Value Determination For Tech Companies

As our venture capital ecosystem grows it becomes more important than ever to be able to assess the value of technology companies. It is a complex process which most of the time requires professionals in the space to evaluate future performance rather than historical performance.

It is for this reason that we have developed special methods of evaluating companies in Venture Capital, aka the VC Method. It is not taking away from the processes I have discussed in previous blog articles but provides a more realistic perspective.

The first thing you need to know about the VC Method is that is assuming that whenever you invest in a company its value goes up by the amount invested. Imagine a company that is worth $10m pre-money (pre-investment round), an investor wants to invest $1m. The round the company is worth $11m, so the investor only has a 9% stake in the company not as you might have been tempted to believe.

The second thing you need to know is that the purpose of the valuation dictates the type of results and the way you can manipulate the data.

Assume that you want to use the valuation of the company to determine the value of a company today, and you assume the company should at least in theory achieve binary results in 5–7 years (80% fail or 20% exit).

You will probably look at their projections over the next 5–7 years and create a DCF model, consider that money today is worth more than money in the future (Time value of money 101). For any DCF to work you will have to think about the exit value at the time where you normally want to divest the interest, perhaps it is a revenue multiple in line with the market expectations or current exit multiples from M&A Data.

Now you need to understand what the Discount Factor (DF) will be, the rate at which future projected cash loses its value.

The VC Method thinks about outcomes in terms of probability so that should also apply to the expected Discount Factor.

DF Rate is usually the Weighted Average Cost of Capital (WACC) which involves some thinking about whether the company will use any debt at all and the cost of debt over the period. It also involves the expected return for the investor (cost of equity) which is usually very high. Most fund economics work if they are at least able to return their LPs capital with a hurdle rate of 8% (annualised) over a 10-year lifecycle in most cases.

WACC = E/V x Ce + D/V x Cd x (1-T)

Where:

  • E = Value of equity
  • D = Value of debt
  • Ce = Cost of equity
  • Cd = Cost of debt
  • V = D + E
  • T = Tax rate

The added complexity for the VC Method is that once you do have a DF Rate you need to adjust it with the probability of success for similar companies in the market, considering the point in the lifecycle where the VC invests. The later stage the high the probability of success.

The Rate of Discount for VC valuations ends up something like this:

  • Rvc = {[(1+Rd)/p(success)^¹/t]-1}
  • Rvc — Rate of Discount for VC valuation
  • Rd — usually the WACC
  • p(success) — the probability the company will succeed
  • t — time periods you are accounting for in the prediction (5–7 years)

It is important to consider the impact this has on one’s decision to invest or on fund economics, yet it remains an approach that can account for the high rate of failure and thus provide an illustration of a more accurate reality of the expected returns in the portfolio.

It also calibrates the often excessive projections of growth balancing the diversion between DCF and other techniques of valuating a company, such as multiples where the company is compared in relative terms with companies similar where data is available.

Personally, I find some comfort in looking at companies through the lenses of probability, departing from the robust way DCF has been applied in other areas of finance where there was a better understanding of financial performance.

It can be used to determine the right stake the fund needs to acquire to realise the level of returns they expect.

Of course, it has limitations especially pre any type of data on performance, where the founders' ability to negotiate and some comparables that might be able to dictate where the valuation should be.

The value determination process for a venture company in my view must include the following:

Quantitative

  • An understanding of its historical performance, including but not limited to sustained revenue growth, users or customer growth, Cost of Acquisition and Lifetime Value of each user/customer, cohort analysis (retention of users over a 12-month period in probabilistic terms)
  • An understanding of projected performance and probability of success helps create a Discount Cash Flow valuation over the specified lifecycle of the company in the portfolio (usually 5–7 years)
  • An understanding of how the company performed against a specific benchmark (similar companies in the market) in terms of revenue / EBITDA / Profit or Contribution Margin → Multiple analysis
  • An understanding of similar companies (competitors) and their valuation at each funding round
  • Factors that will influence valuation and in general modelling: cyclical nature of the business (seasonality), market competitors and how crowded their addressable market and region is, pricing policy and how competitive it is compared with other providers of similar services/tech/product
  • Size of the market, structural changes in the dynamic of the market (incumbent tech providers disrupting large monopolistic providers)

Qualitative

  • The expertise of the team and previous entrepreneurial success
  • Exits of the founding team and whether they were VC backed
  • Board of advisors, links to industry
  • Key talent from other high growth companies
  • The purpose of the valuation can also inform the approach (new funding round, acquisition, EMI schemes or other employee’s incentives)
  • The parameters of the valuation can provide an indication of how the company can position itself based on a sound commercial and financial assessment of its potential

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