What is a fair salary in a Nordic-based startup?

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Arkwright X

5 min readFeb 26, 2020

One of the hardest things to do in business, is finding the right price. Whether it is the price of a product, a service, a company or simply the price of a great team. For a startup, finding the right team, and making sure that they stay satisfied and motivated, is crucial for successfully scaling the business. Offering the right salary is an important part of this equation, but, unfortunately, there is limited data and transparency on this topic today.

Arkwright X work and meet with talented startups every day. We follow the Nordic startup scene closely and know the highs, the lows and the many challenges new businesses must overcome on their way to success. Together with Danske Bank, and with the support of StartupLab and a range of fantastic partners across the Nordic region, we set out to gather the necessary data to get a better understanding of salaries in the startup scene, in each of the Nordic countries. This resulted in the Startup Salary Survey, which is a guide to help entrepreneurs, investors, candidates and others benchmark the price of startup talent.

In this post we wanted to share some of the salary benchmarks from the report, which we have found to be the very useful (no, we are not biased…). If you want to read the full report and lots of interesting findings, you can find it via the link below.

Link to full report
(don’t worry, it’s free)

Briefly about the study

The study is a collaboration between Arkwright X and Danske Bank, supported by StartupLab and a range of great partners. The study is based on an online survey among startup employees, with an impressive 689 relevant respondents holding various positions and with a wide variety of backgrounds and experiences from the Nordic countries; Denmark, Finland, Norway and Sweden.

Small disclaimer: The data presented below serves as a benchmark for annual startup salaries for each of the Nordic countries. Bear in mind that the data presented includes base salary and bonus only — not equity or other perks.

How we split the data

We gathered a lot of data and could have shown a variety of things but have tried to boil this down to what we find most important. The way we have done this is by categorizing the data and setting up two different data splits, which we present in the following section.

Data split 1: Seniority and Company size

Seniority is split into three subcategories being

CXO
Senior employee
Regular employee

Note: you can find the exact definitions of each of the subcategories in the appendix of the full report.

Company size, which is measured based on # of employees, is split into intervals of:

1–10 employees
11–50 employees
50+ employees

Data split 2: Function and experience

Function is split into four subcategories being:

Management
Technical
Sales
Business/Operations

Note: you can find the exact definitions of each of the subcategories in the appendix of the full report.

Experience is split into intervals of:

0–4 years of experience
5–9 years of experience
10–14 years of experience
15+ years of experience

Since we published the report in early 2019, we have received some great feedback on how the salary data is used. Startups, recruiters and candidates crosscheck the different data categories to create a range of what a fair salary for the specific position should be.

Let’s take an example of how this works:

We are a Norwegian company
We are approximately 30 employees today
We are looking to hire a ‘senior resource’ (which in the survey was defined as a ‘Head of unit/department’ or simply as a ‘senior resource’)
The person will work with Business / Operations
Preferably the person has around 5–7 years’ of working experience

What is a fair range for the base salary + bonus?

With the data given above, we would create the range based on the two rows highlighted below.

Thus, we would look at an annual salary range from 549.00 NOK — 605.000 NOK as a starting point.

Further, as we understand that salaries are affected by a range of factors, which aren’t shown here, such as relevant work experience and the offered equity package, we would look at the data distribution as well. This can also help us understand if the averages we are considering might be skewed by outliers.

Below, you will find the data for Denmark, Finland, Norway and Sweden.

Important: be aware that once you start slicing the data, there will be a few splits where we either have no responses or very few (as you will see below), so always make sure to check the distribution in addition to the average figure to avoid being misguided by outliers.