Benchmarking the MuleSoft IPO in two charts

March 13, 2017

A tech IPO is a bizarre way to celebrate success: after putting in years of sweat equity building companies from scratch, the payoff for founders and management teams involves subjecting themselves to a forum in which anyone is free to buy shares in their company and tell others what they think it is worth. Often, this involves levels of abstraction, with investors responding to the broad menu of options by simplifying companies down to their financial metrics. I know from personal experience that without this abstraction public markets investors couldn't do their jobs, and the vast majority (sorry, algo-driven quant funds) do it with keen awareness that there is wondrous complexity behind the numbers: buildings full of people and Kind bars, corporate cultures, products with less bugs every day and most importantly stories of survival and growth against the odds from humble beginnings. 

 

Unfortunately, as a VC it is hard to have to have the time to know the full story behind each new public company, though it is easy to appreciate the magnitude of what they've achieved. What I can do, though, is show how I would go about thinking about the MuleSoft IPO in my old role as an investor in public companies.

 

Though many factors go into valuation, the two most significant ones for most companies are growth and profitability. When evaluating an IPO, the first thing I do is build a basic financial model and benchmark my favorite financial metrics against the other models I've built. This was a daily routine in my past life covering tech stocks and can be a helpful lens for evaluating companies, though again it is just a starting point for more detailed fundamental analysis. Two simple charts can tell us an enormous amount about how a new issue will fit into the public SaaS ecosystem: 

 

First, I look at my preferred measure of SaaS growth (year over year gross profit growth) plotted against a measure of SaaS profitability (free cash flow margin). There are lots of puts and takes to both of these metrics which will end up as separate posts, but the underlying idea holds regardless of what growth/profitability metrics one chooses: for a given level of growth, higher margins are better and for a given level of margins higher growth is better. 

 

Of course, in SaaS models it is hard to have both- since companies are spending up front to acquire recurring revenue streams, those at high growth rates are justifiably loss-making. This plays out in the data, as we see a clear negative correlation between growth and profitability. 

 

MuleSoft (MULE), however, joins elite company: of the SaaS companies on which I maintain detailed financial models, only Shopify grew faster last year, yet MULE ran admirably close to FCF breakeven. 

Second, turning to valuation- we can use the same metrics from the above chart (FCF margin and GP growth), but add them together and plot them against my preferred valuation metric- enterprise value to forward gross profit (again, the choice of this metric is a complex question that deserves its own post). Note that the gross profit estimates are pulled from my own models of these companies since consensus estimates on GAAP gross profit are hard to come by. Despite that, we see clearly that investors put quite a bit of stock in these two backward looking factors when arriving at a forward multiple: we don't even need a statistical tool to tell use that the fit is pretty nice, though wide disparities in valuation are still present in the middle section. 

 

MULE is inserted here based on top of the IPO range ($14/share or a $1.8bn enterprise value using the fully diluted share count), and it looks like the bankers have done a pretty good job pricing it to sell- it isn't hard to see it trading into the 11-13x gross profit range and still fitting into the existing SaaS valuation paradigm nicely. 

 

Note: These actually aren't my preferred metrics, as  FCF can be misleading without adjusting for the dilutive effect of share based compensation, but they ARE the metrics that the market seems to care most about today based on my work. 

 

 

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