3 ms·
This! In addition to all of the above, it is very hard for the candidate to judge what "0.X % of the company" is worth. Like if one gave up, say 50,000 in salar
by harikb 7y ago
This! In addition to all of the above, it is very hard for the candidate to judge what "0.X % of the company" is worth. Like if one gave up, say 50,000 in salary, is the equity worth that much or some good multiple of it.
The "preferred shares" and various other gimmicks played by VCs mean they might let the "current value" appear inflated than it really is. I have seen startups "start" with a valuation of "50 million dollars" out of thin air. No sales, no product, but a combination of confusing paperwork makes it appear as if someone recently "invested at that valuation". It will be too late by the time you find that the investor was nothing other than the founder, who found a creative way to value his/her time or seed money.
Another major mistake made by new candidates is to miss the fact that there is a vesting period - the upfront large amount means nothing if you quit after a year. On top of it one may not even get any new ISOs in future years. Companies always show "current-year salary + total ISO issued" as "total compensation" - that is absurd. Even if you know what you are doing, you will fall for it after 10 repetitions.
- jaz46 7y agoThe standards that have us thinking about this in terms of % ownership of the company is part of the problem IMO. Future rounds and other factors can quickly make this calculus impossible or with 1000% error margin. IMO, the correct way to approach this is keep everything in terms of $$ values. There is available research online that can allow you to aggregate data for comparable companies on things like: "if the preferred shares price was worth $X per share at the series A, what was the that same share worth at IPO/acquisition?" It's still not easy to answer as the data is sparse and widely varying, but thinking in these terms normalizes the conversation around dollars and gets rid of the "what dilution might happen" part of the equation. For example, my company is in the open source data infra space. So while its hard to get very many data points, trying to get info about the preferred and common share prices at each round and all the up to IPO of companies like MongoDB, Hortonworks, Elastic, Cloudera, etc -- even though they all raised totally different number of rounds and IPOed at different valuations -- in aggregate you can start to build an insightful picture.