The Economic Value of Decentralized Identity — Part 1
The theory of the “meta-platform” network effects and IT power-plays
[ Note: this is a version edited down from a longer whitepaper titled “Decentralized Identity as a Meta-platform: How Cooperation Beats Aggregation,” published by the Rebooting the Web of Trust biannual conference, available here in its canonical form. It was written collaboratively by Michael Shea, Samuel M. Smith Ph.D., Carsten Stöcker Ph.D., with editing and contributions from Juan Caballero Ph.D. and Matt G. Condon. ]
Series Abstract
For decades now, the consensus of high-level IT management, and perhaps even more consequentially, the consensus around how to value IT companies, has focused primarily on their market power and the defensibility of their niche in platforms and/or closed ecosystems. This collaborative paper, which grew out of a dialogue between some decentralized-identity thought leaders at #RWoT9 in Prague 2019, seeks to shift some of the economic building blocks and ideological assumptions undergirding this preponderance of faith in “centralized” business models.
Fundamental to this shift in thinking is the difference between a platform and a “meta-platform,” which, as the etymology would imply, exists behind, between, and beyond other platforms. For our purposes, we define this meta-platform functionally, as a platform that enables and fosters participant-controlled value transfer across and among conventional platforms and their participants, allowing each participant to choose freely between platforms [1]. We believe that in the coming decades, metaplatforms will drastically change the functioning, and valuation of platform-based business models.
Because traditional platforms are a type of network, a meta-platform enables a network-of-networks effects, and this difference is just as consequential. This cooperation among platforms may be advantageous in comparison to centralized power (non-cooperation) in some contexts, particularly where a new network scaling law for meta-platforms can be argued to apply directly [2][3]. An open, interoperable, portable, decentralized identity framework is a prime candidate for becoming such a meta-platform and for leveraging this aggregate network effect.
Significant momentum has been developing behind a universal decentralized identity system based on open standards, including the W3C-supported decentralized identifier (DID) and verifiable credential (VC) standards [4][5]. Associated industry groups supporting this open standard include the Decentralized Identity Foundation (DIF), the Sovrin Foundation, and the HyperLedger Foundation projects Indy, Aries, and Ursa.
The purpose of this article is to foster awareness of the economic potential of cooperation and the crucial role decentralized identity may play in unleashing new sources of value creation and transfer among cooperating platforms.
Introduction
We are all familiar with many of the existing software platforms that are used today: in a consumer context, we speak of Google for searching, Amazon for purchasing goods, and Facebook or Twitter for social media exchanges. In an enterprise/business context, the platforms are different: Salesforce for CRM, TradeLens for containerized shipping and logistics, and Amazon AWS for cloud-based IT services. In economics terminology, we could state generally that the progressive reduction in transactions costs that a platform offers its operators is what drives the growth of that platform. These transaction costs include triangulation, transfer, and trust. For example, these costs include those incurred in matching buyers to sellers and in facilitating interactions or executing payments. This progressively lower per-transaction overhead accrues not just profitability but also other forms of value to the platform itself via Metcalfe’s law of network effects. Buyers and sellers on a platform get a significant reduction in transaction costs as well, from their point of view. The platform owners typically levy a fee on each transaction, as well as gaining market-wide access to large amounts of transaction data.
To date, in order to maximize network-effect-driven value, the “platform game” has been defined by a “winner takes all” rule book. The solitary focus of the platforms has been to grow the network as large as possible as quickly as possible. In a “winner takes all” world, this is the only road to survival. And the winners are few and powerful, and typically highly centralized, so they are therefore readily able to exploit their participants. Oddly, as the world has become dominated by a few powerful centralized platforms, entire industries have grown suspicious of this value proposition, and hence trust has diminished in would-be platforms and maneuvers to become one.
We are no longer in a centralized world.
With a proper meta-platform counterbalancing these centralizing tendencies, a “winner takes all” approach is no longer the only, or even, perhaps, the most sustainable model for establishing platforms. This article examines one blockchain-enabled technology and market driver for decentralization: an identity meta-platform. It describes how identity can provide the connective pathways (in software terms, the “protocol”) that unlocks the potent force of data-flow decentralization and provides the foundation for the creation of a platform-of-platforms (what we will call a “meta-platform”) that provides its participants with a new level of control and portability. By making their participation portable to other platforms structured around the same protocol, these platforms empower the individual actor vis-a-vis the platform.
We will first discuss how the network scaling law for meta-platforms differs from the network scaling law traditionally seen on closed platforms today, and we will examine how the cooperating members of a decentralized identity meta-platform may out-compete traditional, centralized identity platforms (such as the federation regime known by its ubiquitous “login in with Google/Facebook” buttons, through which end-users access other services but, in the process, outsource control over their identity, data, metadata, and online relationships)[1]. Not only do macro-level advantages emerge for the cooperating platforms themselves, but it is also hard to overstate the micro-level impact that decentralization of identity infrastructure can have for the individual consumer, who grows increasingly hungry for ways to take back control.
We will outline how participant control means that participants may form customized or bespoke virtual platforms of their own choosing. These virtual platforms could aggregate and/or amplify their identity’s value across multiple platforms. Participant control better balances the interests of participants and platform operators. It provides a check on exploitation while increasing the value of the platform to both participants and operators due to increased attractiveness and cooperation [6][7]. Key points of this analysis at the participant/consumer level are outlined by this diagram:
Sidebar: The Cooperative Network of Networks Effect
A network “scaling law” describes how some properties of a network change as a function of the size of the network. In the case of platform networks, the relevant property is network value, and the size is measured by the number of participants. The most well-known network scaling law is Metcalfe’s Law [8], according to which the value of the network to a single participant is proportional to the total number of participants. If we let a represent the average proportionality constant and N the number of participants then we have the following expression for the average value of a network to a participant, v, that is,
v = a⋅N
Furthermore the total value of the network, V, is just the sum of the values from each of the N participants. This gives the following expression:
V = v⋅N = a⋅N⋅N = a⋅N²
Any property or trait of the network that scales by the square of the size of the network greatly amplifies even minor advantages accruing to relative size. This naturally creates a “race to scale” between competitors in any market that highly values such a network trait. For this reason, the software industry values “network effects” highly, often applying the term anywhere Metcalfe’s Law applies, even with major caveats, in calculations of valuation or market position. (For a discussion of the quantitative validation of this effect, See Smith, 2019[9]).
Metcalfe’s scaling law of cooperative networks
The exponential increase in value described by Metcalfe’s law poses the question: What happens if two competing networks cooperate so that the combined network has a larger N than either network on its own? To put it another way, can cooperation between two networks be as valuable as mergers or acquisitions between them?
Suppose that two networks of size N₁ and N₂ respectively were to combine by making their services interoperable (or ideally going further: cooperating and actively minimizing friction across the two networks). Individually, the N₁ network’s total value is,
V₁ = a⋅N₁²,
and the N₂ network’s total value is
V₂ = a⋅N₂².
After combining, the average value to a participant of either network N₁ or N₂ is due to the combined size of the new network, N₁+N₂. This becomes,
v₁ = v₂ = a⋅( N₁+N₂).
The total value of network N₁ becomes,
V₁ = a⋅N₁⋅( N₁+N₂) = a⋅N₁²+a⋅N₁⋅N₂.
Likewise the total value of network N₂ becomes,
V₂ = a⋅N₂⋅( N₁+N₂) = a⋅N₂²+a⋅N₁⋅N₂.
We can thus imagine network-based business contexts where, merely by cooperating, each of the two networks has increased its total value by
a⋅N₁⋅N₂.
This is a very valuable benefit of cooperation. The total value of the combined network is just the sum,
V = V₁ + V₂ = a⋅N₁²+2⋅a⋅N₁⋅N₂+a⋅N₂² = a⋅(N₁+N₂)²,
which is the same as one larger network of size (N₁+N₂). The two networks can be of any size relative to each other. Suppose for example that N₂ is twice the size of N₁ The following diagram shows graphically the increased value due to cooperation, at this level of abstraction:
The same analysis can be extended to multiple cooperating networks [10]. In the above example, the cooperative effect came from making the networks interoperable. This may (and traditionally does) pose a problem if both network’s products are competitive. We discuss in detail elsewhere the lifetime value of cooperation for competing network products[1], but in broad strokes we could say it is a function of relative network size and degree of market saturation.
Cooperation in the calculus of business strategy
Despite the cooperative increase in total value, there may still be an aversion to cooperation due to the competitive nature of the products or other countervailing tendencies such as culture or momentum. Economic “brute force” may still win out in many real-world contexts, where eliminating the risk of later antagonisms or conflicts or other benefits unrelated to network effects outweigh the costs and risks entailed by acquiring, eliminating, or predatorily subordinating a competitor.
But all other things being equal, cooperation might present most of the benefits of expansion with none of the costs or risks, when connecting two networks has more net gains than net losses. Most economics of cooperation and sustainable competition (including between nations and industries, not just corporations and markets) require an accounting for scale that is not reductive and unidirectional, but which includes incentives to stay small and disincentives (like bad public relations or regulatory consequences) to overambitious mergers. For instance, in a situation where each network’s governance and maintenance are optimally manageable and efficient at a given size, yet both accrue all the benefits of expanding just by freely networking their domains, the latter is a natural choice.
This “free” (and low-friction) value transfer across networks within the same context is what is normally considered when using the term ‘cooperation’. By ‘context’ we mean similar types of products and services. We call ‘intra-contextual’ this cooperation that results in intra-contextual value transfer between networks. Our goal should be the nurturing of these kinds of contexts, where data flow and interoperability can be maximized while still preserving the necessary privacy and rights of all players.
Networks that provide different, non-interoperable products and services create what we call trans-contextual network value transfer. This trans-contextual value transfer has the potential to remove barriers to cooperation among perceived competitors. One might well pose the question, is trans-contextual value transfer even possible? And if so, to what extent can that value transfer be called “free”? Emphasizing this categorical distinction (intra- vs inter-contextual) and accounting wholistically for the costs of overcoming non-interoperability in strategic planning might make a pivot towards more cooperative tactics more feasible in the short-term.
In the next installment in the series, we will zoom in to make this theory of “value transfers” occurring between contexts and context-specific products more concrete, focusing a further analysis at the micro-economic level by considering the benefits and costs for the individual participating business. Afterwards, we will devote the last installment in the series to a series of potential use-cases and industry-specific analyses before concluding.
Stay sphered by joining Spherity’s Newsletter list and following us on Linkedin and Twitter.
