2 reasons why GIS jobs pay $19,049 less

Out of all the things I love about the geospatial and GIS industries, there are two that I have always taken issue with.

The first is that more technical skills are not always taught in GIS, and if they are they require going back for a certificate or masters program (the only reason I am not discussing this today is because I don’t have any data on that topic, yet).

The second, and the likely reason why you opened the newsletter today, is the salary gap between comparable positions in the GIS and non-geospatial worlds for a nearly identical position. What I mean by this is that a GIS Analyst is usually paid less than a Data Analyst. I estimated this gap to be, at least in the US where I am based, somewhere between $12 to $20k per year. I pulled some data from two job websites that have average salaries for the entire US, as well as my own data.

Now the data that I pulled is from this video where I break down the salary gap but also the skills gap. The main take away is that the only major difference in the actual skills required for GIS jobs that differ from a Data Analyst, is the use of GIS software. So let’s break down the two main reason why that salary gap exists in the first place.

Skills

The way I define skills is that they are tool agnostic. To borrow from a cooking example if you can cook a burger that is a skill. But if you know how to cook a burger for McDonalds, that is actually a process. Making a McDonalds burger is so systematized that it requires more attention to following the right steps and times, rather than skills to know how to form, season, cook, and assemble a burger.

The way we learn and practice traditional GIS is comparable to the way that burgers are cooked at McDonalds. We have a set of clear instructions and steps to complete a certain process. Open this menu, click this option, adjust these parameters, etc. I think that the procedural nature of it is a bit masked by two things.

The first is the education and theory attached to these process. Many of us who have gone through a traditional GIS or Geography education have learned about the theory of different spatial analyses in a higher education setting. So we understand what is happening in that process and the reasons for using that process, yet when we go to use it we are dropped into a McDonalds kitchen to press the right button and flip the right switch to complete it.

The other is the cartographic design element. There are many amazing maps produced every year with new designs, styles, and techniques that provide a certain amount of artistic expression in the geospatial process, I ultimately believe that this freedom of expression detracts from the fact that the underlying process to get there remains relatively unchanged. If you want to break out of the constraints of the system you are using, apply a slightly different technique, or use larger scale data, you are likely in for a rough road ahead.

Even if you make it look new and different, a Big Mac is still a Big Mac.

On the other hand Data Analysts start from a place that is tool agnostic – meaning that they need transferable skills to perform the analysis they need to. That includes you sing the right tool for the job, be it SQL or Excel, Python or PowerBI. The analysis they do is really left up to them to perform; to use techniques and strategies that they choose to apply using the tools that best fit the job – much like the chef making the perfect burger.

And that brings me to my next point.

Value

Much of the work that GIS Analysts do is tied to a specific project. It has a specific scope, start, duration, and end. While you may be working on more than one project at a time, the fact remains that the value that you produce, or the leverage, is directly linked to your time and ability to produce projects.

What I mean by this is that if you spend most of your time working on and delivering against things like creating maps or dashboards, rather than tools that help others access self service insights, you are likely not gaining the leverage that you need. I have heard of organizations that produce tens of thousands of maps each year. They are more or less a production factory for providing an actual map for a specific need – request comes in, map comes out.

What these teams could do to increase their value and their leverage is create automated data pipelines or interactive tools that already have those data points and insights and are being updated without extra input from the user, or from you as the creator.

This may seem counterintuitive – by working less (meaning creating a data pipeline or automated insights once) you are actually delivering more value?

I think this has been something that has been drilled into the core of GIS at all levels. Many GIS programs still have a big focus on map presentations and posters as a core deliverable from some courses. And even at the Esri User Conference, the Map Gallery is one of the big draws at the event – and all of those maps are focused on one person creating a single output.

Imagine if the Map Gallery was called the Insights Gallery? What if there was not a map but just an output of any form and they were judged based on how much value was derived from that insight pipeline, how fast stakeholders could access those insights, and how automated it was to produce?

That change in mindset is critical to making the leap. The best Data Analysts and Data Scientists know this and judge their work on insight delivery, rather than how many dashboards they were able to produce. And that, in my opinion, is reflected in the salary gap between the two roles.

By changing the thinking around how to approach skills as a chef and creating value rather than output, I hope that this will start to change the dynamic for the GIS field and ultimately increases the value for those in the field, both in terms of impact and salary.

If you made it this far and are interested in joining my new membership community focused on problems like these, you can learn more here.