Crowd-investing platform Rocket DAO has recently started testing its startup evaluation system. It means that the new principles of startup evaluation which the platform founders put on the basis of the project have produced initial results. Let’s talk about the way the approach of Rocket DAO differs from other approaches which are actively used today.
It’s obvious that startup evaluation is generally ordered by those who will use the knowledge about startup readiness and key metrics to their own advantages and who considers that all these evaluation costs will be refunded one day. These are investors and investment funds. As a rule, assessment criteria remain a secret for other investors, as the adequacy of assessment provides competitive advantages to the investor who is looking for new unicorns. In so doing, it turns out that investors don’t trust experts with their own approaches to startup evaluation. This is so because not the expert, but the investor actually risks the money.
That’s why an expert, or analyst, simply technologizes and algorithmizes a subjective approach an investor adheres to while evaluation projects. In practice, it turns out that analyst or expert make some basic screening of startups according to a predetermined by the investor set of parameters. After that, this investor examines these selected projects independently, then assigns meeting with the team, talks to them etc. After all, business-angel and venture investing is a high-risk activity, so the ones who invest their own money in startups are responsible for the final choice.
Therefore, one can consider an evaluation system a truly competitive one if in the end, it gives the most effective startup assessment results on these two parameters:
% of successful exits of startups. If the industry average is 4%, then any surplus of this parameter is more effective than mindless investments.
$XXX. The calculation is very simple. That 4 % of survived startups in their profitability should exceed costs of all survived and “dead” startups.
However, the profitability of the startup which has direct interactions with clients is not the only strategy of the return on investment. Let’s not forget also about the opportunity to sell startups to larger corporations, competitors; mergers and acquisitions practices; decisions made on the basis of insider information; strategies aimed at short-term growth and stock devaluation of the companies which acquire other startups. All those who are focused on this income-generation model develop their own approaches and set their own goals for startup evaluation, which, by the way, are not reported to anyone for obvious reasons.
Thus, experts don’t interact with each other, no expert knowledge about startups can eventually emerge. Those insights about startup success factors proven in practice are hidden from others, so they have no chance to become an asset of the community.
Value funds represent quite an interesting environment for knowledge generation about the ways of business value measuring (not of the startups). Usually, these funds are headed by experts who among other things primarily sell their expertise in startup valuation to contributors. Their work is quite interesting to analyze for the following reasons.
Firstly, they must always communicate with their contributors explaining their investment decisions (that’s why the invaluable knowledge about factors influencing the company value is contained in compilations of letters like, for example, a classic book of Warren Buffett). Secondly, value investing is long-term focused, therefore, we get an opportunity to test funds’ decisions.
So, both the publicity of the valuation and its parameters, as well as the opportunity to test these decisions over the long-term, do influence the growth of knowledge about a proper valuation procedure of a business judging by the example of value investors.
However, a substantial limitation in the use of the value investing experience in venture investing is that companies whose shares are held by value investors have gone through a series of filtration procedures while entering the stock market, have cash flow and a financial reporting. In venture investing the degree of uncertainty is way above, that is why one can’t use value investing techniques in venture investing procedures.
Crowd investing is indeed an environment which should provide transparency and knowledge accumulation about the valuation of investment projects. Since many investors participate in crowd-investing, there is a need to inform a huge amount of investors with the factors needed to make certain investment decisions. It’s achieved, paradoxically, by the centralization of startup valuation.
All services where crowd investing is usually organized turn out to be a kind of rating tables with a centralized and often non-transparent assessment system. They win the trust of investors when tokens of top-rated startups enter cryptocurrency market and face a great demand from the community as was initially forecasted. It takes place without any transparent financial reporting and real cash flow of these startups. So, then it becomes clear that non-transparent centralized startup assessment platforms and solutions serve to the speculative purposes rather than to the investment ones.
Startup infrastructure implies incremental growth of its value and the resale of its share. It means that an investor, directly or indirectly, estimates startup value, while the founder of a startup working on the project orientates to the actions which will lead to the startup value growth (for investors) whether he/she actually wants it or not. There are certain parameters on a fund market which allow investors to understand what the financial situation of a business actually is. Since a startup doesn’t have a transparent and public financial reporting in the early investing stages, it’s difficult to calculate the true startup value on the venture market. Therefore, investors use their own metrics. Well, the more investors, the more metrics consequently.
The startup founder improves indicators according to investor’s requirements.
And if suddenly this investor loses interest in a startup, it will require many efforts to draw the attention of another one, as, obviously, he/she will have his/her own approach to startup valuation.
Therefore, established stock markets with direct connections between operative companies reports and any approaches to value assessment are considered to be beneficial to their participants.
The problem of the venture startup valuation is not only in the fact that the valuation metrics developed for the companies which have conducted IPOs are not suitable for startups. But also in the fact that startups must be evaluated by other proxy indicators. The problem is that venture investors have their own, implicit and unpublic approaches for startup valuation. That’s why it becomes so difficult for startup founders to create a strategy for the growth of their business value.
What to do in that case? How can one solve the problem of the honest investment startup valuation for a big number of investors with a relatively small average cheque size?
If many people become investors today, then a lot of people must assess startups.
We are convinced, that the decentralization is the future. But we are also convinced, that instruments for turning isolated individuals into an organized group are needed for the effective decentralization as well. In our view, it’s possible only by turning a crowd into the community. And so, only three specialized communities will participate in the venture process, such as the investment community, the startup community and the expert community. The last one should define the perspectivity of startups following the principles of transparency, impartiality, and objectivity.
Therefore, in Rocket DAO we initially set a task to create a service for building, functioning and developing of these three communities — of investors, startups, and experts.
We understand that the community of experts is, in general, much more effective, stable and resultative, than each of its members individually. Certainly, Rocket DAO team is the main initiator of the creation and the work of community from the very beginning, but very soon the community itself will take all core management functions on its own.
The main shortcoming of the existing evaluation practice lies within the fact that both investors and startups are trying to turn solo. Startups do their best to maximize their value while investors underestimate projects in order to get a better deal. In this case, experts will become a kind of independent actors all together united by historically powerful value — the pursuit of the truth. In our situation, it concerns solution of the startup success riddle. Experts will not adjust parameters letting the increase or decrease of the actual startup value serving the interests of startup teams or investors but rather will provide both parties with independent reviews.
This approach will point out more perspective startups (what is a true value for venture investors) and help innovative project find out the areas for further effective growth and development.
So, an expert community should be independent of investors and startups. How can these goals be achieved? Who will pay for this expert community?
We strongly believe that startups are to pay for the expert reviews, as this is will be their most valuable self-investment for future fundraising campaigns, these sums will substitute multiply exceeding costs spent on marketing, promotion, investors attracting to the project.
But well, if experts are paid for their expertise, how can one validate the independence of the assessment? This is the key factor of the investors’ trust.
Our complex solution will solve this controversy through:
decentralization of the evaluation — different experts will perform different tasks: some of them will develop methodologists, others actually evaluate projects, the third group will control the quality of the evaluation results;
specialization in one of the evaluation parameters and consequently assessment of a project on one parameter only: team, product, business model, market, technology, legal, financial model, risks, resources and assets, PR and promotion;
strict algorithmization and standardization of the evaluation operations so that expert would always follow predetermined transparent and unambiguous steps;
expert ratings dependent on the quality of evaluation;
time limits set for the evaluation procedure.
Transparency of the evaluation process will be guaranteed by our platform, community regulations and methodologies of startups evaluation will be the primary responsibility of the expert community.
In order to constantly increase the quality of the evaluation procedures and let expert focus on the evaluation methodologies only we divided all experts into two major groups.
The first one will be responsible for methodologies development, while others will assess projects using community-approved methodologies. If some of the experts want to prove others that he/she is better than the rest of the experts, then he/she may simply write a new evaluation methodology and to present it to the community. But first, he/she will have to evaluate at least 10 projects using an existing methodology in order to specify all nuances from the inside.
The author of the methodology will receive commissions each time his/her methodology is used. So an expert will not only obtain community respect and test his/her own hypotheses concerning startups success factors but will also monetize his/her knowledge developing new methodologies.
Rocket DAO experts have already developed 14 evaluation methodologies for 10 parameters, 10 of these methodologies all together constitute the first set of requirements to startups on different investment rounds.
Summing up, we are striving to create the first ever decentralized public startup evaluation system, the one which will be effectively used by all members of the investing crowd.
If you feel like you could contribute to the development of the community, if you are able to develop a new methodology, then welcome to Rocket DAO Expert.
Author: Andrew Miroshnichenko
Translated by: Alena Palchenko
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