Can a dashboard bust the myth of a tech bias?
TL;DR: Did you also miss the dashboard where you can explore the salary data in more detail and reduce the tech bias?
Jump directly to the dashboard (in another article)
GET REMINDED ABOUT THE NEXT SURVEY by submitting your e-mail
The Berlin Salary Trends Survey, published a good month ago, was a massive success and is here to stay. It was also a lengthy report with plenty of charts and text. I can’t blame you for skimming (50% of Handpicked readers have never noticed it). But maybe some readers were too fast on pulling the tech bias revolver on social media.
Here, for example, is the most upvoted comment from the r/Berlin post:
The data doesn’t lie: 401 (41,3%) respondents said they work in the “Technology/Software development” industry. But does that mean all of them are software engineers?
We also had a lot of “non-EU” respondents (436, 45%). But are all of them working in tech? According to the latest Destatis data “non-German” population in Berlin is 22.2% (out of these, 29.2% is EU). An anonymous survey clearly can’t be representative, but it’s probably not off by factor 25. So we won’t be rebranding anything.
Parts of the commentariat agreed with the comment, and it’s okay. Still, I figured: what would happen if there was a dashboard where you could check this data yourself?
Well, you’re not gonna believe this… but there was a dashboard! 😅 I just failed to present it more prominently, so most readers never saw it.
What is hiding in the data?
One of the primary motivations for doing the survey was to have independent data points besides those from Kununu, Glassdoor & Co. We made it happen, and tech bias doesn’t matter. (addition on 27.8 after this thoughtful comment on Reddit: actually, bias is unavoidable)
A big part of removing the tech bias is the dashboard. We can use it to look for specific data points.
So let’s dig in.
Here is the link if you are restless, and here is what it looks like:
First, I tested ChatGPT Code Interpreter and calculated:
- Average annual bonus in Berlin (245/970 respondents): €12,482.43 with a Median €7,000
- Average Equity Compensation in Berlin (187): €28,089.87 with a Median €15,000
Afterwards, I spent 30 minutes using the dashboard and here are the results:
- The average annual gross salary per 40h week in Berlin was €73,438
- The median annual gross salary in Berlin was €70,000
But you can see that in the picture above. 🤝 (these are also the numbers that triggered tech bias the most)
So, let’s see where the dashboard filters get us!
If we exclude Technology and Software as an industry, we get (569):
- Average (40h): €69,216
- Median: €65,000
If we exclude Non-EU, we get (507) :
- Average (40h): €71,094
- Median: €63,000
If we exclude Non-EU and Technology and Software, we get (323), this time visually:
If we only look at Non-EU, we get (463):
- Average (40h): €75,999
- Median: €73,000
This means that foreigners are getting paid the most, and we can only speculate if all the well-paid German software engineers are in Bavaria and Ba-Wü! 😅 You can check the jobs of the “Non-EU” group by filters too.
How about a random example from another industry? Information & Communication industry (86):
- Average (40h): €75,352
- Median: €71,500
How about only Individual contributors (no management/team responsibility) without Non-EU (357)?
- Average (40h): €66,573
- Median: €61,000
You get the point; there are plenty of filters to play around. You can try it yourself. But, before you jump there, it even gets better: you can also search directly with the role names.
How about if we try “project”? We get:
- Average (40h): €64,793
- Median: €57,000
Sorry, project managers, it pays more to be in “product”:
- Average (40h): €79,624
- Median: €76,500
What about “account”?
- Average (40h): €46,111
- Median: €45,000
This will include Senior Account Managers, Key Account Managers and even Accountants. All are listed in the table below.
You could also start with “junior” and then add a filter for age and get two engineers:
How about “senior”? Or “architect”. Or “actor”. Try for yourself. You can also check your salary by inputting a number and see in which percentile you land.
Fazit: Tech myth at least partially busted. There is much more in the data than tech bias, and I plan to continue with this project next year in exactly the same format.
If you would like to be reminded to participate, drop your e-mail here.
Finally, how does the data compare to official sources?
I could not find anything more recent and better than this from 21.12.2020 (Statistik Berlin Brandenburg):
“The level of average earnings varies considerably by industry and economic sector. In 2019, for example, employees subject to social insurance contributions in the economic sectors of information and communications, financial and insurance services, and energy supply earned an average of between 55,000 and 67,000 euros gross per year. By contrast, earnings in the health, social services, education and training, and services and trade sectors averaged only between 33,000 and 46,000 euros; the hospitality industry brought up the rear with only around 22,000 euros.” (translated by deepl)
So the data we collected is actually pretty reliable and not that far off. Even more, if we look at more recent data per industry:
Thanks for reading, and make sure to subscribe to Handpicked Berlin:
