Valuing start-ups is one of the most complex exercises a valuer is likely to face. The main reason for this is that start-ups are innovative companies for which limited financial information is available. The economic model of a start-up is usually not yet stable, and the start-up will have to get through a large number of stages before it reaches maturity. In this context, it is very difficult for a valuer to identify listed assets or comparable transactions, much less provide credible forecasts of cash flows.
Despite these challenges, investors can and routinely do estimate the value of start-ups. At the beginning of its existence, a start-up’s financing essentially depends on the initial capital infusion and the assumptions underlying it. This implies having a value for the start-up; without such a value assigned to the first round, investors could not participate in future rounds of financing.
This context encourages the rise of valuation errors, with valuers unable to make use of their usual points of reference or easily implement classic financial methods. Numerous practitioners consider the valuation of start-ups as an artificial exercise, one that depends on a set of market conventions that in turn rest on assumptions that almost all involved recognize as hopelessly unrealistic. In many if not most cases, investors receive a specified fraction of a start-up’s equity in exchange for financing its capital expenditure over the next few months. But as a general rule, valuation practices for start-ups vary wildly, and there is nothing approaching a consensus among experts on best practice.
The aim of this article is to show that, despite these difficulties, the value of the shares in a start-up can be estimated by applying the standard financial framework in a good number of cases. It is simply necessary to keep in mind and adhere to a certain number of fundamental principles and adapt the valuation methodology to the context. We present in this article seven errors or practices to be avoided that are likely to distort the valuation of a start-up’s equity. Our aim is to provide a framework for valuing start-ups that makes it possible to understand different situations and value them at different levels of maturity.
First Deadly Sin: Dismissing the First Principles of Finance
When valuing start-ups, the use of financial methods is complicated by the unique nature of the companies and the significant risks faced by investors. Nevertheless, this does not mean that financial principles do not apply and that only conventions should be considered. It is worth remembering that the fundamental value of any asset is equal to the present value of its expected future cash flows discounted at the risk-adjusted rate. Using this approach, only the systematic risk should be included in the discount rate; the specific risk should be included in the company’s expected cash flows.
In concrete terms, this means determining a start-up’s future cash flows and their likelihood of occurrence, then discounting them at a rate that is consistent with the teachings of financial theory. In other words, the valuer must always bear in mind that the equity value should be justified by some process that involves the discounting future cash flows. If it doesn’t, the valuer would risk overestimating the value of the start-up and contributing to the creation of a financial bubble.
Example: In February 1999, two financial analysts of Credit Suisse First Boston explained that financial principles have to be applied to value internet companies. In the executive summary of their report, they wrote: “if Internet companies have higher valuation than their offline counterparts, the market must believe that they have higher cash flows” (Desk notes, Cash Flow.com – Cash Economics in the New Economy, February 26, 1999). Considering the examples of companies like Dell Computer, Amazon, and Yahoo!, these financial analysts considered that
there were solid fundamentals underpinning the high valuations in the internet sector at the end of the nineties.
One might object that application of financial principles does not protect against mistakes when valuing start-ups. And, indeed, shortly after the publication of this financial analysts’ report, the New Economy bubble actually burst. However, a high proportion of valuation errors observed at the end of the nineties for internet companies can potentially be explained by the herd-like behavior of many investors who applied basic multiples and did not make sufficient efforts to apply standard financial principles or reconcile equity values with future discounted cash flows. Whilst it is true that financial reasoning will certainly not prevent investors from exaggerating start-ups’ profitability, it will provide them with a sound and transparent framework for grounding their reasoning and assumptions.
Second Deadly Sin: Failure to Distinguish Risk from Uncertainty
Though start-ups share certain characteristics, they do not form a homogeneous group. Some are at an advanced stage of maturity and have good visibility over their development plan. By investing in start-ups of this type, investors bear some sort of risk, but it is measurable: as such, it is a true risk in the financial sense of the word.
Having made that determination, a valuer can use traditional financial methods to value the start-up because the future cash flows can be defined with a reasonable probability of occurrence. For other start-ups in early stages of development, it is impossible to say, for example, when they will win their first clients or what capital expenditure will be necessary for their development. In such cases, the risk borne by the investors is no longer (reasonably) measurable and therefore becomes an uncertainty—and traditional valuation principles can no longer be applied. A financial valuation would only be possible with extremely wide ranges of values–too wide in any case to make decisions.
Consequently, investors are likely to use market conventions to undertake transactions. They will aim to find an agreement making it possible to pursue the project thanks to capital injections from new investors, who will want to limit their risk—for example, by using hybrid financing like convertible bonds that also provide an option to benefit from favorable scenarios. The founders will accept dilution of their control to a certain extent in order to continue developing the project. Thus, the valuer must accept that start-ups do not form a homogeneous group and the valuation methodology applied to value a start-up must therefore be adapted based on its level of maturity.
Example: The distinction between an uncertain and a risky environment is illustrated by the following two cases of start-ups:
Airbnb. Airbnb provides a great illustration of a highly uncertain venture. It was characterized by uncertainty about demand, and about the adoption rate, the availability of the core resources, and other key variables. In addition, there was a clear regulatory risk. Renting air mattresses in the lounge of private flats in 2009 didn’t come across as a clearly winning idea. Paul Graham, iconic entrepreneur and founder of Y Combinator even stated (about Airbnb) “These people are actually doing this. What’s wrong with them?”. But after, he enrolled them in Y Combinator. Experts must remain humble! As the success of Airbnb clearly demonstrates, some projects are uncertain because it is impossible to perform an early assessment of the fundamentals of the business case. They create what amounts to an entirely new value proposition in a market that has yet to develop. This is almost always the case for disruptive innovations (not always technologies) that open new market territories. Early-round valuations in such cases (before Series B) are mostly based on the readiness of investors to see if an unusual—but interesting—idea takes off, and for such investors’ on a necessarily subjective assessment of what a fair share of the returns could be, if the idea proves successful. Such a
process is also directly affected by how much capital is available among early-stage VC investors to fund projects setting out on a promising—but, again, highly uncertain—journey.
Sensome. Sensome, by contrast, is a great example of a risky project, but with a quantifiable level of uncertainty. The company has developed remote monitoring technology that turns invasive vascular medical devices into connected healthcare devices. Many if not most projects in the health domain exhibit this type of risk/uncertainty profile. The market and value proposition are often clear from the beginning: curing a disease, providing a new tool for better or cheaper diagnosis, etc. In such cases, it is clearly possible to assess the number of patients, the economics of the disease, and the pain point that the venture addresses. The main components of risk lie in the development of the science and technology linked to the project, and, of course, regulation. And in such cases, valuation of the start-up can be performed using existing approaches.
Third Deadly Sin: Using Too High Discount Rates
Some professionals use extremely high discount rates—on the order of 30% to 40%—to discount a start-up’s future cash flows, particularly to bring the estimated cash flows, which are often very optimistic, to more reasonable levels. This approach, however, raises questions on both conceptual and technical levels. The use of such high rates effectively assumes that the risk follows a geometric progression, which is not necessarily the case. It ignores the discrete nature of certain risks, and the implicit assumption of the reinvestment of cash flows at the discount rate. Using a high discount rate also poses a problem from a theoretical standpoint. As already mentioned, only the non-diversifiable risk should be considered in the discount rate; specific risks should be dealt with in the cash flows. Finally, using a high discount rate comes down to considering that the cash flows have a lower chance of being generated.
With this in mind, it would be preferable to use a probabilistic approach and a discount rate consistent with the standard financial framework, which aims to reflect only the systematic risk of the venture (as illustrated in the example below). One advantage of this method is that by focusing on a variable like probability of success that can be readily understood, if not always measured with precision, it facilitates both input from and discussion by stakeholders in the venture. By contrast, use of a high discount rate would squash the value with no possibility of debate. Such a practice obscures the valuation process, essentially making it a black box that makes it impossible to see how the assumptions used affect the values.
Example: In the professional literature on start-up and venture capital valuations, early-stage discount rates as high as 50% or 70% are often cited. These high discount rates can be easily translated into a probability of success (or failure). For example, use of a 50% discount rate on a cash flow of 10 generated in perpetuity is equivalent to assuming a probability of success of 20% and discounting the cash flow at 10%:
10/50% = 10*20%/10% = 20.
Discounting this same perpetual cash flow at a rate of 70% comes down to considering a probability of success of 14.3% (10/70% = 10*14.3%/10% = 14.3).
Fourth Deadly Sin: Excessive Emphasis on Near-Term Cash Flows
When we value mature companies, the discounted future cash flows estimated by the management team tend to account for the lion’s share of the value. Besides representing a significant proportion of the total value of the company, these cash flows, which show the company’s short-term financial perspectives, also have the effect of increasing the credibility of the projected cash flows used to define the terminal value—that is, the value of the company after the management team’s forecast period. In the case of start-ups, however, the cash flows estimated by the management team should not merit, and are not generally accorded, the same status. Indeed, in a high number of cases, start-up projects do not progress as initially planned. But investors are well aware of this possibility and, for this reason, are often reluctant to use the discounted cash flow (DCF) method for start-ups.
Nevertheless, such investors will often ask for and use the estimated cash flows as a way to assess the credibility and expectations of the management team, and to ensure management’s fluency in the language of finance, a fundamental requirement for the negotiations on which future fundraising depends. Further, in a very high number of early-stage start-ups, investors base their investment decisions on the perceived quality of the management team as well as the startup’s technological edge.
The cash flow forecasts are only one way to give meaning to the project “story” that the management team aims to develop. While it is relatively easy to show high growth rates for a start-up, it is more difficult to explain in a convincing narrative how these growth rates will be achieved. In such a context, the cash flows estimated by the management team will be of limited importance to the valuer because most of the value will be generated over a longer period and captured by the terminal value.
Example: In its 10K report for the year 1997, Amazon explained to investors that it would continue to incur substantial operating losses for the foreseeable future and that the rate at which such losses would be incurred may increase significantly.
At the same time, the company presented the principles that would lead to value creation and explained that Amazon had to focus on the long term, to establish long-term relationships with its customers, to generate economies of scale (which meant continuing to grow), and to retain key employees. In 1997, the value of Amazon mainly depended on long-term cash flows that could emerge after the forecast horizon. Investors had to accept the reality that the near-term cash flows had a limited effect on the value of the company, which fundamentally depended on its capacity to reach long-term goals.
Fifth Deadly Sin: Neglect of the Terminal Value
The value of a start-up depends on its ability to achieve its longer-term objectives. For this reason, it is worth concentrating on the value generated beyond the cash flow forecast period, which financial analysts attempt to capture in the concept of terminal value. But estimating terminal values is even more challenging in the case of start-ups. Whereas the terminal values for mature companies generally reflect a straightforward extrapolation of past financial performance, in the case of start-ups, the terminal value is often the starting point of the valuation, representing 100% or more of a startup’s enterprise value (thanks to the negative cash flows in the first years arising from the capital expenditure necessary for development). In other words, in many cases, valuing a startup equates to estimating its terminal value.
To do so, a valuer must answer the questions like the following: what is the size of the target market? What market share can the start-up capture in the future? What capital expenditure is necessary to reach this objective? What is the normal future economic profitability likely to be? What is the start-up’s probability of success? What factors (competition, change in regulatory framework, etc.) could call into question the start-up’s economic model and cause it to fail? Is the startup’s technology ahead of the curve? Will users be interested tomorrow? Can we reasonably assume that the start-up will be an attractive target for investors when its economic model becomes established? What is the risk that the start-up may not be able to finance its future investments?
Example: Shift Technology is a SaaS company that delivers fraud detection solutions to insurance companies around the world using data science. Throughout its history, Shift Technology has raised a total of $320 million in seven rounds of fundraising, including $220 million from the most recent round (May 2021) for a post-money valuation of $1 billion (TechCrunch, May 2021).
For such a venture, which brings an innovative solution to a well-established market, early funding rounds are still organized based on one-to-one negotiations. But from Series B, core business metrics are built. Then, the most “rational” approach to valuation would come from an assessment of how much the venture may capture within this market and what related value this represents, often referring to comparable past exits in the same domain. This valuation can then be fine-tuned by considering norms coming from the insurance industry and the business profile of SaaS, among other possible factors.
Sixth Deadly Sin: Applying Multiples without Controlling for the Level of Risk… and Growth!
The multiples (or “comparables”) method is probably the oldest and most widely used valuation technique to estimate the value of a company, not to mention the majority of assets. Its implementation in the case of a start-up, however, is no trivial matter. To estimate the valuation multiple, it is not enough to identify a sample of companies operating in the same sector; a valuer also needs to ensure that the target company is comparable to the sample of companies with regard to its future risk and return on investment.
In the case of start-ups, these conditions are very difficult (if not impossible) to meet. First, it is exceedingly difficult to find companies comparable to start-ups due to their uniqueness and their innovative company status. Second, it is often the case that the revenue of the start-up
is its only positive aggregate (from EBITDA onwards, all intermediate aggregates may be negative). In such cases, the multiples method is not particularly relevant because a revenue multiple does not provide information on future profitability and growth. Finally, with boundless creativity, certain practitioners value start-ups using multiples based on sectoral measures (a multiple based on the number of subscribers, users, or clients; a multiple based on R&D spending, etc.). Here again, these multiples provide no information about future growth and return on investment, and their use can lead to significant errors.
Example: The transaction multiples of technology companies vary greatly, depending on the category under consideration or even within a given category itself (see the table below). For example, for technology companies in “transport/mobility,” the revenue/enterprise value transaction multiples observed in 2018 in Europe were found to lie in a range of values between 2.4x and 19.4x. This can be explained by the fact that technological companies present risk and growth perspectives that are not comparable. In such a situation, valuing a start-up in the
technology industry using a revenue multiple is questionable.
Transaction multiples in the technology industry in Europe in 2018
| Multiple EV/Trailing 12-Month Revenue | |
| Advertising tech | 1.6x–6.7x |
| Deeptech | 4.3x–8.7x |
| Sofware as a Service | 1.4x–8.4x |
| Medtech/Biotech | 5.4x–>20x |
| Marketplace | 1.7x–8.2x |
| Fintech | 7x–17.6x |
| Travel/Hospitality | 1.5x–7.4x |
| Transportation/Mobility | 2.4x–19.4x |
| Internet of Things | 1.7x–7.6x |
| Education Tech | 4.4x–5.1x |
| Media | 1.6x–5.3x |
Source: http://www.avoltapartners.com/tech-exit-transaction-multiples/
Seventh Deadly Sin: Reliance on Sophisticated Models
Certain valuers may be tempted to think that using sophisticated financial models is the solution to valuing a start-up. This thinking was prevalent at the beginning of the “new economy” years, when a new economy was said to require new financial valuation principles!
The possibility that certain kinds of reasoning, like that proposed by option theory, was intriguing at first glance. After all, a start-up has no assets in place and the value of equity can be understood as an option granting the right to develop a new profitable activity in the next few years. However, in practice, this type of approach has proved intractable when the value of an option depends almost entirely on unobservable parameters. Valuing an option essentially corresponds to determining the volatility of the underlying asset, which in the case of a start-up is very difficult to define, much less determine its value.
More concretely, the problem is not the model but the ability to measure risk. In other words, using a sophisticated model is not the right solution to valuing a start-up. It is most likely through a solid understanding of the start-up’s future possibilities, linked to a proper probabilistic approach to growth and profitability scenarios, that the valuer will be able to propose a range of acceptable values.
Example: In an article published in this journal in 2000, Martha Amram and Nalin Kulatilaka explain how and why the use of real options relies on the ability to track market-priced risk. Using examples from oil exploration, pharmaceutical drug development, and internet companies, the authors show how specific features of the industry and the application itself determine the usefulness of the real options approach. For example, for internet companies, the value and exercise of investment options cannot be linked to risks priced in the financial markets.
“Real options provides a powerful way of thinking about future business opportunities and what is required to obtain a fully mature business or fully developed project from an initial investment. For applications with a large component of market-priced
risk, real options provides a complete quantitative framework. But when the application is largely driven by private risk, we find that real options cannot add insight beyond what is provided by
other decision tools.” 1
Conclusion
Valuing a start-up is certainly a difficult exercise, but one that can be undertaken by using the standard financial framework. Of course, the standard financial approach cannot be used when uncertainty predominates and risk cannot be quantified. For example, this would be the case for start-ups that develop technologies where the addressable market and costs of development remain largely unknown. In such cases, it is impossible to estimate the future cash flows or measure the risk. The range of equity market values that the valuer
may determine would make no sense because they would be too wide. But in many other cases, the financial approach, if correctly used, makes it possible to establish the basis on which to estimate the market value of a start-up’s equity. It is then a question of concentrating on the terminal value, determining the probability of success of the project and setting an acceptable discount rate. This approach is consistent with the standard financial framework and makes it possible to understand the relationships between the assumptions used and the range of values proposed. With the risk of justifying outrageous values having been largely eliminated, entrepreneurs and their investors can have a productive discussion of a start-up’s value—one in which the mystery of the valuation no longer remains secreted within a black box.
1 Martha Amran and Nalin Kulatilaka, “Strategy and shareholder value creation: the real options frontier,” Journal of Applied Corporate Finance 13(2), 2000. pp.15-28.
Henri Philippe – Partner – Accuracy
Franck Bancel – Academic Adviser – Accuracy
Bruno Martinaud – Director of the Technology Venture Master Program – Ecole Polytechnique