Introducing Token-Ranked Lists (TRLs)

How to curate service value on a decentralized platform

With the advent of blockchain and tokenization, professional services industry consumers can now reap the benefits of both fragmentation and consolidation at the same time.

How? By creating decentralized networks where all participants are able to compete and no single participant is managing the network. In decentralized networks, both consumers and providers can thrive: consumers have better access to services and more power over quality curation, while providers gain direct access and benefit from a fairer and transparent competition.

A token-ranked list functions to curate value-based relationships with service providers. The design of a token-ranked list allows consumers to curate a list of service providers based on relative performance over a period of time. Under the TRL model, consumers become curators.

The list would have a limited number of slots for Service Providers. Each slot is filled by a service provider representing an individual, a team, or a company, and capable of generating relevant services. Every period of time, new service providers get the opportunity to join the list.

The Token-Ranked List (TRL): How It Works

The following parameters will be referred to later and detailed as we progress on the TRL model.

  • Slots. Places to be occupied by service providers on the platform.
  • Service Provider. Participant providing services to the consumer on the platform. A Service Provider can be an individual, a team, or a company.
  • Consumer. User benefiting from and curating the platform.
  • Period. Specific time period to be defined.
  • Minimum Amount. Minimum amount of tokens to send to access the platform.
  • Cap. Maximum amount of tokens a Consumer is allowed to send to access the platform (Cap — Minimum Amount >0).
  • Basic Comp %. Percentage of tokens distributed as base compensation to Service Providers.
  • Bottom X%. Percentage of Service Providers who are removed from the list every period.

Let’s assume we have 200 Service Providers filling out the 200 Slots. The TRL works as follow:

  • Each Consumer sends a number of tokens into a Bounty Pool at the beginning of a pre-defined Period of time. There will be a Minimum Amount, but Consumers can send as many tokens as they want beyond this threshold, up to a certain Cap. The idea behind sending more than the Minimum would be to attract top Service Providers and incentivize them to provide more value add services.
  • Funding the Bounty Pool provides Consumers full access to the TRL platform. Consumers can look for Service Providers’ profiles, use their services, etc.
  • A Basic Comp % is sent directly and equally to all Service Providers as base compensation.
  • At the end of the Period, Consumers would have to vote on the performance of the Service Providers they interacted with. Consumers’ votes will be weighed based on the number of tokens they sent to the Bounty Pool at the beginning of the Period as well as other factors to be determined.
  • Service Providers will get their bonus from the Bounty Pool based on the aggregate votes they received for the Period.
  • The platform would also rank Service Providers in a list based on total number of votes received, historical performance, tenure on platform, level of engagement with Consumers, and level of collaboration with other Service Providers, among other factors. This allows to create a reputation system for Service Providers over time.
  • At the end of every period, the Bottom X% of Service Providers lose their Slots (if it is 10%, it will be 20 Service Providers in our example), and a TCR-based competition is launched to fill out the vacant slots. This provides a way to rule out bad performers and give newcomers a chance to join the platform.

How to Get on the Platform

A modified version of the TCR is used to manage onboarding on the platform for both sides, Service Providers and Consumers.

Service Providers have to apply to join the Supply Side TCR. The curators are the Consumers. The same TCR dynamics are in effect when a Service Provider applies to join. Once accepted, the Service Provider becomes part of the TRL. At the end of every Period, the Bottom X% (x is to be defined) of Service Providers lose their Slots. Those Service Providers are removed from the TCR automatically and have to reapply.

Consumers have to apply to join the Demand Side TCR. The curators are the other Consumers and experts. The same TCR dynamics apply here. This is more of a whitelisting measure. Being part of the Demand Side TCR does not give the Consumer access to the platform. Access is granted once the Consumer sends tokens to the Bounty Pool.

Case Study: How TRLs Address Europe’s New Research Legislation

One of the relevant applications for this model is equity research. Until 2018, research pricing was bundled with sales and trading commissions, which resulted in many issues: sales and trading commissions were inflated to include the price of research, and many fund managers couldn’t even determine the value of the research they were receiving. Moreover, firms that advised on equity issuance and asset management also claimed to provide “unbiased” investment advice on prices. This has always created conflicts of interest.

In 2018, MiFID II came into effect in Europe to address these pricing, transparency, and incentive issues. The new legislative framework required banks to price research separately. This means that now fund managers are sensitive to research value for money. It also means that research is not free anymore and that funds have to subscribe to many research providers — not a great user experience. As a result, many banks started slashing their research budgets while many independent research companies started to emerge.

A TRL-based platform would address many of the MiFID II requirements by providing fund managers a single point of access to a pool of high quality research providers and giving them the power to curate and compensate those providers based on their performance. It would also empower independent research providers by creating a marketplace where they can compete and receive fair compensation. All of this would be done in a transparent and compliant manner.

Let’s think through the following scenario:

  • Slots = 200
  • Service Providers = Equity Research Providers (a research provider can be an independent equity research analyst, a team of analysts, or a research company)
  • Consumers = Fund Managers (there are other consumers, obviously, but let’s simplify it for the sake of the example)
  • Period = Quarter

Fund managers would send a number of tokens to a Bounty Pool to access the platform for the quarter: Minimum Amount < Tokens Sent < Cap. They would be able to interact with any research provider, ask for and consume research, share ideas, get access to management, etc. At the end of the quarter, the fund managers would vote for each research provider they respectively interacted and worked with. Research providers are compensated from the pool of tokens sent initially by all fund managers based on the aggregate votes they respectively receive for the quarter. The platform also takes into account other objective information such as level of engagement on the platform, level of collaboration, etc., and outputs a ranked list of research providers allowing analysts to build their reputation.

General TRL Benefits

Quality Curation

Consumers have intrinsic interest in curating quality on the platform since they are the ones using the service. If they do a bad job, they will receive bad service. However, making sure all incentives are aligned remains to be validated.

Value-Based Compensation

In the TRL model, Service Providers are not compensated on the volume they produce. They are also not compensated on a case by case basis. The performance assessment and compensation is based on value derived out of the relationship with the Service Provider over a period of time.

Competitive Dynamics

Large Consumers would send a high amount of tokens to attract top performing Service Providers. On the other hand, new Service Providers who are not well established yet would target the smaller Consumers to build credibility. This creates a competitive dynamic on the platform. Constraints remain to be defined to make sure incentives are sound.

Flexibility in Working with Providers

Instead of locking themselves in with a handful of Service Providers, Consumers can distribute their budget among a wider pool of Service Providers by paying on-demand through voting.

Transparency, Transparency, Transparency

The votes are transparent and Service Providers as well as Consumers can see them over time. This is important for two reasons. First, all participants on the platform can see the budget per Consumer and the revenues each Service Provider is earning. Second, a transparent voting process allows participants to track Service Providers’ overall progress and performance over time.

IP Protection

Content created by Service Providers is protected to avoid free-riding problems in two ways. An ERC-721 token is assigned to each piece of content created, allowing platform participants to identify the owner. Also, content is only shared with the participants of the platform, and there is no way to pirate it off of the platform.

Going Forward

The Helena team is still in the process of detailing the parameters of the TRL model and speccing out the token mechanics. Helena is also running pilots to test the platform MVP. If you are an institution in need of research and would like to be part of the pilot, please sign up as an institutional research consumer. If being an entrepreneurial blockchain research analyst excites you, please sign up as a research analyst.

Disclaimer: The views expressed by the author above do not necessarily represent the views of Consensys AG. ConsenSys is a decentralized community with ConsenSys Media being a platform for members to freely express their diverse ideas and perspectives. To learn more about ConsenSys and Ethereum, please visit our website.