Note: this data is from <a href="https://www.sequoia.com/" rel="nofollow">https://www.sequoia.com/</a>, which is a company unrelated to Sequoia Capital.
The data points on pay gap by gender and ethnicity are ones I’ve not seen before and it’s great that this dimension is visualised.<p>A surprising finding here - that doesn’t match what I would have expected - is how Engineering is compensated 90% in cash. I would have assumed equity is pretty heavy for software engineers, especially in senior and above positions.<p>I do wish there were more takeaways to what seems to be data confirming these:<p>1. Compensation is going up, and especially software engineering compensation.<p>2. Startups are starting to compete stronger on cash compensation (thanks to a strong funding environment, and the market).<p>3. Remote work is slowly eroding regional differences in the US (and, as a note, globally, as well).<p>Sadly, there’s no data on remote work here, nor is there anything on what % the market moved up the last year in various disciplines. At least for engineering, the past year has been a major jump upwards in compensation.
Carta releases an Annual Equity Report with similar compensation analysis across race, ethnicity gender. <a href="https://www.cartaequitysummit.com/2021-report/" rel="nofollow">https://www.cartaequitysummit.com/2021-report/</a>
Interesting to see the pay gap charts.<p>> our gender gap data shows that companies are still struggling to offer their female and BIPOC workers equal pay for equal work<p>Does this data account for levels or years of experience? For example, if there are more junior-level women in the industry than senior-and-above level women, then of course you'd expect women to earn less, percentage-wise.<p>If it's not accounted for, then the quoted statement seems false.<p>Similarly, how come asian workers are left out in the following statement:<p>> With a broad stroke, male and White/Caucasian workers simply earn more than their counterparts.<p>It seems asian workers earn even more so it's weird how only white/caucasian is called out.
The average salary distribution is surprising to me. I find myself right in the middle of the distribution (~50th percentile), and yet I know for a fact that I have the highest salary out of everyone in my social circle, which includes several competent workers in the same field. I also believe other data suggests that my household income puts me at least in the top 10% of earners. How can these both be true at the same time? Do these data really represent the state of the general labor market?
My female colleague used to hypothesize why men earned more in general.<p>She said that, if we take an average male and female that have no skills whatsoever, male can still be a coal miner or do a construction job or be a mover better.<p>This means male inherently has higher earning potential. It makes sense that male earns higher.<p>As a side note, I appreciate she talked about this at work openly. As a male, I am scared to discuss such a thing at work.
Definitely interesting to look at the Pay Gap charts. But it might be interesting to see what the pay gap is after looking at hourly wage.
I often hear this argument that men work longer hours. Given how much data they have presented, will definitely be worth looking at that dimension too.<p>Edit: In S/W that might not matter at all, but some business functions hours might matter. More data the merrier.
Charts tend to misinterpret, or not reveal the whole picture.<p>I would be cautious when reading these kinda charts from non-scientific community.<p>Who knows what kind of biases are lurking there at data collection and interpretation level
"With a broad stroke, male and White/Caucasian workers simply earn more than their counterparts. "<p>Why does this sentence leave out Asian workers, when the Asian workers' bell curve actually skews towards even more pay than White/Caucasian workers'?
I was surprised by gender pay gap that follows tenure. Very interesting. Would have expected that total pay gap exist since proportion of women in junior engineers is higher than in senior engineers.<p>Interesting stuff for future perhaps: foreign vs. domestic; and breaking out Chinese + Indian at least for Asian.
For a company in the west, it would be nearly suicide, to discriminate women. So based on this assumption, I think there are other reasons for the 'pay gap'. Actually to really measure it, you should create a sample of companies and go from company to company analyzing any 'pay gaps' including all the factors, like reduced work time. Would not wonder if the graph flips after analyzing it this way.
I'm having trouble understanding what companies or industry these data reflect. <a href="https://dataforest.sequoia.com/about/#methodology" rel="nofollow">https://dataforest.sequoia.com/about/#methodology</a><p>Is this startups? All companies? Are food processors and cement producers and machine shops included here?
It would be great if that conversation around diversify started including original social class diversity as well: if your tech companies are hiring more diverse minority candidates, but they all had lawyer/upper class parents, did you fix anything? Probably not.
The data is apparently from their own employee surveys and includes "a minimum participation standard of two hundred companies but can often grow to include thousands of companies."<p>Hard to know how much you can trust the results with a small and biased sample like this.
Sequoia designers, this is beautiful but it would be great not to rewrite my scroll functionality. Why in the world would I want implied momentum in my scrollwheel? I already know how to use my mouse and am happy with it.