[won't be up-to-the-minute accurate, of course, and won't work for all jurisdictions. But it's a data source that far too few people use, IME]
Smaller companies don't need to publish P&L and cash flow. They can just publish a summary balance sheet. However, if you have the summary balance sheet for two consecutive years, then you can calculate the profit or loss.
About 60% of companies file accounts electronically using XBRL/iXBRL (rather than paper), and these accounts are available for free via daily/monthly zip files published on the Companies House web site.
Too bad they can't be even close to used to predict the revenue of my SAS apps (so far....). Then we have the train of weekly "Sorry users, we are shutting down" posts here on HN (unlikely to happen if they are pulling in ~200K per employee no?).
There is a lot of variation. I view this method with more than a little skepticism.
Search them for free here: http://nuggety.com/u/nuggety/company-or-business-search
Also, btw, I tried nuggety just now and got prompted to sign up for D&B for every search on their site.
The OP method is much simpler and at least as accurate.
If I squint, I can imagine it being related to a few things. Average salary at a SASS startup is roughly the same across startups. Marginal revenue is very high. And then there's something about keeping revenue and costs pretty close even though the entity is in 'start-up mode'. Or perhaps that's more a function of average round size and average targets for making the round last.
Still seems weird that this would come close. Or maybe it's bogus...
This, by the way, is why the multiplier is lower for well-funded companies - if they have more runway in the bank, they'll feel better about a lower level of revenue per employee, since they don't have to operate at a profit in the short term.
Well-funded companies have extra money to spend so they'll have more people than their revenues would indicate, which is simulated by dividing their revenues by a lower cost per employee. (Conversely for poorly funded companies...)
Can somebody explain?
Start ups which are growing quickly can operate at a loss, supported by venture capital, and thus may have lower revenue per employee.
Hence the "value per employee" has to be higher.
That said, there's lots of very important metrics to understand if you're trying to do a comparison - rate of growth, margins, churn, etc. - all of these figure prominently into the health of a SaaS business.
As such, even 1 correction is kind of twiddly, since it does pretty good with average salary. But, its also in that range where you can do it off the top of your head in conversation, by simply referencing a well known labor number, and a +/- factor that most entrepreneur folks you're having drinks with will know.
However I know that one of our competitors had 7 employees in their first year and, because they mistakenly published their full accounts, I also know they made just £80k of revenue that year.
So it doesn't necessarily apply to all companies.
Just absurd.. what about 90% of all those startups that fail that have venture capital and have 10+ employees?
What the article shows you is how to compute the burn rate of your competitor. It proves nothing about revenue. Therefore, most VC-funded companies can afford to have a high burn rate with no revenue [until they fail].
The math works if you assume your competitor is established and stable. But if you are entering the market, you'd like to know how you are impacting your competitor, and that method won't help at all.
A reason why it may: VC advise start-ups on what their run-rates, burn-rates, and staffing levels should be. VC operate on standard formulae.
One result is that you'll see a fairly strong pattern.
Or at least that's my hypothesis.
Phenomena and relationships such as this are why there may be relationships between data patterns, though causality may not be on the basis that's first apparent. And why there may be strong autocorrelation between variables.
