In this series of posts I will examine the compression in tech valuations (as measured by the Enterprise Value/Revenue ratio).In this first post I will take a look at what exactly happened and look a little beneath the surface at some of the underlying trends.
In the second post I will focus on the causes of the upheaval in valuations and finally in the third post I will look to the future and highlight some of the possible and probable valuation trends for the remainder of 2016.
Measuring Valuations for Tech Companies
The received wisdom for tech company valuations, especially young fast-growing companies, is that they should be valued on a multiple of revenue. There are two primary reasons for this, firstly fast growing tech firms rarely have any significant profits (and so ratios such as Price/Earnings or multiples of Net Income will not be useful). Secondly, revenue is a relatively ‘clean’ metric as it is less prone to manipulation and earnings management than figures lower down the Income statement such as Net Income or calculated metrics such as EBITDA.
I will examine other valuations methods and metrics in a future article but for now the primary metric will be the Enterprise Value to Revenue ratio. Enterprise Value (EV) takes market capitalization as its starting point and then adjusts this for the firm’s debt and cash balances to get a more comprehensive valuation (for a more detailed explanation, please refer to Damodaran’s overview of valuation methods).
How Have Valuations Changed?
The compression in the Enterprise Value/Revenue multiple has been extensively documented but just for completeness note the below graph with shows the median EV/Revenue ratio for Saas companies declining since 2013 from a high of 11 in early 2014 to a low of 4 in February 2016.
EV/Revenue Mulitple For Saas Companies
Despite the recent proliferation of blog posts about the ‘Great Compression’, the trend is the trend is not new – the peak in valuations was in early 2014. Most of the commentary on this compression in valuation ratios has focused on Saas companies, so it is worth looking at other tech sectors. The below graph shows the ratios for Digital Media (Google, WebMD, Yahoo, Pandora), eCommerce, Marketplaces and Legacy Tech (comprising mature tech companies such as Microsoft, Oracle and Computer Associates).
There are a few interesting things to note here. Firstly, Legacy Tech has been immune to the trend of valuation compression with its valuation ratio actually increasing from 2.2 in early 2013 to 3.4 in March 2016. Digital Media, eCommerce and Marketplaces ratios have all peaked from Dec 2013 to Dec 2014 and suffered declines since. eCommerce companies have the lowest valuations with the median EV/Revenue ratio at just 1.4.
Before examining the reasons for this compression we can take a closer look at the individual valuations within the averages, in particular the range of the valuations. In March 2013 there was a wide spread of EV/Revenue valuation ratios for Saas companies ranging from 2.75 (for LifeLock) to 31 (for Workday). By March 2016 the range was from 1 (Bazaarvoice) to 11 (Workday).
This can be better illustrated by using fitted normal distributions for different time periods (these distribution curves show frequency for different values of EV/Revenue). The graph below shows the distributions on March each year starting 2013. The graphs graphically illustrate the decline in the average value for Saas EV/Revenue multiples (note that the average is the peak of each graph which has consistently shifted lower – it to the left) more notably the distributions are more compact with March 2016 showing most companies clustered around the mean EV/Revenue of 4 versus the very spread out March 2013 distribution.
- EV/Revenue ratios for Saas, Digital Media and eCommerce companies hit their peaks in 2014 and have been declined since. Legacy Tech companies (such as Oracles) have seen the valuations ratios steadily increase (albeit from a low base).
- eCommerce companies continue to attract the lowest valuation ratios.
- Individual company valuations are now more tightly clustered around the averages with far fewer outliers.
In the next post I will examine the causes of the compression in valuations.