A guide to fair startup valuation by Early Metrics

Dec 16, 2018 | Publisher: Techcelerate Ventures | Category: Technology |  | Collection: Valuations | Views: 8 | Likes: 1

| 1 Contents Executive Summary Introduction Classic Valuation Methods Blue Ocean Strategy for Startup Valuation Impactful Criteria on Fundraising Success Conclusion References Acknowledgements About Early Metrics 3 5 8 13 24 31 33 34 35 | 3 Executive Summary The valuation of a company is a synthesis of multiple scenarios and therefore an art of approximation. This is all the more difficult for investors who are looking to identify the new ventures that will make a real difference in their portfolio. If we were to compare it to a chemistry experiment, startups are a gaseous substance: they move fast and unpredictably, making it difficult to take a telling snapshot of their situation and formulate hypotheses that stand the test of time. Indeed, classic valuation models are geared towards predicting the long-term behaviour of solids, ie. mature companies ready for listing or already listed. This conundrum has become most felt since the advent of Silicon Valley and, more recently, the booming of European and Asian startup hubs. Investing in seed and early stage ventures has never been more exciting but the question of fair valuation still remains, as the current tools are ill-fitted for this exercise. As a rating agency specialised in assessing the growth potential of startups and scale-ups, Early Metrics has seen its clients, investors and multinational companies alike, struggle with this valuation process time and time again when trying to invest in a young company. That is why we set out to conduct this research into how the valuation method of new ventures could be improved. By assessing the strengths and weaknesses of three most commonly used valuation approaches (DCF, multiples and VC method) we were able to identify the key pain points to be improved. By reviewing the available academic literature and correlating our findings to our database of over 2000 rated startups, we were able to define the adaptations that need to be brought to traditional methods to produce fair valuations. Preliminary findings on traditional valuation methodologies We therefore found that it was still relevant to use valuation techniques such as the DCF and multiples approach, as long as certain considerations specific to new ventures are "Startups are like a gaseous substance: they move fast and unpredictably, making it difficult to take a telling snapshot" included. As such, we strongly believe that by combining the DCF, multiples, venture capitalist method as well as the entrepreneur's expectation, it is possible to obtain a fair startup valuation. Using Early Metrics' statistical distribution of growth potential scores, we were also able to add a layer of refinement to the weighted average and to provide an extra level of accuracy. Adding non-financial criteria to valuation methodologies However, beyond its estimated value, several non-financial criteria can impact a startup's potential to raise funds at an attractive valuation. That is why we decided to explore the impact of qualitative criteria on fundraising. Through our backtesting process, we collected information 12 and 24 months after Early Metrics' rating on 469 startups looking for funds and then compared the data to the predictive analysis performed at the time of the rating. This allowed us to identify which parameters can significantly improve the chances of closing a funding a round that meets the entrepreneurs' goals. We also found that a startup's sector can impact its chances of fundraising. Lastly, we analysed the relevance of growth potential in fundraising and found that there is indeed a correlation between the Early Metrics score and their fundraising success. These results lead us to believe that the valuation process can be indeed affected by qualitative aspects of the venture. We hope that by sharing our research and findings we will be able to bring greater transparency to the valuation of startups and that in turn this will lead to successful business relationships between investors and innovative startups. 4 | 2018 Early Metrics. All rights reserved. | 5 Introduction This white paper will evaluate how traditional valuation methods can be adapted in order to obtain a more reliable value for seed and early stage ventures. Firstly, we will give a brief overview of the key levers in valuation and of the difficulties that most face when trying to value early stage companies. We will then assess the strengths and weaknesses of the most common methods, namely the discounted cash flow (DCF), multiples, and venture capitalist approaches. Following this, we will look into the modifications that can be brought to these methods for the valuation of startups. Using the example of a fictitious company, we will exemplify how these adaptations can indeed lead to more comprehensive valuations. Finally, we will explore which non-financial criteria have the most significant impact on a venture's chances of fundraising at a desired valuation. Based on our database of backtested startup ratings, we will analyse the relationship between the venture's sector and fundraising success as well as the potential correlation between the growth potential of a venture and its fundraising ability. Moreover, we will rank the impact of several non-financial criteria on the startup's capacity to raise funds. Key levers in valuation Before diving into the different available valuation methods, we thought it would be interesting to give a brief overview of the factors that draw investors to young ventures in the first place. There are essentially four key levers in early stage investment: cost efficiency, growth potential, market dynamics and leverage. In other words, a venture capitalist tries to achieve a return on investment in four ways. Cost efficiency: Indeed, an investor might choose to get involved with a startup if there is a potential to cut costs and increase cost efficiency within it. In this regard, the free cash flow (FCF) and operating margin of the venture might be important factors in the investor's decision. Growth potential: Young companies that have high chances of seeing an explosive growth and undergoing a successful exit can also yield high returns for investors. So even if a venture lacks some of the attributes needed to grow fast, investors might still choose to offer capital if they see it as an opportunity to bring in their expertise and boost the company's growth potential. Leverage: Leverage is another major factor that impacts early stage investment.. Debt can lower the cost of tax and consequently increase the value of equity. Therefore, being able to leverage debt can have an important effect on the attractiveness of an investment opportunity. Market dynamics: Additionally, investors may be influenced by investment market dynamics especially in sectors where the competition to find good targets is high between venture capital and private equity players. Investors often also use these dynamics to their advantage to increase their return based on general excitement that builds around specific markets or products. 6 | 2018 Early Metrics. All rights reserved. The Venture Capitalist Samantha Jrusalmy, Partner at Elaia Partners "We like to be the first ones to invest in a company rather than investing in more mature companies, that are less risky but offer a lesser return. The second reason why we do early stage investments is that we prefer this stage of a company's life from a human point of view because it is when everything is being created: since we choose only early stages startups, we are there all the steps of the way and it creates a bond between the entrepreneurs and us. We want to live awesome ventures with great entrepreneurs so we partner early and roll up our sleeves. Finally, it allows us to stay in the loop, with the startups to follow on more funding rounds. | 7 Lack of history: One of the key factors that make new ventures difficult to value is the fact that they have a very short history. This may seem obvious, but a one to two-year long history implies it is much harder and riskier to use predictive methods based on financial data. Indeed, startups generate little to no revenue while they incur sizeable charges in order to set up their business. Therefore they generally have negative cash flows. Low survival rate: New ventures generally have a very high risk of bankruptcy, especially in their first four years. The commercialisation and scaling up stages seem to be the toughest and most determinant in terms of survival. John Watson and Jim Everett's study (1996) of over 5196 ventures showed the average annual failure rate exceeded 9%. Therefore, valuation methods must somehow reflect this important risk in the case of young companies. It is worth noting that, although bankruptcy risk is highly correlated to the age of a venture, startups of the same age can still be at very different maturity stages, ranging from just an idea company, to having a minimum viable product (MVP) or a fully- fledged commercialised product. Valuation divergence due to dilution: Another factor which complicates the valuation of startups is the risk of dilution of the company's equity. This is due to the fact that startups are highly dependent on private equity, rather than debt or public markets. Founders generally provide the vast majority of the starting capital before looking for external investors. Chances are that a new venture will go through several rounds of fundraising to acquire the necessary capital to develop their product, go to market and scale. This means that the first investors incur the risk of seeing the value of their shares decrease over time. Therefore, even if a venture is extremely successful at increasing their overall value at exit, the value growth will be lesser for the first investors. This leads to what Luis Villalobos refers to as the valuation divergence: the growth of value at exit of a startup compared to the growth of value perceived by initial investors is generally off by a factor of three to five. Investors generally try to protect themselves by negotiating warrants on first cash flows, veto rights, a ratchet or other special clauses. The difficulties of startup valuation On top of the aforementioned levers, there are factors that are particular to young ventures which should be considered in the valuation process. In fact, these are the key reasons which make valuing startups more difficult than mature companies. Below we look at the main three startup features that complicate the process. | 7 The Accelerator Ccile Brosset, Director at Bpifrance Le Hub "Early stage investors have so much choice when it comes to picking a startup, so it's difficult for them to place the right bet. Startup valuation is also tricky as it's mainly based on immaterial things, with little hard data to use other than that of the market the startup operates in. Classic Valuation Method #1 Discounted Cash Flow (DCF) How it works Income approach techniques seek to determine the value of a company by assessing the value of the future cash flows to be received by the shareholders or the business. This value is discounted for the passage of time and risks at the return rate required by the investors. The discounted cash flow or DCF is the most widely used income approach technique. It aims to forecast the value of cash flows to the firm based on its P&L, ignoring the effects of leverage. It also determines the value of the shareholders' wealth by subtracting the net debt. Simply put, the DCF is measured by combining money, time and risk. The DCF method should discount cash flows until the business stops. Indeed, most businesses are assumed to be a "going concern". Therefore a business plan is generally forecasted over 15 years and then a terminal value (TV) is computed, assuming the company has reached a mature stage. The formula to calculate FCF to the firm is: Free Cash Flow to Firm = EBIT x (1 - Tax%) + Depreciation and Amortisation - Net capital expenditure - Increase in working capital Perpetual growth rate, also referred to as the terminal growth rate, represents an assumption that the company will continue to grow (or decline) at a constant rate into perpetuity. Typically, the rate ranges between the historical inflation rate (2% to 5%) which can sometimes be approximated by the historical GDP growth rate when better suited. This rate is used to determine the terminal value of a company in the DCF approach, among other things, and gives an indication of a company's long- term growth projection. 8 | 2018 Early Metrics. All rights reserved. | 9 For standard businesses, the terminal value can be estimated using the Gordon Shapiro formula: TV = FCFn / (R - g) Where: TV = Terminal value (at liquidation) FCFn = Normalised free cash flow to the firm (in terminal year) R = Weighted average cost of capital (WACC) g = Perpetual growth rate To then calculate the DCF, the formula is: DCF = [CF1 / (1+R)1] + [CF2 / (1+R)2] + ... + [CFn / (1+R)n] Where: CF = Cash flow R= Discount rate (WACC) Weaknesses When it comes to using DCF to value a startup there are several limitations that arise. Firstly the lack of historical performance on which to base forecasts hurts the reliability of cash flow projection and the terminal value calculation. The youth of the company also implies that its future performance is very uncertain and its associated risks are naturally higher. Another limiting factor is the fact that new ventures are often loss-making and therefore have negative cash flows. As was mentioned in the introduction, the risk of bankruptcy is much higher for a new venture. Hence, it is impossible to base its terminal value on a 15 year forecast when it might not even survive 4 years. Meanwhile, startups have great upside potential in case of success. Lastly, stable growth is out of reach when looking at a startup's business plan. Indeed, companies that are between the Seed and Series B round of funding generally experience an extremely rapid growth. This speed of growth clearly cannot be sustained on the long term, therefore it cannot be used to predict the perpetual growth rate, an important variable in the calculation of terminal value. Therefore, the Gordon-Shapiro is ill-fitted for high-growth businesses. There is one more limitation to the DCF that is relevant not only for the valuation of startups but also that of standard businesses: it does not take into account market trends and the company's positioning. That is why it is worth combining the DCF method to the next approach we will analyse: the multiples approach. Classic Valuation Method #2 Multiples Approach How it works The multiples approach, also known as peer multiples method, estimates the value of a company by comparing it to similar companies. Whereas the DCF was an income approach, this is a market approach. To use this approach, the first step is to choose which market and companies to compare the business to. Then, the metrics which to base the comparison on are identified and lastly the value or price of each metric is calculated as a multiple. This allows for the measurement of a relative valuation which should reflect its long term prospects. The aggregates used to compare peers usually include: the top line, EBITDA and the number of customers. The market price is also defined by looking at peers with a similarly structured P&L and business model (subscription, freemium, etc.). 10 | 2018 Early Metrics. All rights reserved. Weaknesses Although this approach is arguably better suited for young ventures, it still presents certain weaknesses. Firstly, many startups are setting new standards by inventing new products or by disrupting existing production standards or distribution channels. This means there is often no market to compare to for groundbreaking innovation. Secondly, at the risk of stating the obvious, listed peers are generally bigger and older companies than the startup in question, so they are not similar enough to be compared to each other. Then, metrics can be negative or too small to be used as a reference. Indeed, revenues are sometimes too low (or non-existent) to be used as a base. A startup's revenues also tend to evolve fast, which begs the question: which revenues should be taken into consideration? The previous year's? The TTM or MRR? Furthermore, other metrics aside from revenue generally remain negative, even for high-potential startups. | 11 Classic Valuation Method #3 Venture Capital Method How it works The venture capital (VC) method takes into account several of the considerations of the DCF and multiples approaches previously presented. However, this approach also relies heavily on the investor's market knowledge and, to a certain extent, intuition. Pricing a young startup based on its current value generally amounts to quite a small sum and is not necessarily representative of the potential of the venture. The VC method aims to mitigate this problem by giving a theoretical future value (or exit value) based on several scenarios. The first step is to look at the turnover and specific aggregates from the P&L and then to apply a multiple to these parameters. This results in an exit value, which is usually high as it only takes into account the startup's potential and not the risks. To then obtain a net present value of the targeted exit value computed, one must apply a discount rate in the form of a percentage on the overall value previously calculated. This rate is representative of the risks associated with the venture and it is primarily based on the maturity of the company and its bankruptcy risk. Weaknesses Because the venture capital method partly relies on the multiples approach, it naturally shares its limitations, such as the difficulty to find comparable aggregates and relevant companies against which the venture in question can be assessed. Moreover, this method can suffer from a lack of transparency especially if mistakes are made when defining key assumptions, such as revenue projections, since they can impact the validity of further steps and are difficult to spot. This can also be frustrating for entrepreneurs because, as an empirical method, it is not always the clearest. Lastly, the opacity of the discount rates can be problematic but misunderstandings can be avoided if the investors clearly define the IRR, i.e. their return objectives. Other classic valuation methods The three methods analysed earlier are certainly not the only ones available to value a company. Notable alternatives include the First Chicago method, which combines the Multiples and DCF methods applied to three scenarios (best, base and worst scenario), as well as the profitability index approach, which quantifies the amount of value created per unit of investment. However, the DCF, Multiples and Venture Capital methods remain the most commonly used ones and have the strongest backing in terms of academic literature. That is why we will not delve further into other methods. Instead, we will explore how the limitations of these three main approaches can be mitigated to obtain a more representative valuation for early stage ventures. 12 | 2018 Early Metrics. All rights reserved. | 13 Blue Ocean Strategy for Startup Valuation When we set out to research better ways to value startups, we decided early on that it was unwise to try and reinvent the wheel. We were not looking to create a solution from scratch which would compete with much more established methods, used and recognised by the investment industry for decades. Instead, we focused on bringing small but significant adaptation to existing techniques and to combine them in a way that is most representative of a young venture's value. The traditional methods we chose to focus on have proven their relevance for standard businesses, but at the time of their conception they were just not meant to be used for young ventures. That is why we identified where their flaws lied in respect to valuing startups and defined the following adaptations to optimise them. | 13 Adapting the DCF to startups Before we delve into the adaptations of the DCF for startups, it is worth noting that challenging the business plan of a venture is an important step before even starting the valuation process. Indeed, if it is done properly, it can significantly improve the level of certainty of the projections. We recommend challenging the business plan of a startup by looking not only at trends, but also at measurable metrics. At Early Metrics, our analysts challenge a venture's business plan by formulating hypotheses based on the data of other business plans from comparable startups. This allows to get a clearer picture of the venture's financial health and level of preparation for future development. 14 | 2018 Early Metrics. All rights reserved. Reducing the forecasting period Given that startups generally experience explosive growth in their first five to ten years, they are far from reaching a growth in line with the market or global GDP. Therefore, the perpetual growth rate (PGR) is not a relevant indicator. New ventures are very far from reaching a stable pace of growth and their lack of history means a projection over 15 years would carry a high level of uncertainty. That is why we argue that it is best to limit the forecasting period to 5 years when valuing startups through the DCF method, in order to reduce the level of uncertainty. Focusing on the top line and exit value As it is not possible to calculate a young venture's PGR, some of the conditions of the Gordon-Shapiro formula are unmet. Therefore, the terminal value (TV) cannot be calculated as a normalised cash flow. To compensate for this, we suggest that the TV should be measured primarily based on the top line. Furthermore, we argue that the exit value of a venture should be considered as a potential cash flow to the shareholders. Measuring risks particular to startups As we mentioned earlier, seed and early stage companies have a high bankruptcy risk. Therefore, this risk and other factors specific to startups should be measured and taken into account into the DCF. By identifying and quantifying the risks related to the venture, it is possible to adapt the DCF method in a way that is more representative of the venture's value. The IRR should reflect these risks as well. | 15 CASE SCENARIO Startup X is a (fictitious) Scottish startup building new manufacturing robots to optimise the production of electric vehicles. The company has been running for two years and has attracted the attention of a VC fund in France specialised in Industry 4.0 solutions. To help the fund decide whether to move forward with Startup X, Early Metrics does an Investment Scan which includes a growth potential rating and a financial valuation. We obtain the following value using the DCF method adapted to startups: Adapting the Multiples Method to Startups Building a database of qualified and comparable aggregates As startups cannot be compared to listed companies in the same industry, the metrics used in the multiples method must be chosen differently than in traditional cases. For instance, we recommend to select peers who have a similar: product and in the same industry approach (technology or commercially led) maturity (seniority, revenue, product stage, etc.) growth potential business model P&L and cost structure. Then, we argue it is best to use the Multiples method by combining several data points, such as a three-pronged approach based on P&L, business model and industry. This is particularly relevant for very innovative businesses who do not have any direct competitors and operate in a new industry. In other words, it allows us to create a relatively homogenous database of comparable aggregates and compensates for the lack of "similar stories" that can make the multiples approach seem inadequate for startups. Moreover, when selecting the metrics, it is worth first defining the drivers that specifically affect the value of the venture in question. Adapting to the right time scale When looking at historical revenues, it is important to adapt the time scale to the venture in order to collect the most relevant and representative data. Indeed, startups change so fast that looking at the previous year's results may not be representative of their potential at all. Therefore, it is best to adapt the time scale of the historical revenues used in the valuation according to the company's product and commercial maturity. For instance, using financial results from the previous month can skew the perception of a young business as it can experience quick and large fluctuation month after month. We argue that it is most reliable to consider results over the previous two semesters when looking at a startup's financial history. Focus on positive metrics Once the metrics have been selected, we argue that it is best to compute multiples on the metric that is the most likely to be above zero. In this regard, sales figures can be a reliable metric to focus on for early stage businesses. 16 | 2018 Early Metrics. All rights reserved. | 17 CASE SCENARIO Since Startup X operates in the robotics and manufacting markets and has had a turnover of 570,000 in 2017, we compare it to other startups of similar maturity and active in the same sectors. We obtain the following value using the Multiples method adapted to startups: Adapting the VC Method to startups Identifying and measuring layers of risk In order to reduce the level of uncertainty and improve on the VC method, we recommend conducting an in-depth identification and measurement of the risks relevant to the startup in question. Indeed, when using this approach, investors usually apply an overall discount rate primarily based on the maturity of the venture or on the financing round stage of the startup as per Damodaran's academic work and other academic literature. However, funding stage is not the only metric that could impact a startup's value negatively. We argue that there are key risks that should be considered on top of the startup's age to determine its value, among which we can focus on liquidity, bankruptcy and dilution. The liquidity risk refers to the potential lack of marketability of a product if the market is not mature enough or demand decreases drastically. It is usually considered to be quite stable at 35%. Then, the bankruptcy risk of a company is largely reliant on the age of the startup and based on academic literature, such as Damodaran's research. Lastly, the dilution risk stems from a companies need to raised capital through several funding rounds. The more rounds a startup wishes to do, the less the value of its stock. This is therefore detrimental to its valuation especially for the first investors buying shares in the company who will see their investment grow less than the overall company value. By considering these three risks, we can obtain a discount rate more closely tailored to the profile of the venture. 18 | 2018 Early Metrics. All rights reserved. | 19 CASE SCENARIO Startup X has to face specific challenges such as certification to bring its product to market. So we defined the risks and opportunities particular to the startup and then measured their impact on future revenues in three scenarios. We obtain the following value using the VC method adapted to startups: Considering the entrepreneurs' goals Although it is rarely taken into account, an entrepreneur's goal for their company can be a good indication of a venture's potential. If the startup's founder has set a desired value in line with that measured by traditional methods (DCF, multiples, etc.) then the investor can be reassured in the fact that the venture is run by a person that has a realistic vision of its potential. On the other hand, it may be beneficial for an entrepreneur to aim a little higher than the conventional value calculated through classic methods. This could indicate that the management of the startup will work hard to surpass expectations and potentially make a difference compared to its competitors. Lastly, if the entrepreneur's valuation is completely off the mark and unrealistic, it could be considered as a red flag for investors. CASE SCENARIO The team at Startup X aims to raise 4.2 million and give away 15% of their shares. They need a lot of capital to improve the design of the robots and scale their production. The company is also hoping to open a new site in Germany. So in this scenario, the investor will have strong bargaining power. By looking at Startup X's need for funding and dilution goal, we can determine how the investor's bargaining power would affect the valuation bracket: 20 | 2018 Early Metrics. All rights reserved. | 21 The Startup Founder Sylvain Tillon, CEO at Tilkee " The valuation of an early stage startup is a matter of power (that investors don't want to take generally), of gauging offer and demand, and sticking a finger in the air. More seriously, our valuation was calculated on the basis of the potential exit value of Tilkee and on our turnover (recurring revenue times five). This reflected the value of our startup quite well, which we capped in order to further the project on our terms: we refused to over-sell (contrary to what fundraisers advised) so that we could maintain a logic that made sense with our growth plans. We accepted a slightly lower valuation but chose investors that best suited us in terms of experience and vision. We also opted for a clear stock option system with achievable goals. For this we had an advantage, we didn't need funds in the short term: we were at breakeven and we had a bit of liquidity. This allowed us to be patient and demanding! The Venture Capitalist Samantha Jrusalmy, Partner at Elaia Partners "We invest in companies, get a share of the capital, a board seat and, within six to seven years, we need to have an exit. If we are not convinced that we can achieve at least five times what we invested, then it's not a good deal for us. Our focus is financial performance so we look at ambitious and global projects. 22 | 2018 Early Metrics. All rights reserved. Weighted average of methods As we have seen so far, each valuation method has its strengths and weaknesses. By combining multiple approaches, it is possible to mitigate their limits and obtain a more representative value. After calculating a startup's value using the aforementioned methods, we recommend doing a weighted average of the obtained results. To weigh each method, we analyse the cost structure and nature of startup and then decide which approach is the most representative. It is rare for the DCF to be the most representative valuation for a startup. This approach works best for businesses that are highly predictable. If a startup signs long contracts with its clients and its management has worked extensively on its projections, making its business plan very reliable, then we could consider that the DCF should have a bigger weight in the averaged value. Although it is very unlikely for a young venture to meet both these conditions, the DCF is the only method that reflects the structure of costs so it is still interesting to consider. When it comes to deciding which one of the multiples or the VC method is most representative, things get a little trickier. The VC approach calculates the future performance of a business (taking growth potential into account), while the peers multiples method measures results achieved so far. Therefore the VC method is better suited to startups with a big growth potential. The multiples approach, on the other hand, is better if revenue forecasts are very uncertain. Overall, the VC method can be seen as more refined because it considers the evolution forecast specific to the valued venture, hence producing a more tailored valuation. Each method produces a bracket or a range where the value should fall. By combining the results of multiple methods there is a risk ending up with quite a large bracket, which in itself is not very informative. To refine this, we use the Early Metrics database of rated startups and see where the company in question falls in the statistical distribution of ratings. In other words, we determine how this company's growth potential compares to others. Depending on the decile where the startup's rating falls, we are able to determine the most likely value within the previously obtained bracket. | 23 CASE SCENARIO In the case of Startup X, the valuation method that is best suited is the venture capital or VC method as it takes into account specific risks and opportunities in the electric vehicle manufacturing sector. As part of Early Metrics' rating, Startup X's growth potential has been scored. Looking at where this score sits compared to that of other rated startups, we find that Startup X is among the top 10% of startups. This allows us to define the amount in the calculated bracket that most accurately reflects Startup X's value. By combining the weighted average of valuations obtained through various methods and looking at the decile that Startup X's rating falls in, we obtain a final valuation: Impactful Criteria on Fundraising Success Overview of fundraising success Early Metrics focuses on measuring the growth potential of technology startups and SMEs using a proprietary methodology. This methodology is centered around three axes of analysis: the management team (eg. ability to convince, past experiences of the founders), the product (eg. maturity, innovation level) and the market (eg. positioning, barriers to entry). Analysts at Early Metrics rate several non-financial criteria in each of these three pillars, collecting hundreds of data points which are then summarised in a score out of 100. Since its foundation, Early Metrics has rated more than 2000 startups in 15 sectors. A portion of this database (900 companies) has also been backtested after the rating, in order to assess the validity of our methodology and maintain a high level of quality in our rating model. This data has also allowed us to identify interesting trends relating to the valuation and fundraising potential of startups. To investigate which non-financial parameters have a strong impact on a startup's potential to fundraise at its desired value, we turned to our own data of backtested ventures. Our first step was to select from our database those which declared wanting to fundraise at the time of rating. This gave us a sample of 469 companies. We then looked at the overall success rate of these startups in raising funds in line with the entrepreneurs' expectations. 24 | 2018 Early Metrics. All rights reserved. Table 1: Overall fundraising success 12 and 24 months post-rating Out of the startups that said they were looking for funds at the time of rating by Early Metrics, 35% managed to secure funding 12 months after being rated and 48% raised 24 months after the rating. As our backtesting process relies on feedback provided by the startups, our samples at 12 and 24 months are not homogenous. Table 2 shows the data collected from the 80 companies backtested both 12 and 24 months after rating, i.e. where the startups replied to our survey twice. | 25 Table 2: Fundraising success of homogenous sample at 12 and 24 months post- rating From the table above, we can see that the sample analysed at 12 and 24 months post-rating confirms the trend observed on the first sample (Table 1). Indeed, 53% of startups closed a fundraising round at or above their expected value. Among these, 33% took 12 months or less to get funding. Analysis by industry After analysing the overall success rate in raising funds of our database of rated startups, we decided to delve deeper into our data and explore the potential correlations between the industry of the young ventures and their potential for fundraising. To proceed in this analysis, we first had to filter out the sectors in which we lacked representative data. Below is the dataset by sector that resulted: Table 3: Fundraising success rate by sector Among the 15 sectors researched in Early Metrics' database, three sectors were excluded from the analysis (AgriTech, EdTech, Tourism and Leisure) as we did not have a representative sample of startups in these (less than 15). The analysis of the sample just over 12 months, which is more homogenous, confirms the aforementioned trends. It also allows us to identify two surprising phenomena - the first being that the CleanTech industry also seems to be more successful than the average in securing funds. The second notable observation is that startups in the IT & Data sector as well as those in the eHealth sector seem to have a particularly low fundraising success rate in the first 12 months following their rating. Although it was excluded in the overall analysis, it is worth noting that the Tourism and Leisure sector has a very strong fundraising success rate. Indeed, 11 out of 14 startups (or 78%) managed to raise funds within 24 months of the rating. This trend would have to be supported by further data to prove its validity, but it is certainly one to look out for. Graph 1: Analysis of fundraising timing by sector Among the selected industries, three of them had an above average success rate: BioTech, Mobility, E-Commerce & Retail. On the other hand, two sectors underperformed on their overall success rate: Smart Cities as well as B2B Software. 26 | 2018 Early Metrics. All rights reserved. | 27 Analysis by growth potential score Beyond the sector of the business, we wished to analyse which other factor would impact the rate of success in fundraising. Firstly, we decided to investigate whether there is a correlation between the growth potential of a startup and its chances of fundraising successfully. We calculated the overall average rating for each sector, the average rating of startups that failed to raise what they hoped, and the average of those who succeeded. The results have been compiled in the table below with an index basis of 100: Table 4: Growth potential score by sector on 100 basis The data above generally confirms the hypothesis that growth potential has an impact on fundraising success: the majority of startups that managed to raise funds had a better growth potential score than those who failed to raise. Table 4 shows that there are three outliers contradicting the trend (Biotech, EdTech, Fintech & InsurTech). This is also clearly visible in Graph 3, which highlights the differences between fundraising success rate and the delta of the scores of startups that raised successfully versus those that didn't. Graph 2: Growth potential rating gap between startups that raised funds and those that did not by sector Graph 3: Analysis of the impact of growth potential (rating) and of the sector of the startup on fundraising success For the Fintech & InsurTech as well as Biotech startups, we can assume that they do not align with the trend because they are highly regulated sectors and therefore involve a longer time-to-market, which can hurt their overall growth potential but not necessarily their fundraising success rate. Moreover, Biotech products are usually capital intensive projects as they require upfront investment from the startup in specific equipment and lengthy R&D. As investors are familiar with the challenges related to this sector, they do not penalise startups based on their lesser growth potential. We can also infer that Edtech also does not reflect the trend due to the limited size of the sample. So from the data above, we can conclude that growth potential is generally positively correlated to fundraising success, but the importance of the growth potential can be influenced by the sector in which the startup operates. 28 | 2018 Early Metrics. All rights reserved. | 29 Innovativeness of the project How original a startup is. The innovation can be in the nature of an offer (a totally new product), technical (a novel production process), marketing (new business model) and/or a geographical innovation (copycat in a new market). Complementarity in skill sets How much the skill sets of the various team members complement each other. The more variety there is in the team's capabilities, the easier it is for the startup to perform well in different aspects of its activities (product development, go-to- market strategy, etc.). Influence in the press and social media How many followers a startup has on social media and how many mentions in the press (different thresholds apply to different maturity stages and sectors). Speed of execution How fast a startup can bring a product to market. This can be affected by the skills of the team members as well as the regulatory environment or even the complexity of the product. Financial management skills How experienced and skilled the team is in managing and monitoring the company's finances. Analysis of impactful qualitative criteria As part of our growth potential assessment of startups, analysts at Early Metrics evaluate a set of qualitative criteria. We have therefore asked ourselves which of these non-financial parameters could be good indicators of fundraising success. For each criterion and for the entirety of the sample, a score between zero and five was attributed. We then divided the sample in two: those that had raised funds at the amount expected by the entrepreneurs and those that had failed to do so. We then measured the relevance of each criterion in relationship to the achievement or failure to reach the target. The model also eliminates collinearity from the results. Following this, we identified among the available criteria those that enabled the prediction of the success or failure of a fundraising round. To carry out this process, we adopted a simple statistical approach based on a binary variable (success or failure of the fundraising). Moreover, the analysed criteria were selected in such a manner to optimise their number among the overall list of available parameters and to predict the occurrence of the binary event. Among the 25 criteria analysed, five of them have been identified as significant (ie. with a shown predictive power), non-linked (with correlations between the criteria as close to zero as possible) and allowing a reliable prediction of the success or failure of a fundraising. By focusing on these 5 qualitative criteria, it is possible to build a predictive model for the success of a funding round. If the startup does well in these five traits it will therefore have a greater negotiation power and better chances of reaching its goal. 30 | 2018 Early Metrics. All rights reserved. The Accelerator Ccile Brosset, Director at Bpifrance Le Hub " I find this list of five criteria very relevant. Indeed at Bpifrance, we mainly look at the innovativeness of the project and the complementarity of the team's skill sets. One topic that could be added to these five is the network of the founders. Some teams can make it on their own but they're rare. For instance, Mathilde Collin, CEO at Front, managed to close a funding round of $66 million led by Sequoia in big part thanks to her personal business network. So it's very important to be able to surround yourself with the best people internally, by hiring the best candidates, and externally, by making strong allies. The Venture Capitalist Samantha Jrusalmy, Partner at Elaia Partners "At the stage where we invest at, meaning pre-Seed, Seed and Series A, the main priority is the team. What we want to see is complementarity not only in the skills but also in the vision of the founding team members. At Elaia we only invest in disruptive projects that have a real technological asset but also that set barriers to entry from the very start. Since we have an expertise in tech investments and we can't assess performance based on traction or execution in a very young venture, we look at the innovativeness of the project which is also a way to "de-risk" ourselves. Knowing how to do a proper P&L and managing company's accounts can also put entrepreneurs in the spotlight, but this is not very relevant for pre-Seed startups since they have little financial data to handle. However, we do challenge the business plan extensively, mainly to understand the coherence of the figures rather than their total accuracy. The Startup Founder Sylvain Tillon, CEO and founder at Tilkee "To my mind, the chances of fundraising success of a startup are also linked to the whole team at large, not only to the management. I was quite surprised that no fund contacted our collaborators to know more about their motivation, their trust in the project, our management style... | 31 Conclusion Assessing the value of a startup is always a difficult task and in this white paper we only scratched the surface as to why that is. It is also a process that undeniably includes an element of subjectivity to some extent. Nonetheless, we have seen that bringing certain alterations to traditional methods and combining their results allows for a relatively reliable calculation of a startup's value. In particular, we argue that when using the discounted cash flow or DCF it is best to limit the forecasting period to five years, to calculate the terminal value based on the top line, and to calculate the risks specific to the venture. Alternatively, if the multiples method is taken, it is important to build a database of qualified metrics and take a three-pronged approach to compare peers across these variables. Moreover, we recommend focusing on positive metrics and looking at the financial data over the last two semesters rather than the past year to obtain a more accurate snapshot of the venture's potential. On the other hand, we believe the venture capitalist method can be improved by identifying and quantifying the major risks faced by startups such as risks of liquidity, bankruptcy and dilution rather than just applying a standardised discount rate based on the company's maturity. We also suggested considering the entrepreneurs' desired value in the overall process, as this can be an indication of their ambition and their ability to self-assess. By applying these adaptations and combining all these approaches, we argue that one can obtain a bracket of valuation that is more reflective of the startup in question compared to traditional methods. Thanks to Early Metrics' database of growth potential ratings, we have shown that we can apply an extra layer of filtering and refine the bracket in relationship to the startup's positioning compared to other rated businesses. Having data about the growth potential of startups has also led us to wonder how non-financial metrics could impact the fundraising success rate of young startups, and therefore affect their valuation. Looking at a sample of startups 12 and 24 months after being rated by Early Metrics, we found that 53% of ventures in the sample closed a funding round at the value desired by the entrepreneurs. Among these, 33% took 12 months or less to get funding. Then, we analysed the ventures' fundraising success in relationship to the sector they operate in and found that in some sectors it is easier to attract capital than others. Among the selected industries, three of them had an above average success rate: BioTech & MedTech, Transport & Mobility, E-Commerce & Retail Enablers. Through further analysis of our database of ratings, we also observed that a better growth potential assessment does generally correlate positively to higher success rate in fundraising, at varied levels depending on the sector. Finally, we delved deeper into the qualitative data to find out which attributes are the best indicators of fundraising success, implying an attractive valuation. The five most impactful criteria were identified as speed of execution, influence on social media, complementarity of the team, innovativeness of the project and financial management skills. Although not directly related to the valuation methods analysed earlier, these qualitative metrics are important as they do ultimately impact the venture's chances of success, not only in fundraising but also in reaching maturity and expanding. | 31 This is a preliminary study on the non-financial criteria that weigh into valuation and fundraising, so we do acknowledge some limitations. For instance, our samples of startups analysed at 12 months after being rated by Early Metrics and then after 24 months are not homogeneous. Indeed, the sample at 24 months is cumulative and includes the startups that raised in the first 12 months post-rating. The decision to combine the two was driven by the need to build a sample size of statistical relevance and allowed us to draw interesting results from the data. Moreover, we lacked data into certain sectors and therefore had to focus our research on fewer markets. However, we argue the study was still representative of a wide range of sectors. We hope that by sharing our research and findings we will be able to bring greater transparency to the valuation of startups and that

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The valuation of a company is a synthesis of multiple scenarios and therefore an art of approximation. This is all the more difficult for investors who are looking to identify the new ventures that will make a real difference in their portfolio. If we were to compare it to a chemistry experiment, startups are a gaseous substance: they move fast and unpredictably, making it difficult to take a telling snapshot of their situation and formulate hypotheses that stand the test of time. Indeed, classic valuation models are geared towards predicting the long-term behaviour of solids, ie. mature companies ready for listing or already listed. This conundrum has become most felt since the advent of Silicon Valley and, more recently, the booming of European and Asian startup hubs. Investing in seed and early stage ventures has never been more exciting but the question of fair valuation still remains, as the current tools are ill-fitted for this exercise.

 

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