a handful of others, at all).
Look at #TRX. It’s an aberration. But it seems to have higher-than-average correlations between reddit active users (or new comments) and token price. Besides, no other publicly measured metric correlates to price as strongly as these (see Github commits x price, on the right, below). Some other studies suggest deep-rooted correlations between cryptocurrencies’ prices and social metrics. That says a lot about what do some portions of the market currently attribute value to. A layman is not to blame for trying to find his own proxies to foresee “network effects”.
5. How are utility tokens claiming to accrue value?
“Tokens which are uniquely required to incentivize or disincentivize behavior in order to provide a service accrue value relative to that services utility”.
The definition above was put forth by Luke Duncan. It’s palatable and useful, even if very theoretical. Three key points: “uniquely” (is the token unique for incentivising the underlying services of the network? How much competition is there for the same ‘mining power’ being tapped?); “incentivise or disincentivise” (how accurately/fully does it capture the value of underlying behaviours?), “utility” (how much real world demand can there be for such underlying services?). Let’s have a closer look on the second one.
There’s a handful of attempts in classifying tokens according to their origin / genealogy; others in trying to stack them according to their legal status, but few that aim to dissect and categorise the value accretion mechanism behind each asset.
’s New Models for Utility Tokens is a piece that stands out, here. We incorporate the ideas proposed and present an extended visualisation below: