Freelancers and Employees in the Data Visualization Industry

Insights from the Annual Data Visualization State of the Industry Survey 2021
by Kristin Baumann

Wherever you look, data is getting collected in one way or another. Therefore the need to find insights in large data sets and make them easily understandable using visualizations is constantly on the rise. More people are joining the data visualization industry and have to decide how they want to work in it. So what are the differences between freelancers and employees?

The following analysis based on results from the Annual Data Visualization State of the Industry Survey conducted by the Data Visualization Society will provide some answers and might help you in the decision process on whether to join as a freelancer or an employee and evaluate possible work environments.

Interested in a specific aspect? Skip ahead to Positions, Target Audiences, Communication Channels, Technologies, or Conclusion.

Freelancer or Employee

The chart below shows the distribution of the respondentsā€™ roles grouped to differentiate between employees, freelancers, and others. They described their roles by selecting up to seven options in this multiple choice question, resulting in many different role combinations.
The majority of the respondents are solely employees. People who work exclusively as freelancers make up only about a fifth of the number of employees. But there is also a considerable number of people who work simultaneously in a permanent position as well as self-employed.
Other role combinations (like respondents who selected that they are hobbyists, students, or academics) make up smaller proportions when viewed individually.

The following sections analyze the responses differentiated between freelancers and employees based on the answer to this first question. To get distinctive results while maintaining enough data points, the definition is as follows:
  • Employees: Respondents who answered by only selecting "Position in an organization with some dataviz job responsibilities" and no other role
  • Freelancers: Respondents who selected at least "Freelance/Consultant/Independent contractor" and not "Position in an organization with some dataviz job responsibilities" ( this allows role combinations like freelancer and students or freelancer and academic)

Positions - Which hat are you wearing?

The subsequent dot plot indicates that the positions that people fill in teams - and with that, the tasks they are undertaking - are quite different for freelancers and employees.
The majority of freelancers are working mostly as designers, also as analysts or developers, while employees are mostly analysts and more often in leadership roles.

Target Audiences - Who is (hopefully) seeing your vis?

The respondents answered that they created their vis for specific audiences. These target audiences varied quite a lot.
Employees made their visualizations mostly for executives, product or project managers, or (other) analysts. Freelancers also targeted these same groups, but less often since they mainly produced their visualizations for the general public, executives, researchers, or policymakers.

Communication Channels - How do you present your finished work?

Creating an intriguing data vis is important, but also needs the proper delivery to your target audience.
The top three communication channels - presentations, dashboards, and documents/reports - are similar for both employees and freelancers.
But stronger differences follow: freelancers rely on web pages, social media, scrollytelling, or physical displays (like a print or installation) more often than employees. Employees prefer sending their work via emails.

Tools & Technologies - How do you create your vis?

The dot plot below demonstrates that the top three tools are similar for both employees and freelancers, with the tool of choice being Excel by a significant margin, followed by Tableau and PowerPoint.
While employees also fall back on PowerBI, freelancers prefer using Adobe Illustrator or just pen and paper. In general, respondents prefer coding in Python, R, and D3.


Looking only at the strongest differences between employees and freelancers, two stereotypes emerge:
On one hand, there is the freelancer who is more focused on the creative side, a designer using Illustrator to create visualizations for a scrollytelling website or social media to target the general public or specific decision-makers.
On the other hand, there is the employee, an analyst or manager who is creating data visualizations with Excel, Tableau, or PowerPoint and delivers them to executives via presentations, dashboards, or even Email.

Of course, the reality is way more diverse than these stereotypes are. The perfect working environment one can thrive in means something different for everybody. I hope this analysis helps you in your decision process on whether to go freelance or work in a permanent position - or even do both simultaneously šŸ¤ž


Project by Kristin Baumann as part of the Data Vis Society Challenge 2021. Github Repo

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