I’ve often found it helpful to have on hand a simple model showing the impact of each financing stages on all team members, suitable for sharing with everyone in the company. I couldn’t find one online, so I built it.
Download the Startup Options Valuation model here.
In particular, this model is designed to help all team members understand the impact of dilution on their options. It’s very powerful to have a model that you can email to everyone in the firm, because then everyone sees clearly that you’re communicating the exact same message to the whole team (including outside consultants and the advisory board, if any). Such a model is particularly helpful for those founders looking for a co-founder or key employee.
While working on my most recent startup, Navon Partners, we were fortunate to have Raul Trevino, a star former Citi investment banker and Columbia MBA, interning with us. Like me, he had the pleasure/pain of being trained as an investment banking analyst. Since he graduated, he’s now Founder and CEO of a Latin America-focused based startup, Participa.me (“I participate”). He wrote the following guest blog post, and worked closely with me to develop this financial model. We had a simple balance sheet by financing round model in our earlier master template financial model, but this model is more suitable for use in employment negotiations.
This capital table startup options valuation model was created with the purpose of valuing options for an illiquid, early-stage start-up. It is particularly valuable for founders because it allows them (and their employees) to assess equity compensation in the form of options paid out to founding team members and other key employees. To illustrate dilution effects, we show a couple of investment rounds (angel and VC) as well as employee option increments at different stages.
In my previous life as an investment banking analyst at Citi (Latin America industrials group), we used to spend hours deriving the appropriate weighted average cost of capital (WACC) for a particular company. We used to take medians and means of unlevered betas of different subsets of comparable companies. Daily updates of the risk-free rates and corporate bond spreads were mandatory, even if the movement from one day to the other consisted of only a couple of basis points. In banking, a lot of my time was spent on modelling cash flows. Projections were based on dozens of operational assumptions related to pricing, production, marketing spend, etc. Market assumptions including market share and macroeconomic data were also in order. Finally, financial assumptions such as capital structure and taxes had to be considered. After capturing all of these assumptions into the model, we had to do sensitivities on the dozen or so that were most important.
In the discounted cash flow (“DCF”) methodology, the terminal value carries a lot of weight and can make up to 70% (or in some cases more) of the total value of the firm. Needless to say, a lot of time and analytics was dedicated to the terminal value. Given all the tweaks and adjustments involved in calculating the overall value of a standalone firm, one can only imagine the wide range of valuations that we came up with. In the end, we presented the results that made the most sense to our senior bankers and to our clients. As I heard David Teten once say “if you torture the data enough, it’ll confess”.
Valuing startups is a far fuzzier process. In particular, most valuations are negotiated rather than derived from any real numbers, like a cash flow. This space is very different from what I had learned in investment banking. When I interned at Navon Partners last summer, I was both surprised and humbled when I realised that I did not know the first thing about valuing start-ups. Vinicius Vacanti and Jim Moran of Yipit had the same experience . Projecting cash flows with any sort of accuracy is difficult at best; the WACC becomes the investor’s required return, and the terminal value is anyone’s best guess.
To bring the case in point to life, I will introduce my startup, Participa.me. Participa.me is an online marketplace of qualified freelancers focused on Latin America (initially Mexico, my native country). To the best of my knowledge, there are no direct competitors in Mexico or Latin America. For my start-up, I built a very robust operational and financial model with a detailed revenue build up and a validated cost structure.
Despite having confidence in my financial projections, I am realistic enough to admit that at this stage (pre-revenues) and with no real comps, it may be hard for potential investors to believe them. (I’m hopeful that they will change their minds soon enough after getting some external validation from potential customers!).
The valuation method I discuss here is how people (other than friends, family and fools) really invest in early stage companies. Compared the DCF methodology, it is quite simple and is based on one thing: returns, based on a range of possible outcomes. Each fund or individual investor has a hurdle rate and based on that they choose whether they want to invest or not. By definition, IRR is calculated using amount invested, amount received at some point in the future, and time passed between the two cash flows. When an investor looks at a company, he projects himself into the future and calculates the value of the company at that point in time. Based on his ownership share of the company at that point (most likely a diluted percentage), he figures out his take-home amount. Couple with his personal hurdle rate and take-home amount, he figures out what his post-money share of the company must be today, in order for him to make that personal hurdle rate.
To illustrate the VC method with real numbers, let’s walk through the attached model for valuing start-ups.
The good news for us engineers (me, by academic training) that favour science over art in valuation is that there is real data out there to justify the returns that angel investors seek. According to the Kauffman study “Returns of Angel Investors in Groups“, the mean IRR of angel investments hovered around 27% as of November 2007. As a classic VC rule of thumb, according to John Frankel of ff Venture Capital and others, a third of startups are zero’s, a third are boring, and the remaining third are where the returns are. If a third of those, or about 10% of the portfolio, work out then you have home-run returns. The bottom line is that that the top 10% of deals provide 90% or so of the returns. (John points out that at ff Venture Capital, we invest heavily in our winners as they start to pull away from the pack, so that even if a third of our companies fail it is not a third of our capital.)
Based on these estimates from some domain experts, we built the attached model to figure out how much a startup at its earliest stage could potentially be worth at exit based on different capitalisation rounds and how much could the payout be for a founding partner. If you have any comments or questions, please enter your comments at the bottom of this blog post.
Download the Startup Options Valuation model here.
Photo credit: dierken