Startup Investigator Framework 1.0
The objective of the framework is to guide the evaluation process and ensure a consistent analysis of a startup. The analysis should provide guidance and inform the decision on whether to invest in a particular startup.
The evaluation process can be split into two components:
- Qualitative Evaluation
- Financial Valuation
The qualitative evaluation is inspired by the Payne Scorecard Method which was developed by Bill Payne. The method aims to provide a scorecard for a startup based on a few success factors with each factor allocated a weight. The weights are allocated based on the importance an investor / analyst placed on that factor. See below the factors that we considered and their associated weights.
Is the problem popular? Is the problem growing?
Is the problem encountered often?
Does it need to be fixed now?
Does it require capital to solve?
Can the solution to this problem be enforced?
Is the solution 10x better than existing solution / competition?
Is the solution scalable?
Is there a product-market-fit? Is there a clear value proposition for customers?
Is the business model clear and profitable?
|Traction to Date|
Does the startup has a functional MVP?
Is the startup quick in iterating on their MVP?
Is the startup securing paying customers for their product?
Is there sufficient barriers to entry as the business scale?
Is it easy for competitors to re-create similar / more superior solution?
Is it easy for existing customer to switch to a competitor?
Is the founding team capable of delivering the outcomes required?
The evaluation essentially involves answering a series of questions that eventually help score for a factor. A score from 1 – 5 will be provided to each question answered. The sum of the score from each question will contribute to the overall score of the factor considered. See below an example when evaluating the “problem” factor.
|Is the problem popular?||4||A rule-of-thumb table will guide the scoring. For example, score 1 given to a market of < $100m and score 5 given to a market of > $1b|
|Is the problem growing?||3||A rule-of-thumb table will guide the scoring. For example, score 1 given to a growth rate of 5% and score 5 given to a growth rate of 20%|
|Is the problem encountered often?||4||A rule-of-thumb table will guide the scoring. For example, score 1 given to a problem encountered once a year and score 5 given to a problem encountered a few times daily|
|Does it require capital to solve?||2||A rule-of-thumb table will guide the scoring. For example, score 1 given to low capital intensive solution and score 5 given to high capital intensive solution|
|13 / 20 (65%)||The overall score for this factor will be multiplied by the weight before being summed up to the overall score for all factors.|
The scoring system is developed using the industry average as the baseline i.e. if a question or factor is given a score of 3, it means that the startup is at the industry average for the factor considered. This process can be slightly biased, as it is based on a rule-of-thumb industry average guidance, and hence will be updated from time to time.
In addition to this scorecard method, we will also be answering the “Peter Thiel 7 Questions” and implement the “Berkus Method” to supplement our scorecard analysis. The key to this process is not just to get the final “score” for the startup, but also the process of answering these questions to get a feel of the business and further generate any other valid questions about the business.
In the last part of the qualitative analysis, we will get a few experts in the field the startup is specializing in and get their thoughts on the product that the startup is building and the plan the startup has to execute their vision. For example, if we are analysing a startup that is trying to create an app for automated investing using algorithmic trading, we will get some experts to provide some insights into what they think about the performance of the algorithm that the startup has developed. Most of the time, we are not experts in what a startup is specifically building and may not know how to benchmark if a product is superior than its competition or not. The aim is to get some experts to inform us in this area.
The second component of the evaluation process is the financial valuation of the startup. Financial valuation of a startup is extremely difficult because of the uncertain nature of the business. The objective of financial valuation of a startup is to ensure that the terms of raise is fair and within the range of industry average. There are a few methods that we will be exploring:
1. Berkus Method and Payne Scorecard Method
The Berkus Method and Payne Scorecard Method valuation methods are continuation from our qualitative evaluation method. Following the qualitative evaluation process using the Scorecard Method, a list of startups in similar industry and development stage in recent period will be compiled. The average valuation of this list of startups is calculated to provide a base valuation.
The qualitative evaluation from the scorecard method provides a total score of 1 or 100% for a startup. We will assume the average score of each startup compiled in our list has an average score of 0.7 or 70% and use that as a baseline. We will then calculate the valuation of the startup using the below formula.
= Scorecard Score / Baseline Score x Average Startup Valuation
For example, assuming that startup XYZ has a score of 80% from our scorecard evaluation and based on a list of similar startups raising at similar stage, the average valuation of those startups is $5 million. Our expected startup valuation is then calculated as:
80% / 70% x $5 million = $5.7 million
Using an uncertainty factor of 0.10, we then set a valuation range $5.7 million +/- 10% for the startup we are valuing.
This method is our preferred method for valuing a startup as it is able to capture the intrinsic value and the potential of a startup better. It is intuitive and helps explain why a startup is valued better or worse than other companies currently operating in the market. Despite all that, it can be biased at times as it can be influenced by the experience and information available to the person doing the analysis.
2. Market Multiple Method
The Market Multiple Method is a relatively simple valuation method that indicates what the market is willing to pay for a company. Using this method, we compile a list of startups in similar industry and stage of growth, calculate the revenue multiple of each startup based on their valuation and average them up to get an average market multiple for these startups.
We then forecast the next 2-3 year of annual revenue of the startup we are valuing and calculate the average of the annual revenue. The expected valuation of the startup is calculated by multiplying the average annual revenue with the average market multiple.
Expected Valuation =
Average Annual Revenue (2 – 3 years) x Average Revenue Multiple (Market)
For example, assuming that startup ABC has the below revenue forecast.
Year 1: $200,000
Year 2: $400,000
Year 3: $1,200,000
Average Annual Revenue = $1,800,000 / 3 = $600,000
Below is a list of startups that had also raised funding in similar industry and stage of growth. We compile the revenue multiple for each startup based on their valuation at time of funding.
Startup DEF: 10
Startup XYZ: 14
Startup ZZZ: 18
Average Revenue Multiple = 42 / 3 = 14
Expected Valuation =
$600,000 x 14 = $8,400,000
Using a an uncertainty factor of 0.25, we then set a valuation range $8.4 million +/- 25% for the startup.
This method is quick and easy. It is mainly used to supplement the valuation calculated using the scorecard method to check if there is any major mistakes made when estimating the valuation using the scorecard method.
3. Discounted Cashflow Method
The Discounted Cashflow Method estimates the value of a startup based on its expected future cash flows. There are two key parameters that influence the valuation estimation using this method:
- Discount Rate
- Expected Cashflow
The discount rate can be thought of as the expected rate of return or the risk premium for investing in a venture. So how can we estimate this discount rate?
Discount Rate = Risk-free Rate of Return1 + Market Rate of Return2 x Risk Factor3
- Risk-free rate of return is the return expected if deployed in risk-free assets such as debt obligations issued by the US Department of the Treasury (Treasury bills, bonds, notes)
- Market rate of return is the expected return the market has on similar ventures. This is extremely difficult to estimate as this may vary for different investors.
- The risk factor measures the risk premium placed on an investment. This is also extremely difficult to measure.
For simplicity and practicality sake, we will simplify the definition of discount rate as the expected rate of return an investor would like for them to invest in the startup. We recognise that different individual has different risk appetite and portfolio make-up. Hence, if an investor feel that they would require a 20% return for them to invest in a particular startup, then that’s the discount rate that will be used for the discounted cash-flow calculation.
The next thing is to forecast the expected cash-flow for the startup. Generally, a startup will provide a very rough guidance on what they plan to achieve from a financial standpoint in the next 18 – 24 months in the offer document. They typically also provide information about their plan and what they expect out of the execution. Based on those information, a cash-flow forecast will be estimated. Different calculations may apply to different business model.
Discounted Cashflow at Exit =
CF1 / (1 + r) + CF2 / (1 + r)2 + CFn / (1 + r)n
CF = Expected Cash-flow
1, 2, …, n = Number of years where n is the number of years to exit the investment
r = Discount Rate
Expected Valuation =
TV / (1 + r)n + Discounted Cashflow at Exit
TV = Terminal Value i.e. expected valuation of startup at exit
See below an example of the valuation estimated for startup JKL using the Discounted Cashflow Method. Let’s say the hypothetical discount rate is set at 50%.
|Year||Cash Flow||Discounted Cash Flow|
Terminal value is then estimated based on industry valuation of a mature company operating in the industry similar to startup JKL. For example, if startup JKL is operating in the ride-sharing space, then terminal value is estimated using valuation multiples for companies like Uber, Ola, Didi, Grab etc. Assuming the average earning multiple for these companies is 15.
Discounted Terminal Value = 15 x $8,000,000 / (1 + 0.5)5 = $15,800,000
Expected Valuation =
$15,800,000 + $3,213,989 = $19,023,989
Using a an uncertainty factor of 0.25, we then set a valuation range $19 million +/- 25% for the startup.
This method is typically a challenge to implement especially for pre-revenue companies or startups due to the uncertainties around future cashflow. This method is also not versatile enough as a calculation only applies to specific scenarios or execution plan presented by the startup at a point in time. But as we know, startups do pivot from time to time, and plans change all the time. The scorecard method of valuing based on the “factors of production” of a startup such as characteristics of the founding team and solution model is far more versatile as these are the key factors that will drive the startup forward, not the execution plan that was presented at the time of funding. As the saying goes,
Hopefully this helps explain the analysis done for the startup we are covering. We will continuously improve and update our methodology to provide better analysis and coverage. Please feel free to provide any comments and feedback or your take of a better way to value a startup.
- The Five Reasons Why Startups Succeed, According to a Legendary Investor
- Why Some Startups Succeed (and Why Most Fail)
- 4 Step Guide to Evaluate Startups and New Venture Ideas
- 5 Things VCs Evaluate before Funding Early Stage Startups
- Valuing Startup Ventures
- 10 Step Guide to Evaluate a Startup
- Peter Thiel on the 7 Questions a Startup Must Answer
- 10 Real-World Startup Valuation Methods